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Edición Bilingüe Bilingual Edition

Revista Mexicana de Ciencias Pecuarias Rev. Mex. Cienc. Pecu. Vol. 12 Núm 2, pp. 318-664, ABRIL-JUNIO-2021

ISSN: 2448-6698

Rev. Mex. Cienc. Pecu. Vol. 12 Núm. 2, pp. 318-664, ABRIL-JUNIO-2021


REVISTA MEXICANA DE CIENCIAS PECUARIAS Volumen 12 Número 2, Abril Junio 2021. Es una publicación trimestral de acceso abierto, revisada por pares y arbitrada, editada por el Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias (INIFAP). Avenida Progreso No. 5, Barrio de Santa Catarina, Delegación Coyoacán, C.P. 04010, Cuidad de México, www.inifap.gob.mx Distribuida por el Centro Nacional de Investigación Disciplinaria en Salud Animal e Inocuidad, Km 15.5 Carretera México-Toluca, Colonia Palo Alto, Cuidad de México, C.P. 05110. Editor responsable: Arturo García Fraustro. Reservas de Derechos al Uso Exclusivo número 04-2021-051209561700-203. ISSN: 2428-6698, otorgados por el Instituto Nacional del Derecho de Autor (INDAUTOR). Responsable de la última actualización de este número: Arturo García Fraustro, Centro Nacional de Investigación Disciplinaria en Salud Animal e Inocuidad, Km. 15.5 Carretera México-Toluca, Colonia Palo Alto, Ciudad de México, C.P. 015110. http://cienciaspecuarias. inifap.gob.mx, la presente publicación tuvo su última actualización en junio de 2021. Queso criollo en hoja de luna, elaborado para venta en el mercado municipal de Molango, Hidalgo. Fotografía: Griselda Monroy Neria

DIRECTORIO EDITOR EN JEFE Arturo García Fraustro

FUNDADOR John A. Pino EDITORES ADJUNTOS Oscar L. Rodríguez Rivera Alfonso Arias Medina

EDITORES POR DISCIPLINA Dra. Yolanda Beatriz Moguel Ordóñez, INIFAP, México Dr. Ramón Molina Barrios, Instituto Tecnológico de Sonora, Dr. Alfonso Juventino Chay Canul, Universidad Autónoma de Tabasco, México Dra. Maria Cristina Schneider, Universidad de Georgetown, Estados Unidos Dr. Feliciano Milian Suazo, Universidad Autónoma de Querétaro, México Dr. Javier F. Enríquez Quiroz, INIFAP, México Dra. Martha Hortencia Martín Rivera, Universidad de Sonora URN, México Dr. Fernando Arturo Ibarra Flores, Universidad de Sonora URN, México Dr. James A. Pfister, USDA, Estados Unidos Dr. Eduardo Daniel Bolaños Aguilar, INIFAP, México Dr. Sergio Iván Román-Ponce, INIFAP, México Dr. Jesús Fernández Martín, INIA, España Dr. Maurcio A. Elzo, Universidad de Florida Dr. Sergio D. Rodríguez Camarillo, INIFAP, México Dra. Nydia Edith Reyes Rodríguez, Universidad Autónoma del Estado de Hidalgo, México Dra. Maria Salud Rubio Lozano, Facultad de Medicina Veterinaria y Zootecnia, UNAM, México Dra. Elizabeth Loza-Rubio, INIFAP, México Dr. Juan Carlos Saiz Calahorra, Instituto Nacional de Investigaciones Agrícolas, España Dr. José Armando Partida de la Peña, INIFAP, México Dr. José Luis Romano Muñoz, INIFAP, México

Dr. Alejandro Plascencia Jorquera, Universidad Autónoma de Baja California, México Dr. Juan Ku Vera, Universidad Autónoma de Yucatán, México Dr. Ricardo Basurto Gutiérrez, INIFAP, México Dr. Luis Corona Gochi, Facultad de Medicina Veterinaria y Zootecnia, UNAM, México Dr. Juan Manuel Pinos Rodríguez, Facultad de Medicina Veterinaria y Zootecnia, Universidad Veracruzana, México Dr. Carlos López Coello, Facultad de Medicina Veterinaria y Zootecnia, UNAM, México Dr. Arturo Francisco Castellanos Ruelas, Facultad de Química. UADY Dra. Guillermina Ávila Ramírez, UNAM, México Dr. Emmanuel Camuus, CIRAD, Francia. Dr. Héctor Jiménez Severiano, INIFAP., México Dr. Juan Hebert Hernández Medrano, UNAM, México Dr. Adrian Guzmán Sánchez, Universidad Autónoma Metropolitana-Xochimilco, México Dr. Eugenio Villagómez Amezcua Manjarrez, INIFAP, CENID Salud Animal e Inocuidad, México Dr. José Juan Hernández Ledezma, Consultor privado Dr. Fernando Cervantes Escoto, Universidad Autónoma Chapingo, México Dr. Adolfo Guadalupe Álvarez Macías, Universidad Autónoma Metropolitana Xochimilco, México Dr. Alfredo Cesín Vargas, UNAM, México Dra. Marisela Leal Hernández, INIFAP, México Dr. Efrén Ramírez Bribiesca, Colegio de Postgraduados, México

TIPOGRAFÍA Y FORMATO: Oscar L. Rodríguez Rivera

Indizada en el “Journal Citation Report” Science Edition del ISI . Inscrita en el Sistema de Clasificación de Revistas Científicas y Tecnológicas de CONACyT; en EBSCO Host y la Red de Revistas Científicas de América Latina y el Caribe, España y Portugal (RedALyC) (www.redalyc.org); en la Red Iberoamericana de Revistas Científicas de Veterinaria de Libre Acceso (www.veterinaria.org/revistas/ revivec); en los Índices SCOPUS y EMBASE de Elsevier (www.elsevier. com).

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REVISTA MEXICANA DE CIENCIAS PECUARIAS La Revista Mexicana de Ciencias Pecuarias es un órgano de difusión científica y técnica de acceso abierto, revisada por pares y arbitrada. Su objetivo es dar a conocer los resultados de las investigaciones realizadas por cualquier institución científica, relacionadas particularmente con las distintas disciplinas de la Medicina Veterinaria y la Zootecnia. Además de trabajos de las disciplinas indicadas en su Comité Editorial, se aceptan también para su evaluación y posible publicación, trabajos de otras disciplinas, siempre y cuando estén relacionados con la investigación pecuaria. Se publican en la revista tres categorías de trabajos: Artículos Científicos, Notas de Investigación y Revisiones Bibliográficas (consultar las Notas al autor); la responsabilidad de cada trabajo recae exclusivamente en los autores, los cuales, por la naturaleza misma de los experimentos pueden verse obligados a referirse en algunos casos a los nombres comerciales de ciertos productos, ello sin embargo, no implica preferencia por los productos citados o ignorancia respecto a los omitidos, ni tampoco significa en modo alguno respaldo publicitario hacia los productos mencionados. Todas las contribuciones serán cuidadosamente evaluadas por árbitros, considerando su calidad y relevancia académica. Queda entendido que el someter un manuscrito implica que la investigación descrita es única e inédita. La publicación de Rev. Mex. Cienc. Pecu. es trimestral en formato bilingüe Español e Inglés. El costo

total por publicar es de $ 7,280.00 más IVA por manuscrito ya editado. Se publica en formato digital en acceso abierto, por lo que se autoriza la reproducción total o parcial del contenido de los artículos si se cita la fuente. El envío de los trabajos de debe realizar directamente en el sitio oficial de la revista. Correspondencia adicional deberá dirigirse al Editor Adjunto a la siguiente dirección: Calle 36 No. 215 x 67 y 69 Colonia Montes de Amé, C.P. 97115 Mérida, Yucatán, México. Tel/Fax +52 (999) 941-5030. Correo electrónico (C-ele): rodriguez_oscar@prodigy.net.mx. La correspondencia relativa a suscripciones, asuntos de intercambio o distribución de números impresos anteriores, deberá dirigirse al Editor en Jefe de la Revista Mexicana de Ciencias Pecuarias, CENID Salud Animal e Inocuidad, Km 15.5 Carretera México-Toluca, Col. Palo Alto, D.F. C.P. 05110, México; Tel: +52(55) 3871-8700 ext. 80316; garcia.arturo@inifap.gob.mx o arias.alfonso@inifap.gob.mx. Inscrita en la base de datos de EBSCO Host y la Red de Revistas Científicas de América Latina y el Caribe, España y Portugal (RedALyC) (www.redalyc.org), en la Red Iberoamericana de Revistas Científicas de Veterinaria de Libre Acceso (www.veterinaria.org/revistas/ revivec), indizada en el “Journal Citation Report” Science Edition del ISI (http://thomsonreuters. com/) y en los Índices SCOPUS y EMBASE de Elsevier (www.elsevier.com)

VISITE NUESTRA PÁGINA EN INTERNET Artículos completos desde 1963 a la fecha y Notas al autor en: http://cienciaspecuarias.inifap.gob.mx Revista Mexicana de Ciencias Pecuarias is an open access peer-reviewed and refereed scientific and technical journal, which publishes results of research carried out in any scientific or academic institution, especially related to different areas of veterinary medicine and animal production. Papers on disciplines different from those shown in Editorial Committee can be accepted, if related to livestock research. The journal publishes three types of papers: Research Articles, Technical Notes and Review Articles (please consult Instructions for authors). Authors are responsible for the content of each manuscript, which, owing to the nature of the experiments described, may contain references, in some cases, to commercial names of certain products, which however, does not denote preference for those products in particular or of a lack of knowledge of any other which are not mentioned, nor does it signify in any way an advertisement or an endorsement of the referred products. All contributions will be carefully refereed for academic relevance and quality. Submission of an article is understood to imply that the research described is unique and unpublished. Rev. Mex. Cien. Pecu. is published quarterly in original lenguage Spanish or English. Total fee charges are US $ 425.00 per article in both printed languages.

Part of, or whole articles published in this Journal may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying or otherwise, provided the source is properly acknowledged. Manuscripts should be submitted directly in the official web site. Additional information may be mailed to Associate Editor, Revista Mexicana de Ciencias Pecuarias, Calle 36 No. 215 x 67 y 69 Colonia Montes de Amé, C.P. 97115 Mérida, Yucatán, México. Tel/Fax +52 (999) 941-5030. E-mail: rodriguez_oscar@prodigy.net.mx. For subscriptions, exchange or distribution of previous printed issues, please contact: Editor-in-Chief of Revista Mexicana de Ciencias Pecuarias, CENID Salud Animal e Inocuidad, Km 15.5 Carretera México-Toluca, Col. Palo Alto, D.F. C.P. 05110, México; Tel: +52(55) 3871-8700 ext. 80316; garcia.arturo@inifap.gob.mx or arias.alfonso@inifap.gob.mx. Registered in the EBSCO Host database. The Latin American and the Caribbean Spain and Portugal Scientific Journals Network (RedALyC) (www.redalyc.org). The Iberoamerican Network of free access Veterinary Scientific Journals (www.veterinaria.org/ revistas/ revivec). Thomson Reuter´s “Journal Citation Report” Science Edition (http://thomsonreuters.com/). Elsevier´s SCOPUS and EMBASE (www.elsevier.com) and the Essential Electronic Agricultural Library (www.teeal.org).

VISIT OUR SITE IN THE INTERNET Full articles from year 1963 to date and Instructions for authors can be accessed via the site http://cienciaspecuarias.inifap.gob.mx

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In memoriam Dr. Pino was founder and director of the National Center for Livestock Research (CNIP, for its acronym in Spanish) of Mexico, as part of the work of the office of special studies of the Rockefeller Foundation and the Secretariat of Agriculture and Livestock. Dr. Pino played a fundamental role in the organization of livestock

research

in

the

country,

with

the

establishment of scholarship programs to carry out postgraduate studies abroad for young researchers John Anthony Pino

(before the existence of CONACYT), the development

(January 26, 1926 – April 5, 2021)

of a network of Experimental Stations in the country and modern specialized laboratories. His work

included the development of research in various areas of diagnosis and prevention of animal diseases and zootechnical specialties for the rational intensification of animal production systems. A fact that deserves a special mention is the vision he had on the importance of documenting the research works that were carried out, for which, he founded in 1963 the periodical journal, with peer-review, under the name of Técnica Pecuaria en México, which has been published uninterruptedly for more than half a century to date, now under the name of Revista Mexicana de Ciencias Pecuarias, which is the oldest scientific journal in the sector and one of the longest-lived scientific journals in the agricultural sector, and many other fields of specialty in the country. Dr. Pino was one of eight children of a couple of immigrants to the United States and the only one of them who completed university studies: he obtained a bachelor's degree in agriculture and after World War II, where he participated as an infantry captain, obtained a doctorate in zoology at Rutgers University in 1951, institution where he served as an academic until 1955, when he was hired by the Rockefeller Foundation, institution where he had a brilliant career, including his work in Mexico, which earned him the position of Director of Agricultural Sciences in 1970.

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In his long and brilliant career, Dr. Pino fulfilled several tasks, some of them standing out: Inter-American Development Bank: 1983-1986, Agricultural Division. National Academy of Sciences: 1986-1990. Winrock International: 1990-1995; Trinational Animal Health Research Project: 1995-1996. National Academy of Sciences, Committee on Animal Health, 1968-1972, and 1974-1977; Agricultural Board, 1971-1973. Board on Agriculture and Renewable Resources, 1973-1977 and vice chair, 1983-1989; National Research Council, Board on Agriculture 1985-1990. Board of Trustees, International Foundation for Science, 1987-1991. Board of Directors, GRCS-Diversity Magazine, 1992-1996. Independent Consultant, 1990-2000, work related to agricultural research organizations, the conservation and utilization of genetic resources, rural development and ecosystems. United States Presidential Agricultural Task Force to Peru, 1982. USAID Project Design Team, Indian National Bureau for Plant Genetic Resources; Review of Foundation for Agricultural Development, Dominican Republic. Appropriate Technology Institute, Development of Rural Microenterprises Providing Services to Agricultural Production in the Puebla Region of Mexico. Member of American Association for the Advancement of Science. Co-editor, volume on Immunity to Blood Parasites of Animals and Man, Plenum Press, 1977. Author and co-author of numerous papers and conferences. The outstanding founder of our magazine formed a beautiful family with his wife Edith Norman Pino (departed), with whom he procreated four children: Susanne Eugenia (departed), John (departed), Eugene David and Thomas Michael, and they have eight grandchildren and twelve great-grandchildren. May Dr. John Anthony Pino rest in peace, who left a deep mark on the agricultural scientific development of our country and won recognition as an extraordinary human being among those who were lucky to know and work with him. IV III


REVISTA MEXICANA DE CIENCIAS PECUARIAS

REV. MEX. CIENC. PECU.

VOL. 12 No. 2

ABRIL-JUNIO-2021

CONTENIDO CONTENTS

ARTÍCULOS Articles

Pág. Efecto de la pasteurización en la concentración de diclorodifeniltricloroetano (DDT) y hexaclorociclohexano (HCH) en leche de bovino Effect of pasteurization on the concentration of dichlorodiphenyltrichloroethane (DDT) and hexachlorocyclohexane (HCH) in bovine milk Violeta Trinidad Pardío Sedas, Karla María López Hernández, Argel Flores Primo, Roxana Uscanga Sero………………………………………………………………………………………………………………………………….318 Physicochemical composition, yield and sensory acceptance of Coalho cheese obtained from Zebu’s cow milk Composición fisicoquímica, rendimiento y aceptación sensorial del queso fresco Coalho obtenido a partir de leche de vaca cebú Ingrid Laíse Silvestre de Oliveira, Adriano Henrique do Nascimento Rangel, Rodrigo Coutinho Madruga, Dorgival Morais de Lima Júnior, Rhaabe Dayane da Silva Gomes, Danielle Cavalcanti Sales, Juliana Paula Felipe de Oliveira, Joadilza da Silva Bezerra …………………………………………….337 Traditional ranchero Jarocho cheese: a multidisciplinary study from a typicity approach El queso tradicional ranchero Jarocho: un estudio multidisciplinario aplicando un enfoque de la tipicidad José Manuel Juárez-Barrientos, Pablo Díaz-Rivera, Emmanuel de Jesús Ramírez-Rivera, Jesús Rodríguez-Miranda, Cecilia Eugenia Martínez-Sánchez, Roselis Carmona-García, Erasmo HermanLara……………………………………………………………………………………………………………………………….…353 Efecto de alimentación húmeda de cerdos en finalización sobre el comportamiento productivo, composición de la canal y calidad de la carne Effect of wet feeding of finishing pigs on production performance, carcass composition and meat quality Néstor Arce Vázquez, Hugo Bernal Barragán, Nydia Corina Vásquez Aguilar, Estela Garza Brenner, Fernando Sánchez Dávila, Adriana Morales Trejo, Miguel Cervantes Ramírez……………………………370

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Sperm subpopulations and quality in fractions obtained after single layer centrifugation in fresh normospermic ram samples Subpoblaciones espermáticas y calidad en fracciones obtenidas tras la centrifugación de una sola capa en muestras frescas de carnero normospérmico Carlos Carmelo Pérez-Marín, Ander Arando, Francisco Maroto-Molina, Alberto Marín, Juan Vicente Delgado………………………………………………………………………………………………………………………….…386 Cowpea [Vigna unguiculata (L.) Walp] herbage yield and nutritional quality in cowpeasorghum mixed strip intercropping systems Rendimiento de la planta de frijol caupí [Vigna unguiculata (L.) Walp] y calidad nutricional en los sistemas de cultivo intercalado de frijol caupí y sorgo Muhammad Aamir Iqbal, Asif Iqbal, Zahoor Ahmad, Ali Raza, Junaid Rahim, Muhammad Imran, Umer Ayyaz Aslam Sheikh, Qaiser Maqsood, Walid Soufan, Nesma M.A. Sahloul, Sobhy Sorour, Ayman El Sabagh……………………………………………………………………………………………………………….402 Prevalencia del virus de la leucosis bovina en búfalos de agua en la región centro occidental de Colombia Prevalence of bovine leukosis virus in water buffaloes in West-central Colombia Juan Carlos Rincón Flórez, Edgar Antonio Peláez Peláez, Nathaly Trejos Marín, Juan Carlos Echeverry López, Juan Carlos González Corrales……………………………………………………………………419 Efecto del modelo y material de construcción de la caja y recubrimiento de los panales de cría en la termorregulación y desarrollo de colonias de Scaptotrigona mexicana Effect of model and construction material of the brood box and brood comb coating on the thermoregulation and development of Scaptotrigona mexicana colonies Juan Antonio Pérez-Sato, Hugo Rodolfo Salazar-Vargas, Juan Valente Hidalgo-Contreras, Natalia Real-Luna, Héctor Debernardi-De La Vequia, Roberto De La Rosa-Santamaría………………………….437 Análisis de la rentabilidad apícola por estratos en Aguascalientes, México Analysis of beekeeping profitability by strata in Aguascalientes, Mexico José Inés Zavala Beltrán, Marco Andrés López Santiago, Ramón Valdivia Alcalá, Blanca Margarita Montiel Batalla…………………………………………………………………………………………………………………...453 Tipología y caracterización de cunicultores en los Estados del centro de México Type and characterization of rabbit farmers in Mexico's central states Alejandra Vélez Izquierdo, José Antonio Espinosa García, Francisco Aguilar Romero…………………469 Intracellular survival of Mycobacterium bovis strains with high and low frequency in cattle populations in a bovine macrophage model Supervivencia intracelular de cepas de Mycobacterium bovis de alta y baja frecuencia probado en un modelo de macrófagos bovinos Alejandro Nava-Vargas, Feliciano Milián-Suazo, Germinal Jorge Cantó-Alarcón, José A. GutiérrezPabello………………………………………………………………………………………………………………………………487

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Genealogía y trayectoria artesanal del queso criollo en hoja de luna de Hidalgo, México Genealogy and artisanal trajectory of the criollo cheese in cocoyam leaf of Hidalgo, Mexico Fernando Cervantes Escoto, María Isabel Palacios Rangel, Griselda Monroy Neria, Alfredo Cesín Vargas, Abraham Villegas de Gante………………………………………………………………………………………503 REVISIONES DE LITERATURA Reviews

Índices de eficiencia alimenticia en ovinos de pelo: calidad de la carne y genes asociados. Revisión Feed efficiency indexes in hair sheep: meat quality and associated genes. Review Carlos Arce-Recinos, Alfonso Juventino Chay-Canul, Baldomero Alarcón-Zúñiga, Jesús Alberto Ramos-Juárez, Luis Manuel Vargas-Villamil, Emilio Manuel Aranda-Ibáñez, Nathaly del Carmen Sánchez-Villegas, Ricardo Lopes Dias da Costa………………………………………………………………………523 Bioelectrical impedance analysis (BIA) in animal production. Review Análisis de impedancia bioeléctrica (AIB) en la producción animal. Revisión Larissa Luísa Schumacher, Julio Viégas, Gilmar dos Santos Cardoso, Anderson Bertoluzzi Moro, Tiago João Tonin, Stela Naetzold Pereira, Leonardo Tombesi da Rocha, Ana Luiza Van Caeneghen, Janaína Vargas Teixeira………………………………………………………………………………………………………553 NOTAS DE INVESTIGACIÓN Technical notes

Chemical and biological additives in high moisture triticale silages: Nutritional value and ingestive behavior in sheep Ensilajes de triticale de alta humedad con aditivos químicos y biológicos: valores nutrimentales y comportamiento de ingesta en ovinos Valter H. Bumbieris-Junior, Egon H. Horst, Murilo D. Paranzini, Odimári P. P. Calixto, Edson L. A. Ribeiro, Leandro D. F. Silva, Ivone Y. Mizubuti, Clóves C. Jobim, Mikael Neumann……………………573 Suplementación de ácidos grasos poliinsaturados en el empadre de ovejas nulíparas Katahdin: eficiencia reproductiva y crecimiento pre-destete de las crías Polyunsaturated fatty acid supplementation during breeding in nulliparous Katahdin ewes: reproductive efficiency and pre-weaning growth in lambs Ricardo Vicente-Pérez, Ulises Macías-Cruz, Leonel Avendaño-Reyes, Enrique O. García-Flores, Ricardo Martínez-Martínez, Oziel D. Montañez-Valdez, José A. Reyes-Gutiérrez, Alfonso J. ChayCanul, María M. Crosby-Galván………………………………………………………………………………………….…586 Presencia de aflatoxina B1 en alimentos para cabras en unidades de producción de leche caprina del altiplano mexicano Presence of aflatoxin B1 in goat feed in goat milk production units of the Mexican Highlands José Jesús Pérez González, Salvador Vega y León, Rey Gutiérrez Tolentino, Beatriz Sofia Schettino Bermúdez, Fátima Itzel Martínez Solis, Arturo Camilo Escobar Medina…………………………………..…598

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Predicción de la calidad fermentativa de ensilados de girasol mediante espectroscopía de reflectancia en el infrarrojo cercano (NIRS) sobre muestras secas Prediction of the fermentative quality of sunflower silage by near-infrared reflectance spectroscopy (NIRS) on oven-dried samples Sonia Pereira-Crespo, Aurora Sainz-Ramírez, Dalia Andrea Plata-Reyes, Aida Gómez-Miranda, Felipe González-Alcántara, Adrián Botana, Laura González, Marcos Veiga, Cesar Resch, Roberto Lorenzana, Fernando Próspero-Bernal, Carlos Manuel Arriaga-Jordán, Gonzalo Flores-Calvete…..609 Corbicular pollen spectrum (Apis mellifera) of samples from Huejotitan, Jalisco, Mexico Espectro de polen corbicular de Apis mellifera en muestras de Huejotitán, Jalisco, México Roberto Quintero Domínguez, Lino de la Cruz Larios, Diego Raymundo González Eguiarte, José Arturo Solís Magallanes, José Francisco Santana Michel, José Luis Reyes Carrillo .……………….……621 Eficacia del timol en el control del hongo Nosema ceranae infectando abejas africanizadas Efficacy of thymol in the control of the fungus Nosema ceranae infecting Africanized bees Azucena Vargas-Valero, Roberto C. Barrientos-Medina, Luis A. Medina Medina…………………………633 Caracterización de la curva de lactancia y calidad de la leche en ovejas Santa Cruz ( Ovis

aries)

Characterization of the lactation curve and milk quality in Santa Cruz sheep ( Ovis aries) Ingrid Merchant, Agustín Orihuela, Reyes Vázquez, Virginio Aguirre……………………………………..…644 Optimización de un protocolo de extracción de ADN a partir de sangre bovina hemolizada y coagulada para la detección molecular de Anaplasma spp. Optimization of a DNA extraction protocol for hemolyzed and coagulated bovine blood for use in molecular detection of Anaplasma spp. Tomás Humberto Landázuri Rafael, Andrés Carrazco, Renato León, Lenin Vinueza, Verónica Barragán ………………………………………………………………………………………………………………………..…653

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Updated: March, 2020 INSTRUCTIONS FOR AUTHORS Revista Mexicana de Ciencias Pecuarias is a scientific journal published in a bilingual format (Spanish and English) which carries three types of papers: Research Articles, Technical Notes, and Reviews. Authors interested in publishing in this journal, should follow the belowmentioned directives which are based on those set down by the International Committee of Medical Journal Editors (ICMJE) Bol Oficina Sanit Panam 1989;107:422-437. 1.

2.

3.

4.

5.

6.

Only original unpublished works will be accepted. Manuscripts based on routine tests, will not be accepted. All experimental data must be subjected to statistical analysis. Papers previously published condensed or in extenso in a Congress or any other type of Meeting will not be accepted (except for Abstracts). All contributions will be peer reviewed by a scientific editorial committee, composed of experts who ignore the name of the authors. The Editor will notify the author the date of manuscript receipt. Papers will be submitted in the Web site http://cienciaspecuarias.inifap.gob.mx, according the “Guide for submit articles in the Web site of the Revista Mexicana de Ciencias Pecuarias”. Manuscripts should be prepared, typed in a 12 points font at double space (including the abstract and tables), At the time of submission a signed agreement co-author letter should enclosed as complementary file; coauthors at different institutions can mail this form independently. The corresponding author should be indicated together with his address (a post office box will not be accepted), telephone and Email.

Title page Abstract Text Acknowledgments and conflict of interest Literature cited 7.

Title page. It should only contain the title of the work, which should be concise but informative; as well as the title translated into English language. In the manuscript is not necessary information as names of authors, departments, institutions and correspondence addresses, etc.; as these data will have to be registered during the capture of the application process on the OJS platform (http://cienciaspecuarias.inifap.gob.mx).

8.

Abstract. On the second page a summary of no more than 250 words should be included. This abstract should start with a clear statement of the objectives and must include basic procedures and methodology. The more significant results and their statistical value and the main conclusions should be elaborated briefly. At the end of the abstract, and on a separate line, a list of up to 10 key words or short phrases that best describe the nature of the research should be stated.

9.

Text. The three categories of articles which are published in Revista Mexicana de Ciencias Pecuarias are the following:

a) Research Articles. They should originate in primary

works and may show partial or final results of research. The text of the article must include the following parts:

To facilitate peer review all pages should be numbered consecutively, including tables, illustrations and graphics, and the lines of each page should be numbered as well.

Introduction Materials and Methods Results Discussion Conclusions and implications Literature cited

Research articles will not exceed 20 double spaced pages, without including Title page and Tables and Figures (8 maximum and be included in the text). Technical notes will have a maximum extension of 15 pages and 6 Tables and Figures. Reviews should not exceed 30 pages and 5 Tables and Figures.

In lengthy articles, it may be necessary to add other sections to make the content clearer. Results and Discussion can be shown as a single section if considered appropriate.

Manuscripts of all three type of articles published in Revista Mexicana de Ciencias Pecuarias should contain the following sections, and each one should begin on a separate page.

b) Technical Notes. They should be brief and be evidence for technical changes, reports of clinical cases of special interest, complete description of a limited investigation, or research results which

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should be published as a note i n the opinion of the editors. The text will contain the same information presented in the sections of the research article but without section titles.

names(s), the number of the edition, the country, the printing house and the year. e. When a reference is made of a chapter of book written by several authors; the name of the author(s) of the chapter should be quoted, followed by the title of the chapter, the editors and the title of the book, the country, the printing house, the year, and the initial and final pages.

c) Reviews. The purpose of these papers is to

summarize, analyze and discuss an outstanding topic. The text of these articles should include the following sections: Introduction, and as many sections as needed that relate to the description of the topic in question.

f. In the case of a thesis, references should be made of the author’s name, the title of the research, the degree obtained, followed by the name of the City, State, and Country, the University (not the school), and finally the year.

10. Acknowledgements. Whenever appropriate, collaborations that need recognition should be specified: a) Acknowledgement of technical support; b) Financial and material support, specifying its nature; and c) Financial relationships that could be the source of a conflict of interest.

Examples The style of the following examples, which are partly based on the format the National Library of Medicine of the United States employs in its Index Medicus, should be taken as a model.

People which collaborated in the article may be named, adding their function or contribution; for example: “scientific advisor”, “critical review”, “data collection”, etc. 11. Literature cited. All references should be quoted in their original language. They should be numbered consecutively in the order in which they are first mentioned in the text. Text, tables and figure references should be identified by means of Arabic numbers. Avoid, whenever possible, mentioning in the text the name of the authors. Abstain from using abstracts as references. Also, “unpublished observations” and “personal communications” should not be used as references, although they can be inserted in the text (inside brackets).

Journals

Standard journal article (List the first six authors followed by et al.) I)

Basurto GR, Garza FJD. Efecto de la inclusión de grasa o proteína de escape ruminal en el comportamiento de toretes Brahman en engorda. Téc Pecu Méx 1998;36(1):35-48.

Issue with no volume

Key rules for references

II) Stephano HA, Gay GM, Ramírez TC. Encephalomielitis, reproductive failure and corneal opacity (blue eye) in pigs associated with a paramyxovirus infection. Vet Rec 1988;(122):6-10.

a. The names of the authors should be quoted beginning with the last name spelt with initial capitals, followed by the initials of the first and middle name(s). In the presence of compound last names, add a dash between both, i.e. Elias-Calles E. Do not use any punctuation sign, nor separation between the initials of an author; separate each author with a comma, even after the last but one.

III) Chupin D, Schuh H. Survey of present status of the use of artificial insemination in developing countries. World Anim Rev 1993;(74-75):26-35.

No author given

b. The title of the paper should be written in full, followed by the abbreviated title of the journal without any punctuation sign; then the year of the publication, after that the number of the volume, followed by the number (in brackets) of the journal and finally the number of pages (this in the event of ordinary article).

IV) Cancer in South Africa [editorial]. S Afr Med J 1994;84:15.

Journal supplement V) Hall JB, Staigmiller RB, Short RE, Bellows RA, Bartlett SE. Body composition at puberty in beef heifers as influenced by nutrition and breed [abstract]. J Anim Sci 1998;71(Suppl 1):205.

c. Accepted articles, even if still not published, can be included in the list of references, as long as the journal is specified and followed by “in press” (in brackets). d. In the case of a single author’s book (or more than one, but all responsible for the book’s contents), the title of the book should be indicated after the

X


Organization, as author VI) The Cardiac Society of Australia and New Zealand. Clinical exercise stress testing. Safety and performance guidelines. Med J Aust 1996;(164):282284.

In press VII) Scifres CJ, Kothmann MM. Differential grazing use of herbicide-treated area by cattle. J Range Manage [in press] 2000. Books and other monographs

Author(s) VIII) Steel RGD, Torrie JH. Principles and procedures of statistics: A biometrical approach. 2nd ed. New York, USA: McGraw-Hill Book Co.; 1980.

Organization as author XV) NRC. National Research Council. The nutrient requirements of beef cattle. 6th ed. Washington, DC, USA: National Academy Press; 1984. XVI) SAGAR. Secretaría de Agricultura, Ganadería y Desarrollo Rural. Curso de actualización técnica para la aprobación de médicos veterinarios zootecnistas responsables de establecimientos destinados al sacrificio de animales. México. 1996. XVII) AOAC. Official methods of analysis. 15th ed. Arlington, VA, USA: Association of Official Analytical Chemists. 1990. XVIII) SAS. SAS/STAT User’s Guide (Release 6.03). Cary NC, USA: SAS Inst. Inc. 1988. XIX) SAS. SAS User´s Guide: Statistics (version 5 ed.). Cary NC, USA: SAS Inst. Inc. 1985.

Chapter in a book IX)

Roberts SJ. Equine abortion. In: Faulkner LLC editor. Abortion diseases of cattle. 1rst ed. Springfield, Illinois, USA: Thomas Books; 1968:158-179.

Conference paper X)

Loeza LR, Angeles MAA, Cisneros GF. Alimentación de cerdos. En: Zúñiga GJL, Cruz BJA editores. Tercera reunión anual del centro de investigaciones forestales y agropecuarias del estado de Veracruz. Veracruz. 1990:51-56.

XI)

Olea PR, Cuarón IJA, Ruiz LFJ, Villagómez AE. Concentración de insulina plasmática en cerdas alimentadas con melaza en la dieta durante la inducción de estro lactacional [resumen]. Reunión nacional de investigación pecuaria. Querétaro, Qro. 1998:13.

XII) Cunningham EP. Genetic diversity in domestic animals: strategies for conservation and development. In: Miller RH et al. editors. Proc XX Beltsville Symposium: Biotechnology’s role in genetic improvement of farm animals. USDA. 1996:13.

Thesis XIII) Alvarez MJA. Inmunidad humoral en la anaplasmosis y babesiosis bovinas en becerros mantenidos en una zona endémica [tesis maestría]. México, DF: Universidad Nacional Autónoma de México; 1989.

Electronic publications XX) Jun Y, Ellis M. Effect of group size and feeder type on growth performance and feeding patterns in growing pigs. J Anim Sci 2001;79:803-813. http://jas.fass.org/cgi/reprint/79/4/803.pdf. Accesed Jul 30, 2003. XXI) Villalobos GC, González VE, Ortega SJA. Técnicas para estimar la degradación de proteína y materia orgánica en el rumen y su importancia en rumiantes en pastoreo. Téc Pecu Méx 2000;38(2): 119-134. http://www.tecnicapecuaria.org/trabajos/20021217 5725.pdf. Consultado 30 Jul, 2003. XXII) Sanh MV, Wiktorsson H, Ly LV. Effect of feeding level on milk production, body weight change, feed conversion and postpartum oestrus of crossbred lactating cows in tropical conditions. Livest Prod Sci 2002;27(2-3):331-338. http://www.sciencedirect.com/science/journal/030 16226. Accesed Sep 12, 2003. 12. Tables, Graphics and Illustrations. It is preferable that they should be few, brief and having the necessary data so they could be understood without reading the text. Explanatory material should be placed in footnotes, using conventional symbols.

13. Final version. This is the document in which the authors have already integrated the corrections and modifications indicated by the Review Committee. The works will have to be elaborated with Microsoft Word. Photographs and images must be in jpg (or compatible) format with at least 300 dpi resolution. Photographs, images, graphs, charts or tables must be included in the same text file. The boxes should not contain any vertical lines, and the horizontal ones only those that delimit the column headings, and the line at the end of the box.

XIV) Cairns RB. Infrared spectroscopic studies of solid oxigen [doctoral thesis]. Berkeley, California, USA: University of California; 1965.

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14. Once accepted, the final version will be translated into Spanish or English, although authors should feel free to send the final version in both languages. No charges will be made for style or translation services.

MJ m µl µm mg ml mm min ng

mega joule (s) meter (s) micro liter (s) micro meter (s) milligram (s) milliliter (s) millimeter (s) minute (s) nanogram (s) P probability (statistic) p page CP crude protein PCR polymerase chain reaction pp pages ppm parts per million % percent (with number) rpm revolutions per minute sec second (s) t metric ton (s) TDN total digestible nutrients AU animal unit IU international units

15. Thesis will be published as a Research Article or as a Technical Note, according to these guidelines. 16. Manuscripts not accepted for publication will be returned to the author together with a note explaining the cause for rejection, or suggesting changes which should be made for re-assessment.

17. List of abbreviations: cal cm °C DL50 g ha h i.m. i.v. J kg km L log Mcal

calorie (s) centimeter (s) degree Celsius lethal dose 50% gram (s) hectare (s) hour (s) intramuscular (..ly) intravenous (..ly) joule (s) kilogram (s) kilometer (s) liter (s) decimal logarithm mega calorie (s)

vs

versus

xg

gravidity

The full term for which an abbreviation stands should precede its first use in the text. 18. Scientific names and other Latin terms should be written in italics.

XII


https://doi.org/10.22319/rmcp.v12i2.5483 Article

Effect of pasteurization on the concentration of dichlorodiphenyltrichloroethane (DDT) and hexachlorocyclohexane (HCH) in bovine milk Violeta Trinidad Pardío Sedas a Karla María López Hernández a* Argel Flores Primo a Roxana Uscanga Serrano a a Universidad Veracruzana. Facultad de Medicina Veterinaria

y Zootecnia, Av. Miguel Ángel de Quevedo s/n, Col. Unidad Veracruzana, 91710. Veracruz, Veracruz, México. *Corresponding author: klopez@uv.mx Abstract: Dichlorodiphenyltrichloroethane (DDT) and hexachlorocyclohexane (HCH) are endocrine disruptors whose presence in milk entails a health risk. There is evidence that pasteurization decreases or increases the concentration of organochlorine pesticides in dairy products. The present research evaluated the effect of pasteurization at 63 °C 30 min-1 and 73 °C 15 sec-1 on the concentrations of DDT, HCH and their metabolites in bovine milk, in order to estimate the dietary exposure from human consumption of pasteurized milk. A completely randomized experimental design with two treatments was performed on 100 milk samples collected in Soledad de Doblado and Jamapa, Veracruz, Mexico. Pesticides were quantified by gas chromatography with an electron microcapture detector. Data were analyzed by single-factor analysis of variance (P<0.05), and means were compared with Tukey’s test (P<0.05). The dietary exposure to pesticides was assessed based on the estimated daily intake (EDI) and average daily dose (ADD) in three population groups. Pasteurization at 73 ºC reduced the concentrations of p,p'-DDE, p,p'-DDD, o,p'-DDT, p,p'-DDT and total DDT by 30.94, 44.51, 3.18, 81.23, and 42.82 %, respectively, as well as the concentrations of β-HCH, γ-HCH and total HCH (by 85.68, 18.88, and 99.31 %, respectively). The EDI of total DDT by children, adults, and elderly people was lowest for consumption of milk pasteurized at 73 °C, and that of γ-HCH, for milk pasteurized at 63 °C. The DDP of total DDT decreased with pasteurization at 73 °C. The dietary exposure to DDT and HCH was higher in children. Key words: DDT, HCH, Milk, Pasteurization, Dietary exposure, Children. 318


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Received: 22/08/2019 Accepted: 02/07/2020

Introduction Since 1949, organochlorine pesticides (OCPs), such as dichlorodiphenyltrichloroethane (DDT) and hexachlorocyclohexane (HCH), have been widely used across the world, mainly in agricultural and public health programs for the prevention of pests, weeds and other pathogens in tropical countries(1). In Mexico, DDT was the insecticide used for malaria control; in Veracruz, it was routinely applied in endemic regions until 2003, and γ-HCH (lindane) was used for veterinary pest control(2), since this isomer is considered to be the active element of technical HCH with specific insecticidal properties(3,4). In May 2004, the use of these pesticides was restricted following the entry into force of the Stockholm Convention. The purpose of this international treaty was to protect human health and the environment from toxic, persistent, and bioaccumulative chemicals(5). However, in Mexico and other countries, lindane is used as a seed preservative, as an ectoparasiticide in livestock, and in lotions or soaps for the treatment of scabies and lice in humans(6). Due to their vapor pressure and partition coefficient, OCPs are persistent and mobile compounds present in the environment(7), and, because of their lipophilic nature, they bioaccumulate and biomagnify through the food chain(8,9). DDT and HCH are considered carcinogenic and endocrine disrupting compounds(4,10), whose residues have been reported in animals and humans(11). The half-life of OCPs can range from a few months to several years to decades. The estimated degradation of DDT in soil ranges between 4 and 30 yr(12). Animal exposure to DDT and HCH can increase due to direct treatment with pesticides, inhalation of air, or ingestion of contaminated forage and feed(2). In bovine organisms, OCPs enter the liver after reabsorption and are slowly metabolized before being released into the circulatory system and, eventually, deposited in fat or eliminated through milk, through which they pass to the calf or to the human consumer(9,13). Several studies have demonstrated the presence of DDT and HCH in bovine milk, meat and tissues(9,14,15). Furthermore, bovine milk has been used as an indicator of the persistence of these pesticides due to animal feeding, air inhalation and intensive use in programs for the control of ectoparasites in cattle. Within this context, OCP levels in these foods have been monitored in order to estimate population exposure and potential health risks(16,17). The national production of bovine milk in 2018 was 11.923 billion liters, of which the state of Veracruz contributed 6.0 %. Mexico ranked eighth in milk production worldwide; notably, 319


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the European Union, considered as a geopolitical entity made up of 28 countries, ranked first in milk production(18,19). In Mexico, per capita milk consumption during 2018 was 339 ml/person/day(18). Because of its composition, milk is a complete and balanced food that provides a high content of nutrients in relation to its caloric content, and, therefore, its consumption should be considered necessary from infancy to old age (20). Due to the importance of this product as a food, several researches have been developed with the purpose of reducing the content of OCPs in milk. Abd-Rabo et al(21) reported that pasteurization of buffalo milk at 73 °C caused a 23.07 % decrease in the initial concentration of p,p'-DDE and a 32.85 % decrease in p,p'-DDT, and a 30 % increase in the concentration of p,p'-DDD. Deiana and Fatichenti(22) reported a 6.5 % increase in the concentration of DDT and HCH in bovine milk pasteurized at 73 °C. In contrast, Abou-Arab(23) observed the decrease of -HCH (72.90 and 65.00 %) in bovine milk pasteurized at 63 and 72 ºC. However, little research has been done to evaluate the health risk associated with the consumption of commercially marketed raw and pasteurized milk contaminated with these pesticides(24,25). Abou-Arab et al(26) found that the estimated daily intake (EDI) of -HCH in raw, pasteurized and ultra-pasteurized milk was 0.28, 0.11, and 0.03 µg kg-1 bw d-1, respectively, while the DDT metabolite with the highest EDI was o,p'-DDE (0.48 µg kg-1 bw d-1) from raw milk, and o,p'-DDD (0.60 µg kg-1 bw d-1) from pasteurized milk. Amir et al(17) evaluated the presence of OCPs in various feeds. However, the highest EDIs corresponded to raw milk, with 0.011, 0.074, and 0.103 µg kg-1 bw d-1, respectively, for -HCH, total HCH, and total DDT. Miclean et al(27) reported total EDIs of HCH for women, men and children of 0.002, 0.002, and 0.012 µg kg-1 bw d-1, and of DDT of 0.001, 0.002, and 0.008 µg kg-1 bw d-1, respectively. Based on the above, the objective of this research was to determine the effect of pasteurization at 63 °C 30 min-1 (slow, low-temperature) and at 73 °C 15 sec-1 (fast, hightemperature) on the concentration levels of DDT, HCH and their metabolites (p,p'-DDE, p,p'DDD, o,p'-DDT, p,p'-DDT, -HCH, -HCH, -HCH, and -HCH) in bovine milk from the central agricultural zone of the State of Veracruz, Mexico, as well as to estimate the dietary exposure of population groups of children, adults, and elders to these pesticides contained in raw and pasteurized milk at these two temperatures, by means of EDI and PDD

Material and methods Ten clinically healthy animals over two years old, with more than one calving that were milking in two production units (PU) located in the municipality of Soledad de Doblado (19º03' N, 96º24' W) and Jamapa (19º01' N, 96º13' W), Veracruz, Mexico, were selected. 320


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The municipalities are characterized by a warm sub-humid climate with rainfall in the summer; the annual precipitation range is 900 to 1,100 mm and 1,100 to 1,300, respectively, and the annual temperature range is 24 to 26 ºC(28,29). The study was conducted with the approval of the Bioethics and Animal Welfare Committee of the Faculty of Veterinary Medicine and Animal Husbandry. A total of 100 bovine milk samples (500 ml each) from the first milking of the same selected animals were collected every month during an annual cycle (2017-2018) and transported to the Toxicology Laboratory of the Faculty of Veterinary Medicine and Zootechnics of Universidad Veracruzana in accordance with NOM-243-SSA12010(30). In each sampling, a pool of the samples was collected from both Pus, half of which were randomly assigned to slow pasteurization, and the rest, to fast pasteurization. Thus, 25 out of 100 samples were pasteurized at 63 °C 30 min-1, and the other 25, unpasteurized, constituted the 63 °C control. Likewise, 25 samples were pasteurized at 73 °C 15 sec -1, and 25 unpasteurized samples constituted the 73 °C control. Thus, the mixture of raw milk from different origins made at the collection centers and sold to the dairy industry in the area was simulated.

Milk pasteurization

The pasteurization process was carried out at the Toxicology Laboratory in accordance with the NOM-243-SSA1-2010 standard(30). Briefly: 500 ml of raw milk was heated for slow pasteurization at 63 °C for 30 min, and 500 ml, for rapid pasteurization at 73 °C for 15 sec. At the end of each pasteurization, the samples were rapidly cooled to 4 °C and, once this temperature was reached, immediately centrifuged at 3,500 rpm to separate the fat, which was stored in amber-colored vials labeled and stored at -20 °C until analysis.

Analytical determinations

The determination of the ethereal content of milk was performed using the Gerber method(31), and the concentration levels of DDT, HCH and their metabolites in milk fat were estimated with the modified Murphy methodology(32). All chemicals used in the analyses were Merck’s (Darmstadt, Germany), J.T. Baker’s, and the Sigma-Aldrich Company’s (St. Louis, MO, USA) analytical grade. Each sample was analyzed in triplicate, and the results were expressed as µg kg-1 lipid base. The chemical residues from the analyses stored in amber gallons were collected by the EcoEntorno S.A. de C.V. company, hired by Universidad Veracruzana for the collection of hazardous waste.

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Chromatographic analysis

The concentration of DDT, HCH and their metabolites were quantified on an AgilentHewlett-Packard 6890 Plus gas chromatograph with a 7683 autosampler and a Ni-63 electron microcapture detector. The operating conditions were as follows: injector in splitless mode, a purge flow of 60 mL min-1, a purge time of 0.80 min, and a temperature of 250 ºC, a HP608 column measuring 30 m in length x 530 μm in diameter and 0.5 in μm film thickness, with a constant ultrapure nitrogen flow of 2 ml min-1. The oven was programmed with the following temperature ramp: initial temperature from 80 ºC to 180 ºC at 30 ºC min-1, and from 280 ºC to 10 ºC min-1, sustained during 2.7 min. The run time was 19.03 min; the detector temperature was 320 °C, with a constant nitrogen flow of 30 mL min-1, and an injection volume of 1 μL.

Linearity, limits of detection and quantification

Detector linearity was determined by linear regression analysis, performed by ChemStation software from five points on the calibration curves for each pesticide. Calibration was carried out prior to sample analysis using OCP standards purchased from ChemService (Chem Service, Inc., West Chester, PA, USA) and Supelco (Supelco Park, Bellefonte, PA, USA). Qualitative and quantitative analyses were performed by comparing the retention times and peak area of the sample, respectively, with the calibration reference standards. The limit of detection (LOD) and limit of quantification (LOQ) were calculated for each pesticide according to Su(33). Fortified milk samples with a recovery rate of 91-99 % were used to validate this method. The LOD for DDT and HCH ranged from 0.0004-0.00036 and 0.000020.00031µg kg-1, respectively, and the LOQ ranged from 0.001 µg kg-1 lipid base.

Assessment of dietary exposure to pesticides

Dietary exposure to DDT, HCH and their metabolites was assessed by the estimated daily intake (EDI) and average daily dose (ADD) according to Pandit and Sahu(34). The risk was estimated in three population groups, children, adults, and elders. The EDI was reported as µg pesticide kg-1 bw (body weight) day-1 and was calculated with the following formula: EDI=C_a×F×I; where Ca= mean level of organochlorine pesticide residues in milk samples (µg kg-1 lipid base), F= fat content in milk samples (%), I= milk intake in milliliters per kilogram body weight per day (ml kg-1 bw day-1). The daily milk intake (339 ml per person 322


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day-1) used to calculate the EDIs was based on the per capita consumption of milk in Mexico during 2018, and the average weights per person were 25 kg in children(35), 70 kg in adults(36), and 51 kg in elders(37). The average daily dose (ADD) is the average dose rate in a specific exposure period expressed in mass-time units (µg kg-1 d-1) estimated using the following formula: ADD=C_m×F× I; where Cm= maximum concentration of organochlorine pesticides in milk samples (µg kg-1), F= fat content in milk samples (%), I= milk intake (mL kg-1 bw d-1). The following daily milk intake (mL) and recommended weights (kg) were considered for pesticide ADD in three main population groups: children (480 mL/25 kg)(35), adults (240 mL/70 kg)(38), and elders (310 mL/51 kg)(37).

Statistical analysis

A completely randomized experimental design was employed, with the source of variation being the method of slow and rapid pasteurization of milk to evaluate its effect on the concentration levels of DDT, HCH and their metabolites (p,p'-DDE, p,p'-DDDD, o,p'DDDT, p,p'-DDDT,-HCH, β-HCH, -HCH, and -HCH) in milk. The statistical model of the experimental design was as follows: Yij = µ + τi + ɛij Where: Yij is the response variable (OCP concentration) of the ijth experimental unit (each milk sample) (i and j denote factor level and replication at factor level, respectively); µ is the effect of the overall mean; τi is the effect of the ith treatment (slow and fast pasteurization); ɛij is the effect of the experimental error associated with the ith experimental unit. With the concentrations obtained, a one-way ANOVA (P<0.05) was performed to evaluate the effect of pasteurization at 63 and 73 °C on the mean concentration levels of DDT, HCH, and their metabolites in raw bovine milk. Significant differences between the means were determined by Tukey's test (P<0.05) using the Minitab v.17.0 statistical software.

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Results and discussion Concentration levels of DDT and HCH in raw milk

According to the results (Table 1), the concentrations of p,p'-DDE, p,p'-DDDD, o,p'-DDDT, and total DDT (15.736 ± 8.133, 9.849 ± 5.271, 15.237 ± 9.006 and 26.480 ± 13.880 µg kg-1 lipid base, respectively) of the raw milk used as control pasteurized at 63 ºC were higher (P<0.05) than those of the control milk pasteurized at 73 ºC (3.829 ± 2.172, 4.904 ± 3.493, 3.734 ± 1.526, and 8.920 ± 7.340 µg kg-1 lipid base, respectively. However, the concentrations of total DDT in the control milks did not exceed the Maximum Residue Limit (MRL) of 50 μg kg-1 (lipid basis) established by the Food and Agricultural Organization/World Health Organization(39). Table 1: Mean and standard deviation of DDT, HCH and their metabolites (µg kg-1 lipid base) in control raw milk and pasteurized milk Treatment at 63 ºC 30 min-1 Treatment at 73 ºC 15 seg-1 Control Pasteurized Control Pasteurized Pesticide milk milk milk milk (n=25) (n=25) (n=25) (n=25) a,x b a,y p,p'-DDE 15.736 ± 8.133 10.673 ± 5.682 3.829 ± 2.172 2.644 ± 2.023a p,p'-DDD 9.849 ± 5.271a,x 8.334 ± 4.771a 4.904 ± 3.493a,y 2.721 ± 1.333a o,p'-DDT 15.237 ± 9.006a,x 7.559 ± 4.015b 3.734 ± 1.526a,y 3.615 ± 1.831a p,p'-DDT 13.441 ± 7.905a,x 13.484 ± 6.673a 11.351 ± 6.485a,x 2.130 ± 1.566a DDT total α-HCH β-HCH γ-HCH δ-HCH HCH total

26.480 ± 13.880a,x 0.270 ± 0.154a,x 0.401 ± 0.276a,x 0.511 ± 0.338a,x 0.424 ± 0.229a,x 0.552 ± 0.368a,x

20.170 ± 16.05a

8.920 ± 7.340a,y

5.100 ± 3.210a

0.355 ± 0.137b 0.919 ± 0.062b 0.702 ± 0.236a 1.504 ± 2.379a 1.067 ± 1.076a

0.310 ± 0.111a,x 1.438 ± 0.376a,y 1.187 ± 0.204a,y 0.523 ± 0.346a,x 1.241 ± 0.830a,x

0.543 ± 0.151b 0.206 ± 0.113b 0.963 ± 0.122a 1.504 ± 2.379a 0.684 ± 0.452a

DDT total= p,p'-DDE + p,p'-DDD + o,p'-DDT + p,p'-DDT; HCH total= α-HCH + β-HCH + γ-HCH + δHCH. a,b Values with different letters indicate a significant difference (P<0.05) between columns of the same treatment. x,y Values with different letters indicate a significant difference (P<0.05) between the controls of the two treatments.

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As shown in Table 2, these concentrations detected in raw milk were lower than those recorded in raw bovine milk in the previous study conducted by Pardío et al(40) in the state of Veracruz. Comparing our data with the concentrations of DDT metabolites detected in raw milk from Brazil(24), Colombia(14) and Romania(27), the levels detected in the 63 ºC and 73 ºC control milks in the present study were up to 26 and 11 times higher, respectively. However, in Egypt, the concentration of p,p'-DDDT in raw milk was twice as high as that found in the controls in this research. The β-HCH and γ-HCH concentrations (1.438 ± 0.376 and 1.187 ± 0.204 µg kg-1 lipid base, respectively) of the 73 °C control milk were (P<0.05) higher than those of the 63 °C control concentrations (0.401 ± 0.276 and 0.511 ± 0.338 µg kg-1 lipid base, respectively). Although the total MBM of the 73 °C control milk was 2.24 times higher than that of the 63 °C control, it was not significantly different (P>0.05). The variation in OCP concentrations among the controls may have been due to the indistinct variations in their levels in the milk of each PU throughout the annual cycle. This variation may be attributed to the combination of zootechnical management practices in production units and diets formulated with contaminated ingredients, the effect of kinetics due to the physicochemical properties of each isomer, metabolic activities related to lipid mobilization, and, possibly, a lack of homogeneity in the concentration of metabolites due to the remobilization of lipids and contaminants during milk synthesis, as well as to the application load of the pesticide, since it can be deposited or absorbed from the atmosphere to the surface of the pasture, being affected by temperature, rain, wind and weather(2). The α-HCH, β-HCH, γ-HCH and total HCH metabolites present in the 63 °C and 73 °C controls did not exceed the MRLs established by FAO/WHO, of 50, 20, 10 and 100 µg kg-1 (lipid basis), respectively(39). As shown in Table 2, the concentrations of α-HCH, β-HCH and γ-HCH metabolites evaluated in the present study were lower than those reported by Pardío et al(40) in Veracruz, Mexico. The levels of γ-HCH reported in milk from Tlalixcoyan, Veracruz, Mexico, were 250.3 times higher than those reported in control milk at 63 ºC (0.511 ± 0.338 µg kg-1 lipid base), and 107.76 times higher than those reported in control milk at 73 ºC (1.187 ± 0.204 µg kg-1 lipid base). The concentration of γ-HCH in Egypt was 62.5 times higher than that reported in raw milk at 63 ºC, and 26.9 times higher, in the control milk at 73 ºC. However, the concentration of α-HCH recorded in the Colombian milk was similar to that observed in the control milk at 73 ºC (0.310 ± 0.111 µg kg-1 lipid base).

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Table 2: Organochlorine pesticide residues (µg kg-1 lipid base) in raw milk reported in other studies p,p'p,p'- p,p'o,p'αβγ-

Location/Country

Reference HCH Medellín, 39.000 ND 89.000 26.000 13.000 23.000 49.000 NA Pardío et Veracruz/Mexico al(40) Paso San Juan, 18.000 ND 49.000 ND 13.000 17.000 22.000 NA Pardío et Veracruz/Mexico al(40) Tlalixcoyan, 24.000 ND 36.000 ND 31.00 69.000 128.000 NA Pardío et Veracruz/Mexico al(40) Rio Grande do 0.011 0.000 ND 0.000 0.002 ND 0.006 ND Heck et Sul/Brazil al(24) Cairo/Egypt 12.000 6.000 24.000 3.000 NA NA 32.000 NA Abou-Arab et al(26) Sabanas, ND ND 0.034 ND 0.469 ND ND ND Díaz et Córdoba/Colombia al(14) Rumania 0.011 0.000 0.000 0.000 0.001 0.010 0.002 0.001 Miclean et al(27) DDE

DDD DDT

DDT

HCH

HCH

HCH

NA= not analyzed; ND= not detected.

It should be noted that organochlorine pesticides and their residues are highly lipophilic and persistent in nature, and, therefore, they are easily concentrated in milk fat(26). This implies that, although OCPs were banned for agricultural use in the early 1970s in most countries, their residues still persist. Due to their persistence, the detected concentrations of DDT, HCH and their metabolites in the raw milk of the present study are probably due to the loads of DDT applied during its previous legal use, which has caused the contamination of cattle grazing areas in the state of Veracruz. Likewise, γ-HCH continues to be used for the control of ectoparasites in livestock(2). In fact, these pesticides continue to be applied in various parts of the world because of their potent and broad-spectrum effects against harmful organisms(41).

Effect of pasteurization on DDT and HCH concentration levels

As shown in Tables 1 and 3, after pasteurization at 63 ºC, the concentration levels of the metabolites p,p'-DDE and o,p'-DDDT (10.673 ± 5.682 and 7.559 ± 4.015 µg kg-1 lipid base, respectively) decreased (P<0. 05) with respect to the levels of the control (raw) milk by 32.17 and 50.39 %, respectively, and only p,p'-DDDT increased (P>0.05) in concentration, by 0.31 %, with respect to the control. Therefore, the concentration of total DDT (20,170 ± 16,050 µg kg-1 lipid base) decreased (P>0.05) by 29.83 % with respect to that of the control (26,480 ± 13,880 µg kg-1 lipid base). On the other hand, the levels of α-HCH and β-HCH

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(0.355 ± 0.137 and 0.919 ± 0.062 µg kg-1 lipid base, respectively) increased (P<0.05) by 31.48 and 129.11 %, respectively; however, the increase in the levels of γ-HCH, δ-HCH and total HCH was not significant (P>0.05). The α-HCH and γ-HCH isomers can isomerize to βHCH. The stability of β-HCH, its tendency to accumulate in human and animal tissues over time, its rapid (525-fold) bioconcentration in man, and its slower elimination, represents a risk with respect to its chronic toxicity. This metabolite is the most toxic, followed by α-, γHCH and δ-HCH, due to its longer biological half-life (of 7-8 yr) in the body (ATSDR)(42). Table 3: Variation (%) of the concentration of DDT, HCH and their metabolites due to the pasteurization effect of bovine milk in different studies Type of PEST sample/Provenance

Pasteurization 63 ºC x 30 Pasteurization 73 °C x 15 min-1 seg-1 Reference Decrease Increase Decrease Increase

Buffalo milk/Egypt

p,p'-DDE p,p'-DDD p,p'-DDT

NA NA NA

NA NA NA

23.07 --32.85

--30 ---

Abd-Rabo et al(21)

Bovine milk/Italy

DDT total○ HCH total□

NA NA

NA NA

-----

6.5 6.5

Deiana y Fatichenti(22)

Bovine milk/Egypt

γ-HCH

72.90

---

65.00

---

Abou-Arab (23)

Bovine milk/Mexico p,p'-DDE

32.17

---

30.94

---

p,p'-DDD

15.38

---

44.51

---

o,p'-DDT

50.39

---

3.18

---

p,p'-DDT DDT total α-HCH β-HCH γ-HCH δ-HCH HCH total□

--29.83 -----------

0.31

81.23 42.82 --85.68 18.88 --99.31

----75.16 ----187.57 ---

31.48 129.11 37.37 257.24 93.29

Present studio

PEST= pesticide; NA= not analyzed; DDT total= p,p'-DDE + p,p'-DDD + o,p'-DDT + p,p'-DDT; □HCH total= α-HCH + β-HCH + γ-HCH + δ-HCH.

Pasteurization at 73 ºC reduced (P<0.05) the concentration levels of DDT and its metabolites in milk with respect to the control milk from 3.18 % (o,p'-DDDT) to 81.23 % (p,p'-DDDT). A significant (P<0.05) increase in α-HCH and -HCH levels (0.543 ± 0.151 and 1.504 ± 2.379 µg kg-1 lipid base) was observed at 75.16 and 185.57 %, respectively, and there was a significant (P<0.05) decrease in β-HCH (0.206 ± 0.113 µg kg-1 lipid base), by 85.68 %. The observed decrease in the concentrations of p,p'-DDE, p,p'-DDDD, o,p'-DDDT and total DDT in pasteurized milk at 63 °C compared to the control concentration, except for p,p'-DDDT, could be attributed to the isomerization of p,p'-DDE and p,p'-DDDD to p,p'-DDDT by

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heating. However, the concentrations of HCH and all its metabolites were increased by pasteurization at 63 °C, and α-HCH and δ-HCH metabolites, by pasteurization at 73 °C. Organochlorine pesticides can be degraded by photolysis, hydrolysis, oxidation and reduction, temperature, and pH. The retention of pesticides will depend on the physicochemical properties of the pesticide molecule, as well as of the feed(43). However, the concentration of total DDT in control and pasteurized milk at 63 and 73 °C did not exceed the FAO/WHO MRL of 50 µg kg-1 (lipid basis)(39). Likewise, the metabolites α-HCH, βHCH, γ-HCH and total HCH present in milk pasteurized at 63 ºC and 73 ºC did not exceed the MRLs of 50, 20, 10 and 100 µg kg-1 (lipid basis), respectively, established by FAO/WHO(39). However, the δ-HCH metabolite, whose levels increased in both pasteurizations, is structurally related to carcinogenic HCHs (ATSDR)(42). The results of pasteurization at 63 and 73 °C differ with those found by Abou-Arab(23), who reported a decrease of 72.9 and 65.0 %, respectively, in the concentration of γ-HCH in bovine milk, whereas in the present study this metabolite increased by 37.37 % with pasteurization at 63 °C, but decreased by 18.88 % with pasteurization at 73 °C. In Egypt, Abd-Rabo et al(21) reported that the metabolites p,p'-DDE and p,p'-DDDT decreased in milk pasteurized at 73 °C. The present study shows a similar decrease in p,p'-DDE, but an increase in p,p'-DDDT. The decrease in p,p'-DDD (44.51 %) observed in this study contrasts with the increase reported by these authors (30 %). In Italy, Deiana and Fatichenti(22) reported that the concentrations of total DDT and HCH increased by 6.50 % in bovine milk pasteurized at 73 °C, while in the present study they decreased by 42.82 and 99.31 %, respectively. These results indicate that pasteurization at 73 °C 15 sec-1 reduces the concentration of most of the OCP analyzed. It is important to note that milk is considered a staple product in human nutrition. The benefits of bovine milk are not limited to its nutritional value; these are a factor in the prevention of pathologies such as cardiovascular diseases, certain types of cancer, arterial hypertension, and bone or dental diseases(20). Hence the importance of reducing the concentration of these contaminants in milk by pasteurization, given that their presence entails a risk to public health.

Estimation of dietary exposure to DDT and HCH through human consumption of bovine milk

Estimated daily intake (EDI) of DDT and HCH

In order to protect public health, OCP intake limits have been established for milk and other foods that should not be exceeded. The Acceptable Daily Intake (ADI) of total DDT is 20 µg

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kg-1 bw d-1 recommended by FAO/WHO(39), and 0.5 µg, recommended by the EPA(44); the for γ-HCH (lindane), it is 8 µg(39). Thus, the EDI was calculated for total DDT and the metabolite γ-HCH from the concentration detected in the milks studied for three population groups: children, adults and the elderly. Table 4 shows that in the children's group, the highest EDI was calculated in the 63 °C control milk, which did not exceed the acceptable values recommended by FAO/WHO (20 µg kg-1 bw d-1), but was 28.06 times higher than the levels recommended by EPA (0.5 µg). In the adult group, the highest concentration also occurred in the 63 °C control milk, without exceeding the FAO/WHO recommended values; however, exceeded the EPA acceptable values by 10 times. The EDI of the elderly group was higher for the 63 °C control milk, exceeding the EPA acceptable values by 13.74 times. Abou-Arab et al(26) estimated total DDT EDIs of 0.394 and 0.113 µg kg-1 bw d-1 for adults and 0.475 and 0.135 µg for children, likewise γ-HCH EDIs were 0.280 and 0.113 µg for adults and 0.336 and 0.135 µg for children from consumption of raw and pasteurized (63 °C) milk, respectively, from local markets in Cairo, Egypt. Accordingly, the EDIs in the present study were lower than those estimated in adults and children consuming raw and pasteurized milk in Egypt, because the concentrations of DDT and HCH in that area were higher than those reported in the present investigation. Table 4: Estimated daily intake (EDI) (µg kg-1 bw d-1) of total DDT and γ-HCH for children, adults and the elderly estimated on consumption of raw (control) and pasteurized milk Treatment 63 ºC x 30 min-1 Population Control group milk Total DDT Children 14.03 Adults 5.00 Elders 6.87

Pasteurized milk

Treatment 73 ºC x 15 sec-1 ADI (µg kg-1 bw dControl Pasteurized 1) milk milk 20(39) 0.05(44)

10.68 3.81 5.23

4.72 1.62 2.31

2.70 0.96 1.32

γ-HCH Children

0.27

0.37

0.62

0.50

Adults

0.04

0.06

7.81

0.09

Elders

0.08

0.11

0.19

0.16

8(39)

ADI= acceptable daily intake; FAO/WHO, 1997(39); EPA(44). Total DDT= p,p'-DDE + p,p'-DDD + o,p'-DDT + p,p'-DDT.

The highest γ-HCH EDI in the three population groups occurred in the 73 °C control milk. However, none of the EDIs exceeded the acceptable value recommended by FAO/WHO (8 µg kg-1 bw per day). Pardío et al(40) reported that the EDI for infants and adults from 329


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consumption of raw milk from Tlalixcoyan, Veracruz, Mexico, contaminated with γ-HCH was 0.666 and 0.021 µg kg-1 bw d-1, respectively. However, the EDIs for infants and adults from consumption of raw milk contaminated with total DDT were highest for milk from Medellín, Veracruz, Mexico with values of 0.530 and 0.017 µg kg-1 bw d-1, respectively. In a recent study, Miclean et al(27) reported EDIs of total HCH in raw milk for women, men and children of 0.002, 0.002 and 0.012 µg, respectively; for total DDT they were 0.001, 0.002 and 0.008 µg for women, men and children, respectively, lower than those estimated for total DDT in children in the present study for the consumption of pasteurized milk at 63 and 73 °C and raw milk (respective controls). Comparing the results of Pardío et al(40) with those of the present study, it is observed that exposure to -HCH and total DDT through the consumption of raw milk has increased in the area. The above indicates an increase in contamination over time due to the continued use of -HCH in livestock in the region and the high DDT loads sprayed in the past that resulted in contaminated pastures near urban and suburban areas where DDT was sprayed for malaria control(2). However, 30 to 37 % of the unpasteurized fluid milk of the national production is destined to the production of artisanal cheeses(45), of the production in the state of Veracruz, 50 % of the unpasteurized fluid milk in storage is sold to local cheese dairies for the production of cheese and other artisanal dairy products that are marketed in the main urban areas of the state(46). As a consequence, consumers of milk produced in this agricultural zone of Veracruz are exposed to dietary levels of OPs that are higher than exposure levels in developed countries, where the use of these pesticides was banned many years ago(40). This risk could be reduced if the milk were pasteurized at 73 °C 15 sec-1 to reduce the concentration of most of the OCPs analyzed. As shown in Table 3, according to the literature consulted, very few studies have been conducted on slow and rapid pasteurization and the estimation of the respective dietary intake. Monitoring the levels of these OCPs in milk and other foods is essential to ensure that the MRLs and ADIs recommended by FAO/WHO are not exceeded.

Estimated average daily dose (ADD) of DDT

The ADD is a prediction of the daily intake of residues of a pesticide based on the estimation of residue concentrations in food and on the available food consumption data for a given population(47). For total DDT, the Food and Agriculture Organization of the United Nations (FAO) and the World Health Organization (WHO) have established the ADD of 48 µg kg-1 d-1(45). In the case of HCH, there is no established ADD. The highest estimated ADDs in children, adults and elders, from 63 ºC control milk, were 142.01, 71.00 and 91.72 µg kg-1 d-1, respectively; these values exceed the FAO/WHO recommended limit (48 µg) by 2.9 times in the children’s group, 1.4 times among the adults,

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and 1.9 times among elderly people. After pasteurizing this milk at 63 ºC, the calculated ADDs in the three population groups (114.06, 57.03 and 73.66 µg kg-1 d-1, in children, adults and elders, respectively) also exceeded the recommended limit. Notably, the estimated ADD for consumption of control milk at 73 ºC in children was 59.48 µg, which is higher than the limit recommended by FAO/WHO (48 µg). However, once the milk was pasteurized, the ADD value was 6.15 times lower (9.67 µg) than that of the control milk (9.67 µg). The ADD calculated in adults and elders for the control milk (29.74 and 38.41 µg, respectively) and for milk pasteurized at 73 ºC (18.08 and 23.35 µg, respectively) remained below the limit recommended by FAO/WHO and were lower than those estimated for the consumption of raw milk used as control at 63 ºC. These results contrast with those reported by Pardío et al(40) who estimated lower daily doses for children and for adults (4,068 and 2,339 µg, respectively) who consumed raw milk from Medellín, Veracruz, Mexico. It should be noted that there are certain population groups that are more vulnerable to the effects of these pesticides, such as the child population ―especially those with some degree of malnutrition―, and the female population of childbearing age, particularly during pregnancy, given that there is evidence of their hormonal and lipid disruption activity(48). The effects of OCP exposure to human health through food is a problem that deserves more attention. The results obtained indicate their presence in raw and pasteurized milk and an increase in ADDs, making it essential to review the MRLs and seek alternative pest control methods in order to improve food safety and protect public health.

Conclusions and implications The pasteurization process of milk at 73 ºC reduces the concentrations of the DDT and its metabolites, as well as most of the concentrations of HCH metabolites. Therefore, the thermal process under these conditions represents a favorable alternative for the reduction of dietary exposure to these pesticides through human consumption of pasteurized milk at 73 ºC.

Acknowledgements

The authors are grateful to the Project “Building and Strengthening of Academic Bodies and Integration of Networks” (“Formación y Fortalecimiento de Cuerpos Académicos e Integración de Redes”), code 103.5/03/477 UVER-F-11, PRODEP funds, for funding this study.

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https://doi.org/10.22319/rmcp.v12i2.5600 Article

Physicochemical composition, yield and sensory acceptance of Coalho cheese obtained from Zebu’s cow milk

Ingrid Laíse Silvestre de Oliveira a Adriano Henrique do Nascimento Rangel a Rodrigo Coutinho Madruga b Dorgival Morais de Lima Júnior c Rhaabe Dayane da Silva Gomes a Danielle Cavalcanti Sales a Juliana Paula Felipe de Oliveira d Joadilza da Silva Bezerra e

a

Universidade Federal do Rio Grande do Norte (UFRN), Unidade Acadêmica Especializada em Ciências Agrárias, Macaíba, Brazil. b

Associação Brasileira dos Criadores de Zebu (ABCZ), Brazil.

c

Universidade Federal Rural do Semi-Árido (UFERSA), Departamento de Ciencias Animais. Massoró, Brazil. d

Universidade Federel Rural de Pernambuco, Departamento de Zootecnia. Recife, Brazil.

e

Universidade Federal Rural de Pernambuco (UFRPE), Departmento de Morfologia e Fisiologia Animal, Recife/PE, Brazil.

*Corresponding author: jupaula.oliv@yahoo.com.br

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Abstract: The aims were to evaluate the effect of breed on the genetic polymorphism kappa-casein, physicochemical composition of milk and Coalho cheese, and on cheese yield; and to evaluate the effect of different periods of storage on sensorial acceptance of the Coalho cheese obtained from milk of Guzerat, Gyr and Sindi cows. Twenty (20) cows of Zebu breeds were selected, from which it was obtained the frequency values of the genetic polymorphism kappa-casein. Milk were submitted to fat, protein, lactose, non-fat solids and total solids, electrical conductivity analysis and somatic cell count. Cheeses were submitted to fat, protein, total solids, pH, moisture and yield (g TS/L) analysis. Attributes appearance, aroma, texture and flavor were judged at the 1st, 25th and 46th day of storage. There was a total frequency of 0.70 for genotype AA, 0.30 for genotype AB. There was no significant difference in milk composition among the studied breeds. However, there were differences in the physicochemical composition (with the exception of the protein) and the yield of the cheeses, but all the breeds showed a similar real yield. It was found effect of the storage period on the cheeses sensory attributes in the different breeds, with the exception of the appearance. The milk of the Guzerat, Gyr and Sindi breeds constitute an excellent raw material for the production of curd cheese and ensures a satisfactory sensorial acceptance of the product at the 1st, 25th and 46th days of storage. Key words: Bos taurus indicus, Breed, Consumer, Dairy product, Storage.

Received: 21/01/2020 Accepted: 24/09/2020

Introduction Zebu cattle (Bos taurus indicus) were imported from India to Brazil in the 19th century. It represents more than 80 % of the national herd(1) due to its adaptability and performance in tropical climate conditions and has important participation in the success of cattle ranching in the country. Zebu cows make up the bulk of the Brazilian dairy herd, including their crosses with specialized breeds (Bos taurus taurus) for milk production, especially the Dutch breed(2). Brazil is the largest investor in genetic improvement of zebu cattle in the world(3), involving strategic projects for genetic improvement of zebu animals with milk aptitude, mainly Gyr

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and Guzerat. Current stock data for actions such as these show that the production means at 305 d of the Gyr, Guzerat and Sindi breeds are 11.25 kg(4), 7.46 kg(5), and 5.59 kg(6), respectively. Milk production and quality characteristics are directly influenced by environmental factors, nutrition, genetics and by the animal’s own physiology(7). Breed is a genetic factor with a relevant effect on the productive performance of dairy animals. The physiology of a specialized cow for milk production enables it to produce in large volume, but with low solids concentration, unlike a pure zebu cow with milk aptitude. This occurs because the production level of the cow is negatively related to the fat, protein and total solids percentages of the milk(8,9). Milk proteins can be classified into caseins and whey proteins. Caseins make up approximately 80 % of the milk proteins and are subdivided into 4 fractions: α1, α2, β and K. In the bovine species, genetic markers are used for selecting animals by determining gene pairs (A and B), which are present in milk caseins, such as kappa-casein. In general terms, the A allele has a significant effect on milk production and B allele on protein and fat concentration, resulting in a better yield of dairy products(10). Several polymorphisms have been found for this protein, which is responsible for stabilizing the milk against heat treatments and clot formation(11). The possibility of using milk to obtain dairy products is an important opportunity to add value to raw milk, diversify the product portfolio, and boost the competitiveness and profitability of the sector. Coalho cheese is a traditional dairy derivative of the culture of the Northeast Region of Brazil. It is a cheese obtained by a fermentation and coagulation process of raw or pasteurized milk. Cured cheeses from zebu breeds can already be found in the market, which shows the dairy potential of these breeds for cheese production. However, there are few studies on cheese obtained from zebu milk. Sensory evaluation is the most common method to analyze food quality(12). The sensorial attributes of products can be measured via specific tests, identifying the importance of each of them for their acceptance by consumers(13). Therefore, the aims were to evaluate the effect of breed on the genetic polymorphism kappa-casein, physico-chemical composition of milk and Coalho cheese, and on cheese yield; and to evaluate the effect of different periods of storage on sensorial acceptance of the Coalho cheese obtained from milk of Guzerat, Gyr and Sindi cows.

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Material and methods Determination of the genetic polymorphism of kappa-casein

The steps between the DNA extraction and capillary electrophoresis were developed at the Central Gene Genetics Laboratory of Animal Genotyping Ltda (Belo Horizonte, Minas Gerais, Brazil) using in-house developed protocols. The genomic DNA was extracted from the capillary bulb of each animal, producing a total of 22 samples. Buffered solutions containing a detergent and the tris-hydroxymethyl aminomethane (Tris), sodium chloride (NaCl) and ethylene diamine tetra acetic acid (EDTA) reagents were used for cell lysis. After the DNA extraction, the samples were submitted to the polymerase chain reaction (PCR) technique of the STR regions, using a Veriti™ thermal cycler (Applied Biosystems, Forster City, CA, USA). Microtubes containing the necessary reagents for the enzymatic reaction were placed in the thermocycler: DNA fragments extracted from the capillary bulb, DNA-free water, deoxyribonucleotide triphosphates (dNTPs), oligonucleotide primers, DNA polymerase enzyme, magnesium and buffer solution. The primers used in the reaction were made by Life Technologies. The amplified DNA fragments were subjected to capillary electrophoresis in a laserinduced fluorescence automated system (ABI Sequencer 3500xL) to verify the quality and concentration of DNA in each sample. The band reading was performed using GeneMapper Software®. The fragments were induced to migrate by capillary electrophoresis, and then aligned based on size and detected by a laser beam. In the same run molecular weight standards and AA, AB and BB known samples were applied. Finally, genotypic and allelic frequencies were obtained for the three evaluated breeds after identifying the genetic polymorphisms of the kappa-casein gene by the PCR technique.

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Raw material collection

Raw milk for producing Coalho cheese was obtained from Guzerat (n= 3), Gyr (n= 7) and Sindi (n= 10) females. The collection procedure for analyzing the physicochemical composition of the milk was performed manually using a properly sanitized stainless steel ladle after homogenization of the milk. The samples were conditioned in plastic bottles with a volume of 40 mL, identified individually, and kept in a thermal container with ice to preserve the temperature between 4 and 7 °C until the analysis procedure in the milk quality laboratory of the Federal University of Rio Grande do Norte. Fifteen liters of milk from each breed were also collected for producing Coalho cheeses, which were kept in isothermal containers and sent to the Dairy Processing Unit (DPU) of UFRN.

Coalho cheese production

Cheese production of the three breeds was carried out following the same technological manufacturing process, which was carried out at DPU of UFRN. Milk samples from the three breeds for producing the cheeses were separately subjected to LTLT pasteurization (low temperature, long time 65°C/30 min). After thermal processing, they were cooled to 35 °C for rennet addition (Renin). After homogenization of the ingredients (milk and rennet), the mass was rested for 40 min until reaching the curd point, before cutting. The curd was subsequently heated under manual stirring to 45 °C. Then the whey was partially removed for salting the curd. The pre-pressing and forming procedures were carried out in the form itself for subsequent pressing and turning the curd. The cheese production process is shown in Figure 1. The process was finished with the vacuum cheese packaging and stored at 4 °C in a cooling chamber. The raw material, ingredients and packaging used for the cheese production were handled according to good dairy manufacturing practices.

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Figure 1: Flow diagram for the production of Coalho cheese

Physicochemical analyzes of milk

The milk from the three breeds was analyzed for the fat, protein, lactose, solids-not-fat (SNF) and total solids (TS) percentages by the infrared absorption method in DairySpec FT® equipment (Bentley Instruments Inc., Chaska MN, USA). The electrical conductivity of the milk was measured using a Quimis® digital conductivity meter - ISO 9001 (SP, BR). The Somatic Cell Count (SCC) was estimated using the Somaticell® kit (Madasa, São Paulo, Brazil), following the manufacturer’s recommendations. The SCC value varied from 69,000 cells/mL to 1’970,000 cells/mL.

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Physicochemical analyzes of cheese

After producing the cheeses, 10 grams of each sample were removed and shredded in a Philipis Walita® blender (R12134) to reduce the particles, which were then submitted to physicochemical analysis of protein, fat, total solids, ash and pH. Protein percentage was determined based on the procedure of Cecchi(14). The fat content was determined by extracting the petroleum ether solvent at 90 °C for 1 h using a Ankom® XT15 Extractor (NY, USA), following the equipment instructions. The percentage of total solids of the samples was established by the oven drying method at 105 °C for 6 h and the ashes determined by combustion of the organic matter in muffle furnace at 600 °C for 4 h(15). The pH of the cheeses was determined using a previously calibrated Lucadema® 210 pH meter (SP, BR) with three readings per sample. All physicochemical analyzes of the cheeses were carried out at 46 d of maturation.

Calculation of Coalho cheese yield

The yield of cheeses was expressed in grams of total cheese solids per liter of milk (g TS/L) and calculated by the formula(16):

In which, Y= yield; W= kilos of cheeses obtained; TS= Total solids percentage of cheeses; V= milk volume used.

Sensory analysis

The sensorial acceptance test of the Coalho cheese samples was carried out at the Agricultural Sciences Unit - Jundiaí Agricultural School (EAJ), Federal University of Rio Grande do Norte (UFRN) campus, conducted with 60 untrained female and male participants (18 to 60 yr old) who judged the attributes of appearance, aroma, texture and taste of the Coalho cheeses on the 1st, 25th and 46th days of shelf life. The evaluator selection was performed based on voluntary consent and the absence of allergic reactions to milk and dairy products. The sensory evaluation of Coalho cheese samples was carried out using a hedonic scale of 9 points, anchored at extremes 1 (I highly disliked it) and 9 (I liked it very much)(17). 343


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The tests were carried out by the participants individually in an environment with controlled humidity and temperature (air-conditioned room with air conditioning) in which white light was used, thus ensuring the ideal environmental conditions for conducting sensory analysis. The participants were instructed on all the procedures for conducting the tests before beginning the evaluations. A small portion of a low-salt cracker and a portion of still water at room temperature was offered to be consumed between different samples to clean the palate and remove any residual taste. The Coalho cheese samples (25 g) intended for the tests were kept in ice isothermal boxes until they were served to the tasters in 50 ml white disposable plastic cups. Samples were coded with numbers composed of three random digits using a random number table.

Data analysis

Data analysis was performed using descriptive statistics by mean and standard deviation. The analysis of variance (ANOVA) of the data was performed to evaluate the effect of breed on the physical-chemical characteristics of the milk and cheeses, and on cheese yield. Each evaluator assigned their preference for the sensorial acceptance evaluations of cheeses by acceptability testing and the results were determined by means of the final average score of the scores presented by the judges to the different evaluated attributes in the sensorial analysis and submitted to analysis of variance (ANOVA). The Tukey test was used at 5% significance to compare the means of all analyzes using SAS software (version 9.0).

Results and discussion Genetic polymorphism of kappa-casein

The frequency values of the kappa-casein genetic polymorphism in the Guzerat, Gyr and Sindi breeds are shown in Table 1. There was a total frequency of 0.70 (n= 14) for genotype AA, 0.30 (n= 6) for genotype AB, and 0 for genotype BB. No homozygous BB genotypes were found in this study. These results are in agreement with those reported in other studies, in which they showed a higher frequency of the AA and AB genotypes, and no observation of the BB homozygote in dairy breeds(18,19).

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Table 1: Distribution of the polymorphism frequency of the kappa-casein gene for the analyzed breeds Kappa-casein polymorphism Alleles Breed AA AB BB A B Guzerat 0.66 0.33 0.83 0.17 Gyr 1 0 1 0 Sindi 0.50 0.50 0.75 0.25 Total 0.70 0.30 0.85 0.15 The highest frequency of the A allele in Brazilian zebu herds may be due to the origin of the animals and to selecting meat production at the beginning of their exploitation(20), since Indian zebu animals have a higher frequency of the B allele when compared to the Brazilian averages. Another factor is the number of animals at the effective herd level being selected. Homozygous animals are possibly being chosen for the A allele or using the heterozygotes in smaller proportions. The polymorphism frequency of the kappa-casein gene for the B allele of the three breeds is close to that reported by others(21). The authors analyzed the genetic polymorphism of kappa-casein in Brazilian zebu animals and found a frequency of 30 %, 1-10 % and 18 % of B allele in Sindi (n= 55), Gyr (n= 150) and Guzerat (n= 69), respectively. The selection of AB or BB animals in the kappa-casein genotype is important for dairy derivative production, since the B allele correlates with milk chemical composition parameters, mainly fat and protein, and promotes an increase in yield and cheese quality(10). The cheese yield of cows with genotype BB is higher in comparison to the milk from AA cows, and variant B is determinant in the efficiency process in milk coagulation time. The kappa-casein BB gene pair is correlated to higher processing characteristics, where cows with BB genotype for kappa-casein obtain shorter coagulation time for cheeses, higher density curd formation due to smaller micelle size, as well as higher cheese yield in relation to the milk from cows with AA genotype for kappa-casein(22,23). Thus, this variant can be used as a selection criterion in breeding programs on farms with a cheese-based purpose. The B allele also has a positive influence on milk protein and fat content(24,25); however, as in the present work, some reserchers(26,27) found no effect on the protein percentage produced in animals of different genotypes. Confirming the mentioned studies, the Sindi breed obtained the highest frequency of the B allele (25 %) when compared to the other breeds. This result may have implied the highest percentage of fat and total solids and yield in the cheese obtained from milk of Sindi breed.

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Physicochemical evaluation of milk from zebu cows

The Table 2 shows the means and standard deviation for the physicochemical composition of the milk of the three breeds. There was no significant difference (P>0.05) for milk composition among the studied breeds. Similar results between the breeds can be attributed to the same management conditions employed and the similar genetic potential for milk composition. Table 2: Physicochemical composition of the milk from the Guzerat, Gyr and Sindi zebu breeds Breed Item P-value Guzerat Gyr Sindi Fat, % 5.14 + 1.08 4.81 + 0.67 5.35 + 1.06 0.14 Protein, % 3.12 + 0.48 3.13 + 0.34 3.16 + 0.37 0.24 Lactose, % 4.66 + 0.71 4.68 + 0.51 4.72 + 0.56 0.21 SNF, % 8.51 + 1.29 8.52 + 0.92 8.60 + 1.02 0.12 TS, % 14.16 + 1.8 13.98 + 1.41 14.65 + 1.79 0.18 3 SCC,10 /mL 333.33 + 348.53 243.10 + 248.77 256.87 + 444.65 0.62 ELC, mS/cm 3.94 + 0.33 4.07 + 0.35 3.81 + 0.32 0.34 SNF= Solids-Not-Fat; TS= Total solids; SCC= Somatic cell count; ELC= Electrical conductivity.

Because there is no difference between the breeds, especially in fat and protein percentages, there is similar potential of the three breeds to produce these components. The total solids concentration in milk stands out as the main basis for paying for quality in most countries with a high development rate and in some places in Brazil. In studying electrical conductivity (ELC) and somatic cell counts (SCC) of zebu cow milk, Moura et al(28) found higher values than those reported in the present study, which found 1’629,000 cells/mL for the Gyr breed and 1’356,000 cells/mL for the Guzerat breed, but the results found for ELC are close with results of 3.88 and 3.59 mS/cm for the Gyr and Guzerat breeds, respectively.

Physicochemical evaluation of dairy cheeses from zebu cows

Table 3 shows the mean values for physicochemical composition of the Coalho cheese from the Guzerat, Gyr and Sindi zebu breeds. The results demonstrate that the protein content was similar for the evaluated cheeses (P>0.05). The cheese from the Sindi breed

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presented higher fat and total solids percentages, as well as a higher pH value when compared to those obtained from the milk of the other breeds. On the other hand, the Guzerat cheese obtained lower fat concentration and higher ash concentration, while the Gyr breed had a lower pH value. The fat percentage expressed in relation to the total solids avoids measurement errors in the yield occurring due to moisture loss. Described on a dry basis, the fat values of the cheeses respectively correspond to: 48.12 %, 53.79 % and 54.83 % for the Guzerat, Gyr and Sindi breeds. Thus, the results found are within those established by legislation for Coalho cheese(29), which defines between 35 to 60 % of fat in total solids as standard values. The regulation further states that Coalho cheese may be defined as semi-fat (25.0 to 44.9 %), fat (45.0 to 59.9 %) or extra fat (minimum of 60.0 %) in relation to fat content, and therefore the cheeses in this study are classified as fatty cheeses. Table 3: Physicochemical composition and yield of Coalho cheese from the Guzerat, Gyr and Sindi zebu breeds (Mean + SD) Breed Item P-value Guzerat Gyr Sindi Fat, % 24.26 + 0.51c 27.77 + 0.73b 32.23 + 1.26a <0.05 Protein, % 18.77 + 0.83 17.93 + 1.39 17.91 + 0.55 0.15 b b a Total solids, % 50.41 + 1.06 51.62 + 0.07 58.78 + 1.13 <0.05 a b b Ashes, % 3.30 + 0.01 2.58 + 0.24 2.49 + 0.30 <0.05 b c a pH 6.92 + 0.02 6.28 + 0.05 7.16 + 0.14 <0.05 c b a Yield, g TS/L 82.25 83.33 93.68 <0.05 abc

g TS/L: grams of total solids per liter. Means in the same line with different letters represent differences (P<0.05).

The Sindi breed presented a higher percentage of total solids (TS) in the cheese, conferring greater potential for yield (g TS/L) in producing the derivative. There is still no regulation to standardize the physicochemical parameters of protein and ash, since the production process of most Coalho cheeses is still artisanal. The pH values ranged from 6.28 to 7.16. These results were higher than those found by Araújo and Nassu(30) in evaluating the pH of industrialized and artisanal Coalho cheese, which varied from 5.10 to 5.80. The Sindi cheese had the highest pH (7.16). The Sindi breed obtained higher (P<0.05) performance in the Coalho cheese yield (g TS/L) due to the higher total solids concentration present in the milk. However, by analyzing the real yield (l/kg), all breeds obtained similar yield, using 6.13 (Guzerat), 6.05 (Gyr) and 6.27 (Sindi) liters of milk to produce 1kg of cheese, thereby confirming the potential of all breeds for cheese production.

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Sensory evaluation of milk Coalho cheese from zebu cows

The results obtained from sensory analysis of the Coalho cheese of the three zebu breeds at different storage periods are presented in Table 4. The sensory scores varied from 6.32 (slightly liked) to 7.98 (moderately enjoyed). Coalho cheeses of different breeds presented similar appearance during the storage period (P>0.05). Table 4: Sensory scores obtained on the acceptance test of Coalho cheese from zebu milk at different storage periods (Means+ SD) Sensorial Parameters Breed Day Appearance Aroma Texture Flavor c abc 7.18+1.50 1 6.58+1.53 7.56+0.98 7.70+1.27a 25 7.31+1.48 Guzerat 6.81+1.60bc 7.55+1.18abc 6.51+1.47bc 46 7.38+1.13 7.37+1.10abc 7.71+0.99ab 6.83+1.46bc 1 7.64+1.15 6.84+1.48bc 7.85+1.02a 7.98+1.03a 25 7.59+1.23 Gyr 7.67+1.01a 7.16+1.53abc 6.44+1.49c 46 7.63+0.98 7.58+0.99ab 7.05+1.32bc 6.57+1.44bc 1 7.60+1.26 6.72+1.56c 7.46+1.19abc 7.28+1.47ab 25 7.36+1.28 Sindi 6.91+1.51abc 6.96+1.33c 6.32+1.41c 46 7.52+1.15 7.19+1.47abc 6.91+1.37c 6.60+1.63bc 0.12 <0.05 <0.05 <0.05 p-value abc

Means in the same column with different letters are different (P<0.05).

On the first day of storage, it was observed that the cheeses obtained from the milk of the different studied breeds were similar in appearance, aroma and flavor (P>0.05), while only the texture of the Guzerat Coalho cheese (7.71) differed (P<0.05) from Sindi cheese (6.91) at 46 d of storage, reaching a higher score. The aroma of cheeses on the first day of storage had lower sensory scores (slightly appreciated), possibly due to the effect of coagulant proteolysis which may affect the availability of amino acids for enzymatic degradation (31). Different aromatic compounds are generated throughout the storage period during cheese maturation due to several biochemical reactions(32,33). Cheeses made with cow milk from the Guzerat and Sindi breeds reached similar sensory acceptance (P>0.05) for the texture attribute during the whole evaluation period, while the cheese made with milk from Gyr cows showed the lowest acceptance (7.05) at 46 d of storage (P<0.05) than on the first day (7.85). According to Ordoñez(34), proteolysis causes changes in the texture and consistency of cheeses, which progressively loses its protein structure over the passage of time, thereby conferring greater softness. Another aspect to be

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considered is that the Coalho cheese is characterized by the firm and “rubbery” consistency due to the aggregation of the fat molecules in the casein micelles, forming a kind of sponge, so that Coalho cheeses with a higher fat content, such as Sindi cheese, may be softer and less consistent, and thereby achieve lower sensory acceptance with these characteristics. The cheeses received better (P<0.05) sensory scores (moderately liked) on the first day of shelf life for the flavor attribute. This is because the chemical composition of the cheese (fat, protein and lactose) influences the product’s taste, especially when there is maturation. This behavior occurs as a function of the lipases acting on the lipids, forming medium and short chain free fatty acids, esters, ketones and aldehydes, interfering in the sensorial characteristics of the cheese(35). The consumer market is becoming more and more demanding with the aim to achieve more competitiveness and acceptance by consumers, and so the dairy sector has been seeking greater variety, improved quality and productivity. Products which reach long shelf life without affecting their sanitary, physicochemical and sensory properties are alternatives to boost wholesale and export trade.

Conclusions and implications The milk from the Guzerat, Gyr and Sindi breeds presents favorable physicochemical characteristics for producing Coalho cheeses, obtaining yields higher than 40 %, therefore constituting excellent raw material for producing derivatives. In addition, the cheeses presented satisfactory sensorial acceptance during the studied storage periods.

Acknowledgements

The authors wish to acknowledge Brazilian Association of Zebu Breeders – Regional Technical Office and Sindhi Breeders Nucleus, Natal-RN, Brazil. We give thanks to the CAPES foundation for financial support.

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https://doi.org/10.22319/rmcp.v12i2.5230 Article

Traditional ranchero Jarocho cheese: a multidisciplinary study from a typicity approach

José Manuel Juárez-Barrientos a Pablo Díaz-Rivera b Emmanuel de Jesús Ramírez-Rivera c Jesús Rodríguez-Miranda d Cecilia Eugenia Martínez-Sánchez d Roselis Carmona-García d Erasmo Herman-Lara d*

a

Universidad del Papaloapan Campus Loma Bonita/DES Ciencias Agropecuarias, Av. Ferrocarril S/N, Cd. Universitaria, C.P. 68400 Loma Bonita, Oaxaca, México.

b

Colegio de Postgraduados. Campus Veracruz. México.

c

Tecnológico Nacional de México/Instituto Tecnológico Superior de Zongolica. México.

d

Tecnológico Nacional de México/Instituto Tecnológico de Tuxtepec. Depto. de Ingeniería Química y Bioquímica. Av. Dr. Víctor Bravo Ahuja No. 561. Col. Predio el Paraíso. 68350 Tuxtepec, Oaxaca, México.

* Corresponding author: erasmo_hl@hotmail.com

Abstract: The objective was to integrate the information of the local milk production system, physicochemical and microbiological characteristics of the milk; elaboration process, and physicochemical, microbiological, and sensory characteristics of cheese to establish its typicity. The manufacturing of the cheese in most of the dairies studied has registered the operation of three generations of families. Variability in their chemical composition, microbiological,

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colour, texture and sensory was related with time and number of turns during the pressing, amount of added salt and vegetal fat. Cheeses with less pressing time had higher moisture content and less protein and fat content. The bacterial counts were related to milk quality tests, training courses and material of containers. These factors also affected the hardness of the cheese. Those with added vegetable fat and with high salt content had the highest hardness. The Hue angle (h°) of the cheeses indicated a tonality close to yellow (90°). Difference in chromaticity (C*) can be related to the use of vegetable fat. Cheeses with higher moisture content were brighter (L*) and had less color saturation. The sensory evaluation showed that the most typical cheeses were perceived in the attributes as salty, milk aroma, and serum and milking smell. Applying sanitation measures of milk collection, good cheese manufacturing practices and avoiding the addition of vegetable fat, it could be possibly getting a legalcommercial protection of the ranchero Jarocho cheese. Key words: Raw milk, Traditional cheese, Typicity, Milk production systems.

Received: 26/01/2019 Accepted: 05/08/2020

Introduction Traditional foods express the individual identity of a society and seemed to look as a symbol of heritage. Transmission of knowledge of traditional food occurs between the older and the younger generation(1). The typicity approach allows analyzing traditional foods that are linked to a territory as the result of a social trajectory of manufacturing techniques, where a collective knowledge is developed from the interaction between physical-biological and human factors. The present study starts from the premise that the typicity is established when the information about the milk production system, milk characteristics, processing parameters, physicochemical, microbiological, and sensory characteristics are integrated(2). Generally, the information that is integrated is previously obtained from a multidisciplinary study in which the different disciplines that serve a common objective concur, but the interaction between them does not modify the disciplines individually(3). This integration is important because an incomplete characterization prevents getting some type of intellectual property right(4) since it is necessary to ensure that there is a connection between the extrinsic attributes of the terroir and intrinsic attributes of this product(5).

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In Mexico, traditional cheeses linked to a region are manufactured(6) however, the available information includes the chemical and microbiological quality and production process(7) leaving aside production systems sensory characteristics of the product. Mexican cheeses face a serious problem related to current regulations, since on the one hand it emphasizes the use of standardized and pasteurized milk so that a cheese can be classified as such and on the other hand it allows the addition of milk in powder and other dairy ingredients or not, favoring the proliferation of imitation cheeses(8). In addition to the regulatory problems, there is the lack of experience in the legal framework for Mexican cheeses to obtain commercial protection. In this regard, Cotija cheese is a cheese with a strong link with the territory and the society that produces it, which has been established by various studies that define its typicality integrating the physicochemical, microbiological and sensory aspects. These cheese are the pioneer for the recognition and protection of traditional Mexican food products since, despite not having obtained the designation of origin, it has been granted the collective mark, which has translated into growth for producers and opens the door for other Mexican cheeses(9).

The ranchero Jarocho cheese is a traditional cheese made from raw bovine milk, produced in the cattle areas of Veracruz and her production represents the major source of income for some families. The objective of this study was to apply the typicity approach to integrate the information about the local milk production system, physicochemical and microbiological characteristics of the milk; elaboration process, physicochemical, microbiological and sensory characteristics of the cheese in an interdisciplinary way to generate information that will eventually allow obtaining trademark protection.

Material and methods Study area and characterization of the bovine milk production system The rural development district 008 in the State of Veracruz, Mexico (18º 11 ́ to 18º 45 ́ N and 95º 09 ́ to 96º 37 ́ W) was explored including the municipalities of Tierra Blanca, Tres Valles, Cosamaloapan, Ixmatlahuacan, Acula, Chacaltianguis and Tlacotalpan, which produce 90.5 % the bovine milk of the district(10). A semi-structured questionnaire to obtain information about livestock approach, feeding and supplementation was applied. The sample size using the data available from INEGI(10) regarding the number of production units as sampling frame was determined (N= 5,924 σ²= 8.0). The following formula was used, considering a confidence level of 95% (Z = 1.96) and a maximum permissible error (B) of 0.5.

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𝑁𝜎 2 (𝑁 − 1)𝐵 2 𝑛= + 𝜎2 𝑍2 The result was n= 120 UP, however, in practice, 124 production units were accessed.

Characterization of the cheese-making process and sampling

A dairy in each municipality was selected based on processed milk per day (at least 500 L). Semi-structured questionnaire considering the variables in Table 1 was applied. Five samples of milk and five samples of cheese were taken weekly in each of the seven dairies (35 samples of milk and 35 samples of cheese) for five weeks, collecting 175 samples of milk and 175 samples of cheese in total. For milk, 500 ml from the storage tank were taken before starting the cheese processing using borosilicate sterile glass bottles. At the end of the production process, 500 g of cheese was taken in sterile bags with hermetic sealing. The samples at 4 ± 1 °C were transported for analysis. All samples were taken in triplicate.

Chemical and microbiological analysis of the milk and cheese

The fat, protein and lactose content in milk were tested with ultrasonic equipment Lactoscan S (Milkotronic Ltd., Nova Zagora, Bulgaria). The fat, moisture and protein content of cheese samples were determined(11). For microbiological analysis 10 ml (milk samples) or 10 g (cheese samples) were diluted in 90 ml of sterile peptone and homogenized one minute at 265 rpm in a homogenizer Stomacher™ model 400 (Seward Limited, UK). Dilutions of 10-1, 10-2 and 10-3 were obtained. Total Bacterial Count (TBC) and Total Coliform Count (TCC) were determined to milk. The TBC, Fungi and TCC were determined to cheese(11). To comply with the normality assumption, the values expressed as Colony Forming Units (cfu) were subjected to a logarithmic transformation and expressed as Log10 of cfu to perform the statistical analysis.

Texture and color of the cheese

The hardness and adhesiveness on cylindrical samples 2.5 cm in diameter and 3.0 cm in height were evaluated. A texturometer TA-XT (Stable Micro Systems, Surrey, UK) with an acrylic disk 35 mm in diameter (A/BE35) at the compression rate 5 mm/s was used. A colorimeter 356


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UltraScan™ Vis (HunterLab, Hunter Associates Laboratory Inc., Virginia, USA) was used to measure the colour parameter as L* (Luminosity), a* (red/green coordinates (+a indicates red, -a indicates green) and b* (yellow/blue coordinates (+b indicates yellow, -b indicates blue). The Chromaticity or saturation (C*) and Hue angle (hº) were calculated. The samples were analyzed in triplicate and at three different points of the cheese surface.

Sensory analysis of cheese

A panel of eight trained judges was formed. The Bright (BR), Porous in view (PV), Serum presence (SP), Hardness to the touch (HT), Creamy to the touch (CT), Milk smell (MS), Serum smell (SS), Milking smell (MKS), Salty (SA), Hardness in mouth (HM), Plastic aroma (PA), Milk Aroma (MA), Serum aftertaste (SAT) and Milk aftertaste (MAT) attributes were evaluated. An unstructured scale from zero (low intensity) to nine (high intensity) was used. The "Typical" (TY) attribute was evaluated using an unstructured scale (right and left anchors were “good example” and “bad example” of a typical cheese)(12). Eight sessions with a replication were conducted to obtain the sensory profile by QDA™. Only samples with bacterial counts within the official Mexican standard were used.

Statistical analysis

The experimental data were analyzed using an analysis of variance (ANOVA), and a minimum significant difference test with a confidence level of 95% was used. The correlation among some variables and the effect of the manufacturing process on the cheese characteristics using SAS version 9.3(13) were determined. The instrumental, sensory and manufacturing process data were integrated by Multiple Factorial Analysis (MFA) and vectorial correlation coefficient Rv using XLSTAT version 1.0(14). The stabilities of the sensory map, confidence ellipses (95%) and Hotelling’s test T2 using SensoMineR with language R version 2.15.3 (R Development Core Team) were determined.

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Results and discussion

Characterization of the bovine milk production system

Only dual-purpose systems were observed, Swiss×Cebu crosses were predominant (85 %), used to obtain acceptable levels of milk production with animals resistant to tropical conditions(15). The herd feeding consists in Cynodon nlemfuensis (Vanderyst) (23.4 %), Brachiaria humidícola, (Rendle) (18.2 %), Digitaria eriantha (Stent) (17.3 %), and undefined mixtures (41.1 %). The supplementation with protein concentrates in 20 % of cases only in the dry season was observed, which, as mentioned by some producers, is carried out with the objective of maintaining production levels and not increasing production costs. The dairy herd consists an average of 63 cows milked once daily by hand (98.4 %). An average milk production of 4.4 L·cow-1, that in 32 % of cases do not sell it because they use it to produce cheese.

Characterization of the cheese making process

The production process of ranchero Jarocho cheese registers three generations in 57.2 % of the dairies; The process consists of (a) raw milk is coagulated (32-34 °C/2-3 h) with commercial rennet (Cuamex, México Industries); (b) the curd is cut; (c) the serum is drained by decanting; (d) salt is added manually by crumbling to reduce the curd size; (e) the curd is pressed in plastic molds. The variables of the cheese making process are presented in Table 1. The used milk is not standardized or homogenized and calcium chloride and starter culture is not used. It was observed that in 28 % of dairies vegetable fat was added to the milk to increase the yield(16) which is considered an adulteration(17). The pressing was similar to that reported in Caciocavallo cheese(18) and fresh cheese from Croatia(19). A distinctive manufacturing feature is a rotation during the pressing so that the moisture is homogeneously distributed.

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Table 1: Description of variables involved in the manufacturing process of ranchero Jarocho cheese Variable

Levels

Cheese dairies (%)

Quality tests are performed to milk received

Yes No 5 6 7 2.0 3.0 3.5 4.0 4.5 0 2 3 Yes No 10 11-15 16 Plastic Stainless steel 1 3

28 72 57 28 15 14 29 14 29 14 72 14 14 28 72 57 28 15 28 72 42 58

Amount of added salt (%)

Pressing time (hours)

Number of rotations during pressing Addition of vegetable fat Cheese yield (%) The material of the containers used Antiquity of the process (Generations)

Chemical composition and microbiological analysis of milk

The main chemical parameters are shown in Table 2. The milk of Acula and Cosamaloapan presented the lowest fat content, possibly due to rainy season which is presented high moisture and low fiber content on the forage. The milk of Chacaltianguis and Ixmatlahuacan presented physiologically improbable values associated with the addition of vegetable fat. The protein content was low possibly caused by the high yield of Bos Taurus component(20). The lactose content was lower than the reported in dual-purpose systems(15). The milk composition was characterized by low solids content; this is related to genetic, technological, environmental and dairy herd variables(21). The main indicators microbial of contamination of milk are presented in Table 2. The TBC indicated an inadequate hygiene in the milking and post-milking management(22) since they were higher than 100,000 cfu ml-1 (23). For TCC only the milk of 359


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Tierra Blanca and Cosamaloapan fulfilled the regulatory count which sets a lower count of 750 cfu ml-1(23) related to failures in the removal of residual water or milk from the deposits or containers(22). Table 2: Chemical composition and microbiological analysis of milk in different cheese dairies (Mean±SD) Fat

Protein

Lactose

TBC

TCC

Municipality (g L-1) Ixmatlahuacan * Chacaltianguis * Tierra Blanca Tres Valles Tlacotalpan Cosamaloapan Acula SEM *

84.50 ± 0.30e 73.35 ± 0.10d 35.00 ± 0.10c 34.20 ± 0.30c 32.20 ± 0.40b 31.75 ± 0.20b 24.75 ± 0.50a 4.877

(log10 cfu mL-1)

32.0 ± 0.80c 27.1 ± 0.38a 26.2 ± 0.04a 29.8 ± 0.32b 31.6 ± 1.80c 26.9 ± 0.87a 30.4 ± 1.40b 2.408

43.3 ± 1.20b 44.3 ± 2.57b 38.6 ± 0.54a 42.6 ± 0.49b 39.1 ± 0.05a 38.2 ± 1.20a 43.2 ± 0.10b 0.578

5.72 ± 0.11e 5.54 ± 0.01b 5.34 ± 0.01a 5.61 ± 0.00d 5.74 ± 0.01f 5.57 ± 0.01c 5.76 ± 0.00g 0.032

4.35 ± 0.00c 4.20 ± 0.02b ND 4.10 ± 0.01a 4.12 ± 0.01b ND 4.35 ± 0.00c 0.427

-1

Milks with added vegetable fat. ND= Not detected (<1 log10 cfu mL ). TBC= Total bacterial count; TCC= Total coliform count. SEM= Standard error of the mean. ɑ Values followed by different letters in superscripts in each column are significantly different at P<0.05.

Chemical composition and microbiological analysis of cheese

The chemical composition of cheeses is shown in Table 3. According to the moisture content, ranchero Jarocho cheese was classified as a fresh and soft cheese(24). The protein content was lower than to that reported in the Mihalic cheese(25). The heterogeneity in the chemical composition was related to making process. The cheeses with less pressing time had higher moisture, less protein, and fat (Figure 1a). This effect has been explained to be a solid concentration effect when the moisture is removed(26). The main indicators microbial of contamination of cheeses are presented in Table 3. The values for all parameters were higher than reported for the Dill cheese made from pasteurized milk(27) and similar than reported for the tropical cream cheese, attributing to the use of raw milk(28). A correlation between the microbial counts of the milk and the microbial counts of the cheeses (TBC: R=0.64, P˂0.05; 360


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TCC: R=0.98, P˂ 0.001) was observed. The cheeses had values of TBC and TCC higher than the milk due to the physical retention of microorganisms in the curd and the microbial growth during coagulation and whey removal(29). Some of the manufacturing process variables affected the microbial counts of the cheese (Figures 1b, 1c and 1d). The dairies where quality tests were performed and stainless-steel vessels were used had the lowest TBC, TCC and Fungi counts. These results occur because the stainless-steel vessels are made can be maintained in a sanitary condition(27). In dairies where training courses were held the TBC, TCC and Fungi counts were the lowest. The high microbial counts in cheeses can be related to the use of unpasteurized milk. The pasteurization can reduce the microbial count(30) however; can eliminate bacteria responsible for the typical flavors(29) and specific sensory characteristics of the cheese(31). Table 3: Chemical composition and microbiological analysis of ranchero Jarocho cheese made in different cheese dairies (Mean±SD) Moisture

Fat

Protein

TBC

Fungi

TCC

Municipality (g kg-1) Acula Chacaltianguis Ixmatlahuacan Tres Valles Cosamaloapan Tlacotalpan Tierra Blanca SEM

(log10 cfu g-1)

510.01 ± 0.25a 540.52 ± 0.31b 540.75 ± 0.15b 560.24 ± 0.01c 590.36 ± 0.22d

170.6 ± 0.50d 150.5 ± 0.54b 180.5 ± 0.54e 160.7 ± 0.43c 130.3 ± 0.41a

250.10 ± 1.06e 230.11 ± 1.58d 200.43 ± 0.40c 190.35 ± 0.37bc 180.23 ± 0.27ab

5.97 ± 0.00c 5.61 ± 0.01ab 6.15 ± 0.11d 5.68 ± 0.00b 5.66 ± 0.01ab

3.91 ± 0.01c 3.39 ± 0.01a 3.64 ± 0.36b 3.20 ± 0.00a

4.94 ± 0.00d 4.26 ± 0.03c 4.95 ± 0.00d 4.16 ± 0.01a

ND

ND

600.54 ± 0.01e

160.1 ± 0.41bc

180.16 ± 0.19ab

5.78 ± 0.01b

3.20 ± 0.03a

4.15 ± 0.01b

620.2 ± 0.26f 8.099

160.0 ± 0.0bc 3.272

170.1 ± 0.27a 6.087

5.5 ± 0.02a 0.044

ND

ND

0.355

0.459 -1

TBC= Total bacterial count; TCC= Total coliform count. ND= Not detected (<1 log10 cfu mL ). SEM = Standard error of the mean. abcdef Values followed by different letters in superscripts in each column are different (P<0.05).

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Figure 1: (a) Effect of (a) pressing time on the moisture, fat and protein content, (b) milk quality testing to receive it in the cheese dairies, (c) material of the containers used, (d) training of producers, over total bacterial count (TBC), total coliform count (TCC) and Fungi in analyzed cheeses

Texture and color of cheeses The texture analysis results of the cheeses are shown in Table 4. The hardness and adhesiveness were lower than the fresh cheeses with added canola oil(32). The pressing time, a number of rotations, the addition of vegetable fat and percentage of salt parameters affect the cheese hardness (Figure 2). A longer pressing time allowed a more water transferred out of the cheese, which increased the fat and protein concentrations and the hardness(33). The number of rotations during pressing affected the water removal, where the cheese that is rotated more times retains more moisture and has the lowest hardness. The cheeses with added vegetable fat had the highest hardness (P˂0.05) because the larger diameter of the vegetable fat globules enables the interaction with more protein per unit area and causes greater resistance to deformation of the protein matrix(16,32). A higher percentage of added salt increases the hardness of the cheese, probably due to a decrease in the degree of proteolysis(34). The color parameters are shown in Table 4. L* indicates high brightness and is consistent with the observed in the fresh cheese of Minas Gerais in Brazil(26). The Hue angles indicate a tonality close to yellow (90°) with differences in saturation (C*). The yellowing of cheeses made from cow's milk is characteristic because cows can transfer dietary carotenoids to the milk(25). The moisture content is correlated with the values of L* (R= 0.38, P ˂ 0.001) and C* (R= -0.43, P˂0.001): the cheeses with higher 362


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humidity were brighter and had less color saturation because higher water content increases the ability to reflect or transmit light(26). The difference in color saturation can be related to the use of vegetable fat, which was previously reported(16). Table 4: Texture and color parameters for the ranchero Jarocho cheese made in different cheese dairies (Mean±SD) Hardness

Adhesiveness

L*

C*

Municipality (N) Tierra Blanca Tlacotalpan Tres Valles Cosamaloapan Acula Chacaltianguis Ixmatlahuacan SEM

0.72 ± 0.10a 1.72 ± 0.17b 1.81 ± 0.61b 1.85 ± 0.41b 2.18 ±0.64bc 2.56 ± 0.59c 3.18 ± 0.60c 0.182

-0.26 ± 0.27a -0.11 ± 0.11a -0.18 ± 0.14a -0.03 ± 0.04a -0.08 ± 0.10a -0.16 ± 0.18a -0.14 ± 0.10a 0.031

91.5 ± 5.46ab 14.7 ± 1.10bc 92.5 ± 0.70b 12.0 ± 2.91a 92.1 ± 0.64ab 14.2 ± 0.62ab 91.9 ± 0.73ab 13.0 ± 0.66ab 91.0 ± 0.42ab 16.4 ± 1.04c 90.5 ± 0.67a 16.1 ± 0.89c 90.7 ± 0.79ab 15.6 ± 0.53c 0.423 0.418

89.4 ± 0.29a 87.2 ± 3.05a 88.3 ± 0.70a 89.3 ± 0.40a 89.4 ± 0.47a 89.0 ± 0.37a 89.3 ± 0.38a 0.281

L*= Luminosity; C*= Chromaticity or saturation; h°= Hue angle. SEM = Standard error of the mean. abc Values followed by different letters in superscripts in each column are different (P<0.05).

Figure 2: Effect of a) pressing time, b) rotation, c) addition of vegetable fat and c) percentage of added salt on the hardness of ranchero Jarocho cheese

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Sensory analysis

The confidence ellipses showed the discriminant effect of the panel which formed three groups, according to Hotelling’s test T2 (0.205, 0.39 and 0.14) (Figure 3a). The sensory profile revealed that the cheeses of Tierra Blanca were characterized by the higher intensity in attributes BR, CT, MA and MAT. The cheeses of Acula and Ixmatlahuacan had lower intensities of BR, MA, and SA. The cheeses of Tlacotalpan, Cosamaloapan, Chacaltianguis, and Tres Valles showed more intensity in SAT, MA, MKS and SS (Figure 3b). Figures 3c and 3d show 70 % of the total inertia of the data in the two principal components. The cheeses of Tres Valles, Tlacotalpan and Cosamaloapan were grouped according to the percentage of added salt and considered the most typical with highest intensities of MAT, SA, SS, MKS and MA (Figure 3c). The attributes SA and SS were established to differentiate Mihalic cheeses(25) because the salt content affects the aroma intensity of cheeses(35). The attributes BR and CT were associated with higher moisture content and greater L*. The attributes HT and HM were associated with higher protein content, total solid and more hardness. Figure 3d shows that the sensory and physicochemical data are near at midpoint among all cheeses, confirmed with the Rv coefficient (RvSE-FQ = 0.74). Figure 3: (a) Confidence ellipses around of cheeses, (b) sensory profile of the cheeses, (c) sensory-physicochemical correlation, (d) Overall and partial representation of cheeses in the MFA (solid line: sensory data, dashed line: physicochemical data)

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“Through the integration of the information, it was observed that the ranchero Jarocho cheese has a high potential to obtain commercial protection, however, it presents the following difficulties: The high variability in milk quality is a consequence of the inequality in which the local milk systems of dual purpose are developed, therefore, originates a high heterogeneity in the quality of the cheeses. Therefore, at the production system level, it is necessary to train producers to maintain a more stable and homogenous milk quality. Another important problem is the addition of vegetable fat as a strategy to increase cheese yield. In this regard, it is preponderant to convince the producer that this practice must be eradicated since it discards the product to obtain commercial protection. Finally, the lack of pasteurization of milk for the production of cheeses is perhaps the most worrisome problem since it firstly violates current local regulations and also represents a high risk of contamination with pathogenic bacteria such as Salmonella, E. coli, Listeria, Campylobacter and others that cause disease in humans. This problem may seem simple; however, the sensory attributes of cheeses are strongly related to some specific microorganisms and although pasteurization eliminates pathogenic bacteria, it also destroys bacteria related to the development of aromas and flavors. Therefore, it is necessary to carry out more studies focused on correlating specific bacteria in milk with the development of sensory attributes that make ranchero Jarocho cheese be perceived as “typical” with the aim of isolating the milk microbiota so that it can be added after the pasteurization process. These studies must be carried out so that the developed technology can be transferred later to the producers”.

Conclusions and implications This study revealed that the ranchero Jarocho cheese is manufactured with milk from local dual purpose systems and the making process reflects the traditional empirical knowledge and is associated with the cultural practices that have maintained these biological resources over several generations. The multivariate integration revealed that the cheeses with greater intensity in the sensory attributes as serum and milking smell, milk aroma intensified by a higher percentage of salt were perceived as the most typical ranchero Jarocho cheese. Likewise, some aspects of this study revealed that the use of raw milk and lack of sanitation could compromises the safety of consumers. On the other hand, the heterogeneity in composition of ranchero Jarocho cheese related to differences in the production process in some cheese factories, as well as, the addition of vegetable fat in milk could classified it as an analogous cheese. However, the multidisciplinary approach allowed to appreciate the potential of this cheese for obtaining its typicity, for that purpose, applying sanitation measures during milk collection, good cheese manufacturing practices and avoiding the addition of vegetable fat, it could be possible get a legal-commercial protection of the ranchero Jarocho cheese.

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22. Pantoja J, Reinemann J, Ruegg L. Associations among milk quality indicators in raw bulk milk. J Dairy Sci 2009;92:4978–4987. 23. Murphy S, Boor K. Trouble-shooting sources and causes of high bacteria counts in raw milk. Dairy Food Environ Sanit 2000;20(8):606–611. 24. Ramírez-López C, Vélez-Ruiz JF. Quesos frescos: propiedades, métodos de determinación y factores que afectan su calidad. Temas Selectos de Ingeniería de Alimentos 2012;6:131– 148. 25. Aday S, Karagul YY. Physicochemical and sensory properties of Mihalic cheese. Int J Food Prop 2014;17:2207–2227. 26. Magenis R, Prudêncio S, Fritzen F, Stephan P, do Egito A, Daguer H. Rheological, physicochemical and authenticity assessment of Minas Frescal cheese. Food Control 2014;45:22–28. 27. Irkin R. Determination of microbial contamination sources for use in quality management of cheese industry: “Dil” cheese as an example. J Verbrauch Lebensm 2010;5:91–96. 28. Romero-Castillo P, Leyva R, Cruz J, Santos M. Evaluación de la calidad sanitaria de quesos crema tropical mexicanos de la región de Tonalá, Chiapas. Rev Mex Ing Quím 2009;8:111–119. 29. Torres-Llanez MJ, Vallejo-Cordoba B, Díaz-Cinco ME, Mazorra-Manzano MA, GonzalezCordova AF. Characterization of the natural microflora of artisanal Mexican fresco cheese. Food Control 2006;17(9):683-690. 30. USDA. Unıted State Department of Agriculture Milk for Manufacturing Purposes and its Production and Processing, Recommended Requirements. Dairy Programs. USA. 2011. 31. Aldrete-Tapia A, Escobar-Ramírez MC, Tamplin ML, Hernández-Iturriaga M. HighThroughput sequencing of microbial communities in Poro Cheese, an artisanal Mexican cheese. Food Microbiol 2014;44:136–141. 32. Lobato-Calleros C, Reyes-Hernández J, Beristain C, Hornelas-Uribe Y, Sánchez-García J, Vernon-Carter E. Microstructure and texture of white fresh cheese made with canola oil and whey protein concentrate in partial or total replacement of milk fat. Food Res Int 2007;40:529–537. 33. Hussein G, Shalaby S. Microstructure and textural properties of Kareish cheese manufactured by various ways. Ann Agric Sci 2014;59:25–31.

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https://doi.org/10.22319/rmcp.v12i2.5582 Article

Effect of wet feeding of finishing pigs on production performance, carcass composition and meat quality

Néstor Arce Vázquez a Hugo Bernal Barragán a* Nydia Corina Vásquez Aguilar a Estela Garza Brenner a Fernando Sánchez Dávila a Adriana Morales Trejo b Miguel Cervantes Ramírez b

a

Universidad Autónoma de Nuevo León. Facultad de Agronomía. Campus de Ciencias Agropecuarias UANL. Calle Francisco Villa S/N. Fracc. Ex-Hacienda “El Canadá”. 66054 Gral. Escobedo, N.L., México. b

Universidad Autónoma de Baja California. Instituto de Ciencia Agrícolas. Mexicali. Baja California. México.

*Corresponding author: hugo.bernalbr@uanl.edu.mx

Abstract: The objective of the study was to evaluate the effect of feeding finishing pigs with a wet diet (feed:water, 1:1), versus a dry diet based on sorghum and soybean meal (15.0% CP, 3,200 kcal ME/kg DM), on the productive behavior, carcass composition and meat quality. Sixteen (York-Landrace x Duroc) crossbred pigs weighing 68.4 ± 2.4 kg were individually housed and assigned to two treatments (n= 8 replicates per treatment): DF, dry feed; WF, wet feed. Feed was offered daily in two equal portions (0800 and 1500 h) for 5 wk. Individual live weight (LW) and feed consumption were recorded every week in order to calculate the daily

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weight gain (DWG) and feed efficiency (FE). The carcass composition was measured; the meat quality was assessed in samples of Longissimus dorsi. Wet-fed pigs had higher (P<0.05), final LW (108.4 vs 101.9 kg), and DWG (1.043 vs. 0.990 kg/day) than dry-fed pigs. DF pigs had lower intake (wk 5) and feed efficiency (FE) (by wk 3) than WF pigs (Treatment x Week Interaction, P<0.05). WF pigs had greater leg and hot and cold carcass weights (P<0.05). The weight of the loin, ribs, and shoulder, and the protein content, water holding capacity, and pH of meat were similar (P>0.05) between treatments. The hardness, adhesiveness, chewiness, and toughness values were lower (P<0.05) in meat from WF pigs. In conclusion, the wet-fed pigs had better productive performance, carcass composition and meat characteristics than the dry-fed pigs. Key words: Wet feed, Dry feed, Finishing pigs, Carcass measurement.

Received: 19/12/2019 Accepted: 02/11/2020

Introduction Correct feeding management is important to improve animal welfare, growth efficiency and production data of pigs. One possibility to improve feeding systems for pigs is to mix dry feed with water (proportions between 1:1.0 and 1.5)(1). Wet feeding has been shown to reduce stress in the transition from liquid to solid diet of weaned piglets(1,2,3); this may have beneficial effects such as reducing the use of antibiotics in current production systems(4,5). In addition, wet feed improves water and feed intake(3,6), as well as nutrient supply, in growingfinishing pigs(7), compared to dry feed, potentially favoring the productive performance(4) without affecting the fat content and carcass quality of the pigs(1,5). Sensory characteristics, such as tenderness, color, and marbling are important in determining the quality and consumer approval of beef(8), chicken(9), rabbit(10), and pork(11,12). These improvements may be greater in regions where the ambient temperature exceeds the pigs' thermoneutral (comfort) zone. However, information on the effect of wet feed on intensive pork production systems in hot areas like northern Mexico is scarce. Therefore, the objective of the present study was to determine the effect of sorghum and soybean meal based wet feed on the growth rate and efficiency, productive behavior, carcass composition and meat quality of finishing pigs. The hypothesis of the present study was that the feed intake and utilization of pigs under these climatic conditions might be improved by a wet diet.

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Material and methods The pigs used in this research were cared for in accordance with the guidelines established in the Mexican Official Animal Care Standard (Norma Oficial Mexicana para el Cuidado de Animales)(13). The study was conducted at the Swine Experimental Station of the Marín Academic Unit of the Agronomy Department of the Autonomous University of Nuevo León, located in Marín, N.L., Mexico. Sixteen pigs (8 females and 8 castrated males; experimental units) of the York-Landrace x Duroc terminal cross with an initial live weight of 68.4 ± 2.4 kg were used. The animals were housed individually in pens with concrete floors (1.4 m2), equipped with stainless steel drinking troughs and plastic feeders. The pigs were randomly assigned by sex to each of the two treatments: WF, wet feed at a ratio of 1:1 (diet:water), and DF, dry feed. The diet offered to the pigs was based on ground sorghum grain, soybean meal, and a vitamin and mineral premix, formulated with 3,200 kcal ME/kg and 15% crude protein, in order to meet or exceed the nutritional requirements of pigs in the 50 to 120 kg weight range, NRC(7).

Experimental procedure

During the experimental period, the minimum and maximum ambient temperature was recorded daily at the pen level, using a digital thermometer (STEREN®, model TER-100, China). The adaptation period to the pens and feeds was one week, followed by a 5-wk trial period. The live weight of the pigs was recorded weekly in order to calculate the average daily weight gain (ADWG). The offered and refused feed was recorded daily in order to calculate weekly daily feed intake (DFI) and the gain/consumption ratio (feed efficiency = FE). At the end of the experiment, all pigs were slaughtered in a TIF (Federal Inspection Type) slaughterhouse. The hot carcass (HC) and cold carcass (CC; 24 h post-slaughter, 2 °C) weights were recorded. The length of the carcass was measured by recording the distance (cm) between the 6th cervical vertebra and the hip bone(11); the weights of the primary carcass cuts were recorded: leg, shoulder, loin and ribs according to the Mexican Standard for Livestock Products (Norma Mexicana de Productos Pecuarios)(14).

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Meat laboratory analysi After 24 h post mortem, the pH, color and water holding capacity (WHC, %) of the Longissimus dorsi (LD) muscle were determined in quadruplicate for each sample(11). In the present study, the muscle pH was determined by directly inserting the electrode of a puncture potentiometer (Orion 3 star Thermo Fisher Scientific, USA). In order to evaluate the quality of the meat, a sample of LD muscle was taken from between the 10th and 12th rib, and was stored at -20 °C until analysis. Its color was analyzed with a colorimeter (Minolta Chroma Meter 2002, Konica Minolta Holdings, Inc., Tokyo, Japan), and the values were expressed according to the CIE System (B*, a* and b*). The WHC was determined by the compression method previously described(15). The shear force (SF) was measured on four rectangles (4x2x2 cm) of each LD sample, with cuts parallel to the direction of the muscle fibers, using a texturometer (TA.XT2i Stable Micro Systems Serrey, England) equipped with a Warner-Bratzler knife. The shear conditions were speed of 2 mms-1 in the pre-test, 2 mms-1 in the test, 10 mms-1 in the posttest, at a distance of 30 mm(16). The texture profile analysis (TPA) of the LD samples was performed with a texturometer (TA.XT2i Stable Micro Systems Serrey, England), using four standardized cubes of 2 cm for each sample, which were obtained perpendicular to the direction of the muscle fibers. A cylindrical piston was used to compress the sample to 60 % of the original height during two compression cycles with a time interval of 5 sec between them. Force-time stress-strain curves were obtained based on the established velocity conditions: 1.0 mms-1 (pre-test); 5.0 mms-1 (test), and 5.0 mms-1 (post-test). Values for hardness (g), adhesiveness (g/sec), elasticity (mm), cohesiveness, gumminess (g), chewiness (g mm), and toughness were obtained according to previous reports(17,18). All meat samples were analyzed for protein content using the AOAC Method 990.03(19).

Economic analysis

The income from animal growth was calculated considering a live pig price of $32.00 MN/kg, multiplied by the respective weight gain of each animal. The feed cost was calculated considering the price of the feed for both treatments ($ 5.90 MN/kg), multiplied by the respective consumption of each animal. These two variables were used to calculate the difference in income for growth, minus the cost of food. Live hog prices and feed cost were

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obtained with August-September 2018 base prices published by the Confederation of Mexican Swine Farmers (Confederación de Porcicultores de México)(20) and Mexico's National Market Information and Integration System (Sistema Nacional de Información e Integración de Mercados de México)(21).

Statistical analysis

The data were analyzed under a randomized complete block design using the SPSS statistical package version 22 (Version 2013. IBM SPSS Statistics for Windows, Version 22.0, Armonk, NY: IBM Corp.). The data are presented as means, and the significant differences (P<0.05) were determined by Tukey's test.

Results The ambient temperature during the experiment ranged from a minimum of 9.1 °C to a maximum of 35.3 °C, with an average of 27.3 °C during the study. Table 1 shows the results of productive behavior after five experimental weeks. The live weight of wet-fed pigs was higher (P<0.01) at the end of weeks 4 and 5, and during the entire study, compared to dryfed pigs. Differences in live weight between treatments became more pronounced over the experimental weeks (P<0.01). Although the ADWG was not statistically different in each of the weeks, it was statistically different overall in pigs fed the wet diet (P<0.01; Figure 1). The ADFI was lower at wk 1 and higher at wk 5 when offered wet feed (P<0.01), but it was not different throughout the entire study (P>0.10). The variable FE (P<0.05) was better with wet feed in weeks 1 and 3 (Figure 2), and throughout the study.

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Table 1: Effect of offering wet feed (WF) or dry feed (DF) on the live weight, ADFI, ADWG, and FE of finishing pigs (68 to 108 kg) in each experimental week Week 1 2 3 4 5 Individual live weight (ILW, kg) WF 74.8 83.3 91.6 98.4a 108.4a DF 74.2 81.6 88.5 92.6b 101.9b Average daily feed intake (ADFI, kg/d) WF 2.56b 3.14 3.34 3.36 3.35a DF 3.01a 2.959 3.28 3.04 2.84b Average daily weight gain (ADWG, kg/d) WF 0.902 1.22 1.18 0.982 1.43 DF 0.755 1.20 0.991 0.786 1.27 Feed efficiency (FE, kg) WF 0.353a 0.386 0.351a 0.294 0.426 DF 0.250b 0.410 0.298b 0.253 0.448 a,b

P MSE Treatment Week 0.73 0.75

0.001

Interaction

<0.001 0.322

0.064 0.180 0.066

0.010

0.023

0.038 0.010 0.039

<0.001 0.861

0.010 0.032 0.010

<0.001 0.023

MSE= mean standard error; Means with different letters within the same column for each variable are different (P<0.05).

Figure 1: Daily feed intake (Mean ± MSE) of pigs in the final phase (68 a 108 kg) fed with wet feed (WF) and with dry feed (DF)

a,b

Significant difference (P<0.05) between groups.

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Figure 2: Feed efficiency (Mean ± MSE) weekly measurements in pigs at the final stage (68 to 108 kg), with wet feed (WF) and with dry feed (DF)

a,b

Significant difference (P<0.05) between groups.

Weight of the carcass components

Wet-fed pigs had higher hot (P=0.019) and cold (P=0.021) carcass weights than dry-fed pigs (Table 2). The carcass length was not different (P>0.05) for the two treatments. The average weight of the leg and skin + fat was higher (P=0.04) in wet-fed pigs than in dry-fed pigs. The weights of the loin, rib, shoulder and leg did not differ between the wet fed and those fed a dry diet (P>0.05).

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Table 2: Carcass characteristics and weight of the main carcass components of pigs slaughtered at 108 kg live weight, with wet feed (WF) and dry feed (DF) Concept

Treatment DF

MSE

P

90.80 89.13 81.56

84.80 83.39 80.94

1.599 1.564 0.985

0.019 0.021 0.661

10.33 9.33 5.66 4.45 11.63 0.739

9.78 9.34 5.03 4.25 9.65 0.694

0.172 0.212 0.254 0.109 0.468 0.019

0.040 0.967 0.097 0.214 0.009 0.120

WF

Carcass measurements Hot carcass weight, kg Cold carcass weight, kg Carcass length, cm Average piece weight, half carcass, kg Leg Loin Rib Shoulder blade Skin + fat Feet

MSE= mean estándar error.

Physicochemical and textural characteristics of the meat

Table 3 shows the physicochemical and textural characteristics of the meat. No differences were observed in the protein and carbon content, pH, or water holding capacity of the meat (P>0.05) between treatments. The hardness, gumminess, chewiness, and toughness of the meat were higher (P<0.05) in dry-fed pigs than in wet-fed pigs. The shear strength, adhesiveness, elasticity, and cohesiveness did not differ (P>0.05) between treatments. Table 3: Values of physicochemical characteristics and meat texture of pigs slaughtered at 108 kg LW, with wet feed (WF) and with dry feed (DF) Characteristics Physicochemical Protein, % MS Carbon, % MS pH WHC, % Texture Shear force, N Hardness, N

Treatment DF

WF

MSE

P

25.70 16.39 5.50 64.31

25.31 16.07 5.48 62.98

0.300 0.235 0.018 0.864

0.372 0.353 0.506 0.284

41.22 35.37

37.46 57.32

2.384 7.071

0.270 0.032

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Adhesiveness, g/seg Elasticity, mm Cohesiveness Gumminess, g Chewiness, gmm Resistance

-25.11 0.435 0.446 15.86 6.30 0.237

-22.66 0.457 0.453 27.16 11.65 0.283

1.400 0.015 0.010 3.470 1.367 0.013

0.216 0.324 0.584 0.025 0.007 0.015

MSE= mean estándar error; WHC= water holding capacity.

Tendency of meat color

The values of brightness (B*), tendency to red (a*) and to yellow (b*), saturation (C), and hue angle (H) of the flesh were not different (P>0.05) between the two treatments (Table 4). Table 4: The color of the meat measured in the Longissimus dorsi muscle of pigs slaughtered at 108 kg live weight, with wet feed (WF) and dry feed (DF)

Characteristic B* a* b* C H

Treatment WF 53.62 17.03 9.16 19.37 28.29

DF 54.04 17.3 9.32 19.75 28.35

MSE 0.879 0.221 0.255 0.194 0.790

P 0.734 0.392 0.656 0.175 0.954

MSE= mean estándar error. B* brightness; a*= tendency to red; b*= tendency to yellow; C= saturation; H= Hue angle.

Economic analysis

The feed cost (Table 5) was similar (P=0.180) for the wet-fed pigs than for the dry-fed pigs (average = $127.61 MN per animal during the experimental phase). However, due to a higher growth rate, economic income was 13 % higher (P=0.01) for the wet-fed pigs than for the dry-fed pigs. The difference in income due to pig growth minus the feed cost was 27.3 % higher (P=0.008) for pigs that received wet feed than for dry fed pigs.

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Table 5: Analysis of the cost and economic usefulness of pigs in the final stage (68 to 108 kg) fed wet feed (WF) or dry feed (DF) Treatment WF 256.00 130.12 125.88

Economic variable ($ MXN) Income from pig growth Feed cost Difference in income minus cost of feed

DF 226.53 124.96 101.56

MSE 12.145 3.802 9.923

P 0.010 0.180 0.008

MSE= mean estándar error.

Discussion The present experiment was carried out under climatic conditions representative of many dry tropical sites; it is one of the first studies carried out in the northeastern region of Mexico. During the experiment, the pigs were housed in a shed with open sidewalls, so that the animals were under the natural ambient temperature conditions, which ranged from 10 to 35.3 °C. These extremely variable environmental conditions could have affected the feed intake and feed efficiency of the pigs. A significant interaction between experimental week and treatment was obtained for the ADFI and FE, similarly to what was stated in previous reports(22,23). Exposure to a room temperature of 33 °C has been reported to reduce voluntary feed intake of pigs by 20 to 30 %(22). In the present study, the ADFI by wet-fed pigs at wk 1 was 12 % lower; however, it was 18 % higher at wk 5. Although the overall feed intake did not differ, the tendency to increase as the experiment progressed until it became significantly higher at wk 5 indicates that feed moistening may help to recover the voluntary feed intake of animals under climatic conditions of heat stress. Wet feeding also increased the average daily weight gain by 14 %, and the feed efficiency, by 8 %. The higher ADWG of WF pigs, as observed in the present experiment, is in agreement with the results reported in finishing pigs(24) and growing-finishing pigs fed a wet diet for 90 d(25). Taken together, these results indicate that feeding the pigs a wet diet exposed to conditions of high ambient temperature may improve not only the feed intake but also the feed utilization efficiency. Yang et al(6) reported a lower ADWG and FE in growing-finishing pigs fed a liquid diet containing by-products of the ethanol industry, compared to pigs fed a wet diet based on corn and soybean meal. This suggests that, in addition to the type of feed (wet or dry), the ingredients used also play an important role in production efficiency. The wet feed offered to pigs at high ambient temperatures may have allowed them to have a better body temperature balance, resulting in higher weight gain and feed efficiency.

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The higher HC and CC weights in the WF pigs recorded in the present study agree with other previously published results(24), in which the hot carcass weight and yield were higher, but a similar backfat depth were reported in pigs fed a wet diet, indicating the possibility of a positive influence of wet feeding on carcass characteristics. The depth of the backfat has been reported to be similar in pigs whether they are fed a wet or a dry diet(25). However, wet-fed broilers had a higher abdominal fat content(26). When the trough is equipped with an integrated water supply, the pigs tend to consume more feed(24). The higher feed intake in wet-fed pigs reported in wk 5 of the present work may be reflected in a higher backfat content. In the present study, the legs were heavier in wet-fed pigs than in dry-fed pigs. This is consistent with previous reports(27) in which higher leg weights have been recorded in pigs with higher growth rates. The term meat quality describes the sum of different properties(28) such as pH, color, tenderness, WHC, and chemical composition(29), which are particularly important in sensory evaluation(30). In this study, differences were observed in favor of pigs fed a wet diet in terms of meat quality and texture characteristics such as shear strength, gumminess, and chewiness(31). The WHC and color are important attributes that determine the visual appeal and tenderness of the meat(32,33). The values observed in this experiment were similar between treatments and are in agreement with those previously reported(34,35) in finishing pigs. In the present work, the meat from the wet-fed pigs had lower toughness values than that from dry-fed pigs, which is indicative of a greater tenderness(36) ―one of the most important characteristics of the meat quality(32,37). The other results of texture profile analysis, such as adhesiveness and cohesiveness, also used regularly to determine sensory attributes(38), did not differ between treatments in the present work. Color is an important trait of pork quality, which can be affected by various factors, such as the feeding strategy(31) and the breed of the pigs(11,12). In the present study, no differences were found between treatments in the chromatic variables B*, a*, b*, C, and H, which determine the color. Compared with results from previous research(34), the brightness (B*) values in the present work for meat from pigs fed WF and DF (53.6 and 54.0, respectively; Table 4) were indicative of "normal" meat (39). B* values of 58 are indicative of PSE (pale, soft, exudative) meat, while values below 52 indicate the ASD condition (dark, firm, dry)(39,40,41). The economic analysis performed in this study has been used before(42), as it allows combining in a single value (difference of economic income minus the feed cost) the effect that the evaluated type of feed has on various characteristics, such as feed intake, daily weight 380


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gain, and feed efficiency. In the present study, the difference in the income derived from the growth of the pigs minus the feed cost for five weeks was 27.3 % higher for wet-fed pigs. The largest percentage of this economic benefit originated from the higher growth rate recorded in pigs fed a wet diet. In contrast, there was no difference in the feed cost with respect to the form in which the feed (whether dry or wet) was offered to the pigs. In a study published by Myers et al(43), pigs weighing between 80 and 110 kg fed from a wet feed trough had better growth data than pigs fed a dry diet. Based on the weight gain and feed consumption of these pigs(43) when fed a wet or a dry diet, as well as the prices of the feed and the pork meat registered by the present experiment, the economic benefit from wet-fed pigs estimated by Myers et al(43) would have been 9.1 % better than that obtained from dryfed pigs; this figure is lower than the economic benefit registered in the present study. In short, based on the results of this experiment, it is concluded that feeding finishing pigs with a wet diet improves the productive variables (daily weight gain, feed intake, feed efficiency), the economic profit, the carcass composition, and the meat quality.

Acknowledgments

The authors are grateful for the financial support provided by the National Call for Postdoctoral Stays (Convocatoria de Estancias Posdoctorales Nacionales) 2018(1) of the National Council for Science and Technology (Consejo Nacional de Ciencia y Tecnología, CONACYT, Mexico). They also thank the Agronomy Department of the UANL for facilitating the present research.

Conflict of interest

The authors declare that they have no conflicts of interest.

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25. Chae BJ, Han InK, Kim JH, Yang CJ, Ohh SJ, Rhee YC, Chung YK. Effects of feeding processing and feeding methods on growth and carcass traits for growing-finishing pigs. Asian-Aust J Anim Sci 1997;10(2):164-169. 26. Akinola OS, Onakomaiya AO, Agunbiade JA, Oso AO. Growth performance, apparent nutrient digestibility, intestinal morphology and carcass traits of broiler chickens fed dry, wet and fermented-wet feed. Livest Sci 2015;177:103-109. 27. Lanferdini E, Andretta I, Fonseca LS, Morerira RHR, Cantarelli VS, Ferreira RA, Saraiva A, Abreu MLT. Piglet birth weight, subsequent performance, carcass traits and pork quality: A meta-analitycal study. Livest Sci 2018;214:175-179. 28. Maltin C, Balcerzak D, Tilley R, Delday M. Determinants of meat quality: tenderness. Proc Nut Soc 2003;62:337-347. 29. Kim TW, Kim CW, Yang MR, No GR, Kim SW, Kim II-S. Pork quality traits according to postmortem pH and temperature in Berkshire. Korean J Food Sci An 2016;36(1):2936. 30. Hoffman, K. 1994. What is quality? Definition, measurement and evaluation of meat quality. Meat Focus Internat 1994;3(2):73-82. 31. Rosenvold K, Andersen HJ. Factors of significance for pork quality-a review. Meat Sci 2003;64:219-237. 32. Hughes JM, Oisek SK, Purslow PP, Warner RD. A structural approach to understanding the interactions between colour, water-holding capacity and tenderness. Meat Sci 2014;98:520-532. 33. Starky CP, Gessink GH, Oddy VH, Hopkins DL. Explaining the variation in lamb longissimus shear force across and within ageing periods using protein degradation, sarcomere length and collagen characteristics. Meat Sci 2015;105:332-37. 34. Nguyen DH, Park JW, Kim IH. Effect of crumbled diet on growth performance, market day age and meat quality of growing-finishing pigs. J Appl Anim Res 2017;45(1):396399. 35. Sasaky K, Motoyama M, Narita T, Chikuni K. Effects of cooking end-point temperature and muscle part on sensory “hardness” and “chewiness” assessed scales presented in ISO11036:1994. Asian-Aust J Anim Sci 2013;26(10):1490-1495. 36. Válvoká V, Saláková A, Butchtová H, Tremlová B. Chemical, instrumental and sensory characteristics of cooked pork ham. Meat Sci 2007;77:608-615.

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https://doi.org/10.22319/rmcp.v12i2.5683 Article

Sperm subpopulations and quality in fractions obtained after single layer centrifugation in fresh normospermic ram samples

Carlos Carmelo Pérez-Marín a Ander Arando b* Francisco Maroto-Molina c Alberto Marín a Juan Vicente Delgado b

a

Universidad de Córdoba. Department of Animal Medicine and Surgery, Campus de Rabanales, Ctra. Madrid-Cadiz km 396, Cordoba, 14014, Spain. b

Universidad de Córdoba. Department of Genetics, Cordoba, Spain.

c

Universidad de Córdoba, Department of Animal Production. Cordoba, Spain.

*Corresponding author: anderarando@hotmail.com

Abstract: Single layer centrifugation (SLC) technique has been developed to select the best sperm population in the ejaculate in order to increase the fertilization rates by artificial insemination or in vitro fertilization. Normospermic ram semen samples containing 800 and 3,000 × 106 sperms/ml (C800 and C3000, respectively) were processed by SLC. Three sperm fractions were separated in each sample following silica-coloidal sperm centrifugation and sperm yield, quality and subpopulations were analyzed in each one. In C800 group, the sperm recovery rate did not vary in any studied fraction, but when samples were highly concentrated (C3000) the top fraction (F1) contained significantly higher spermatozoa than bottom fraction (F3). Also, it was observed that F1 in C3000 had got a significantly higher percentage of spermatozoa (53.2 %) than in C800, while the quantity of spermatozoa recovered in fraction 2 was lower (25.2 % vs 45.4 %). Based on the sperm motility parameters, three sperm subpopulations were identified: SP1, low velocity spermatozoa showing no progressive movement (19.1 %); SP2, rapid and progressive spermatozoa (43.7 %); and SP3, rapid spermatozoa but non-linear movement 386


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(37.2 %). While SLC has been implemented for sperm separation in suboptimal and/or low concentrated sperm samples, this trial demonstrates that SLC is not efficient to separate different sperm populations in normospermic ram sperm samples containing high concentrations of spermatozoa. Key words: Single layer centrifugation, Ejaculates, Ovine, Spermatozoa.

Received:08/05/2020 Accepted:26/08/2020

Introduction Motility is an important characteristic linked to the progress of spermatozoa throughout the female reproductive tract(1) and to the oocyte penetration. Motility assessment is an essential procedure to evaluate the sperm quality and to approach the potential of male fertility(2). In this context, it is widely accepted that mammalian ejaculates constitute a heterogeneous cell pool with the presence of several sperm subpopulations. In order to select the best spermatozoa, many procedures have been developed to reduce debris, nonspermatozoal cells and bacteria contained in the sperm samples or to remove the seminal plasma to avoid the early capacitation process(3). This practice could have potential for improving results by artificial insemination (AI) and is essential when other biotechnological procedures, such as in vitro production or intracytoplasmic sperm injection, are implemented(4). Percoll, based on polyvinylpyrrolidone-coated silica particles, was one of the most used colloids for sperm separation in numerous species(5-7). However, the detection of certain endotoxins exerting a negative effect on the spermatozoa has reduced its use, and new media have been designed to overcome the shortcomings of Percoll. Silane-coated silica colloids are currently the most used solutions, having proved to be more stable and standardized(8). These colloids are employed in a variety of procedures, such as double layer centrifugation (DLC) or in a simplification of this technique, called single layer centrifugation (SLC)(9). The volume and concentration of the sperm sample could affect the effectiveness of these procedures(10). In this context, DLC has been regarded as impractical as a means of processing whole ejaculates for AI(9), and has been indicated for oligospermic ejaculates, although not for complete normospermic samples. SLC is an easier and less timeconsuming technique that has been widely used in equine(11), but there are few reports of its use in other species. Studies carried out in bulls showed that spermatozoa selected by SLC exhibit an increase in sperm chromatin integrity(12) and high mitochondrial membrane potential, although increased superoxide production(13). However, motility was only improved when low quality sperm samples were processed(14). In reference to the comparison between fractions obtained after colloidal centrifugation, Gosalvez et

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al(15) observed that the spermatozoa isolated in the bottom pellet showed lower sperm DNA fragmentation, although their longevity was lower than in human neat semen. These findings suggest that sperm fractions obtained by different sperm enrichment or separation procedures should be more deeply analyzed, in order to determine their efficiency in viability, concentration and other terms. The high concentration of sperm (as occurs in ruminant ejaculates) make it difficult to use layer centrifugation techniques for processing whole ejaculates(10) and to the best of the present authors’ knowledge, few studies evaluate the effect of colloidal separation in whole fresh, normospermic ram ejaculates. The present study was conducted in ram sperm samples containing different high sperm concentrations, to determine the sperm recovery rate, sperm quality and how different motile sperm subpopulations are distributed in each sperm fraction obtained after separation by SLC.

Material and methods Animals and semen collection Four mature Merino breed rams ranging from 3 to 5 yr old were involved in this study. The animals were housed in individual boxes located at Diputacion of Cordoba (Spain) and commercial concentrate (0.5 kg/d), alfalfa hay, water and minerals were supplied. Semen was collected once a week during non-breeding season (March-June) by artificial vagina and using a sheep as a teaser. Ejaculates were maintained at 37 ºC and mass motility (using the scale from 1 to 5; 40 × magnification; Olympus, Tokyo, Japan), sperm concentration (Accurread, IMV technologies, France) and volume were determined. Ejaculates with mass motility ≥4, concentration ≥3000 × 106 spermatozoa/mL and individual motility ≥70 % were used. All experiments were authorized by the Bioethics Committee of the University of Cordoba (n. 2018PI/29) and they were carried out according to the Spanish Animal Protection Regulation (RD 53/2013), as stipulated by EU Regulation 2010/63.

Experimental design As shown in Figure 1, semen from four rams was collected, assessed, diluted (1:2) and pooled in a home-made extender (TCFEY) containing Tris (33.19 g/L), fructose (9.55 g/L), 10% clarified egg yolk, citric acid (17.29 g/L), penicillin G (4 g/L) and streptomycin (3 g/L) in bi-distilled water. After dilution, two sperm aliquots were placed into conical tubes for centrifugation (300 g× for 20 min); after the supernatant was removed, TCFEY extender was added to reach a final concentration of 800 × 106 spermatozoa/ml (C800) and 3000 × 106 spermatozoa/ml (C3000) and sperm quality was assessed.

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Figure 1: Experimental design scheme used to study the variation of sperm quality and subpopulations at the different fractions obtained after SLC in samples containing 800 and 3000 × 106 spz/ml (C800 and C3000)

SLC based in silane-coated silica (BoviPure and BoviDilute, Nidacon, Sweden) was prepared according to the manufacturer´s instructions. While these solutions were developed for bull sperm, they can be used also for small ruminants. Briefly, one layer of 1.5 ml of 80 % (v/v) BoviPure was deposited into a 15 ml conical tube. Then, sperm samples containing C800 or C3000 were layered on the top (1.5 ml) and centrifuged at 300 g× 20 min. After centrifugation, seminal plasma was discarded (aprox. 1.5 ml), and three different fractions were isolated per sample: the top (F1), the medium (F2) and the bottom (F3) phases, consisting in around 0.5 ml each one using Pasteur pipettes by rounded movements. The experiment was six times replicated using a total of 24 ejaculates. It was determined the sperm recovery rate, sperm quality (sperm motility, concentration, viability, morphology and membrane functionality) and the sperm subpopulations in each of the different fractions obtained after the colloid centrifugation.

Sperm recovery rate Sperm samples were diluted 1:200 and concentration was assessed using a Thoma counting chamber. It was determined the sperm recovery rate in each fraction: Sperm recovery rate = concentration after centrifugation × volume after centrifugation × 100 concentration before centrifugation × volume before centrifugation

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Sperm motility assessment ISAS software v.1.2 (Proiser, Valencia, Spain) was used for sperm motility assessment. Sperm samples were diluted with TCFEY extender to reach a final concentration of 25 × 106 spermatozoa/ml. Samples were maintained at 37 ºC for 10 min and later, a drop (5 µL) was placed on a slide covered with 22 × 22 mm coverslips. Four fields or a minimum of 500 spermatozoa were randomly captured at 25 frames per second. Head sperm area was considered from 10 to 70 µm2. Spermatozoa were categorized as motile when VAP >10 µm/sec, and when they deviated <80 % from a straight line were classified as linearly motile. The following parameters were determined for each analysed sperm sample: total motility (TM; %), progressive motility (PM; %), curvilinear velocity (VCL; µm/sec), straight-line velocity (VSL; µm/sec), average path velocity (VAP; µm/sec), straightness (STR; %), linearity (LIN; %), wobble (WOB; %), amplitude of lateral head displacement (ALH; µm), and beat/cross frequency (BCF; Hz).

Sperm membrane functionality assessment Hypo-osmotic swelling test (HOST)(16)was used to determine the functional membrane status of spermatozoa. From each sperm fraction, 10 µL was diluted into 100 µL of hypoosmotic sodium citrate solution (1.351 g fructose, 0.735 g sodium citrate, and 100 mL bidistilled water; 100 mOsmol/kg) and warmed at room temperature for 30 min. After incubation, samples were fixed in 2% glutaraldehyde and observed under phase contrast microscopy (× 400 magnification). The sperm membrane was considered intact and functional when the sperm tail exhibited coiling. A total of 200 sperm cells were analyzed and the results were expressed as percentage of positive endosmosis.

Sperm morphology assessment Hemacolor staining (Merck, Darmstadt, Germany) was used to identify different sperm morphological abnormalities(17). A volume of 10 µl of semen was spread on a slide and stained according to the manufacturer’s instructions. The percentage of sperm abnormalities was determined by counting around 200 sperm cells (× 1000 magnification) (Olympus, Tokyo, Japan).

Sperm viability assessment Sperm viability was assessed by eosin-nigrosin stain(18). In brief, a total of 0.67 g Eosin Y (Panreac, Barcelona, Spain) and 0.9 g sodium chloride (Panreac, Barcelona, Spain) were dissolved in bi-distilled water (100 mL) under gentle heating, and then 10 g nigrosin (Panreac, Barcelona, Spain) was added. A 10 µL drop of sperm sample was mixed with a 10 µL drop of stain on a glass slide and the smear was made. For evaluation, 200 sperm cells were analyzed (× 1000 magnification) (Olympus, Tokyo, Japan). The spermatozoa were categorized as live (i.e. membrane was intact) when cells were unstained or as dead

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(i.e. membrane was altered) when they were pink-stained by eosin. Results were expressed as percentage of live sperm.

Statistical analysis The SPSS 17.0 package (SPSS, Chicago, IL, USA) was used for statistical analysis. Data are shown as a mean ± SD. Normality was tested using the Shapiro-Wilks test and when data were not normal, they were transformed. Those variables expressed as percentages (LIN, STR and WOB) were arcsine transformed, while others expressed as absolute values (VCL, VSL, VAP, ALH and BCF) were log transformed. Sperm parameters at the different fractions obtained after SLC in samples containing C800 or C3000 were compared with the fresh sperm values in order to determine the recovery rate and the sperm quality. One-way ANOVA was performed to compare the sperm recovery rate and sperm quality. Bonferroni post hoc test was used when significant differences between fractions (P≤0.05) were detected. In order to identify specific sperm subpopulations based on the kinetic parameters, a total of 20,485 observations from fresh and processed semen were evaluated using clustering procedures. Firstly, a principal components (PC) analysis was carried out on the data to reduce the eight studied variables (VCL, VSL, VAP, LIN, STR, WOB, ALH, and BCF) to the smallest number of linear combinations of the initial variables (called PCs) that save the majority of information of the original variables. It was expected that a few PCs explain a high proportion of the total variance. The VARIMAX rotation method was used and the number of PCs was selected using the Kaiser criterion for selecting those with an eingen value greater than 1. After that, a two-step cluster procedure was used to analyze the sperm-derived indexes obtained after PC. Different subpopulations were then identified and outliers were detected. The type of sperm subpopulation was analyzed in each sperm sample and the Chi square test was used to compare the relative frequencies of subpopulations within each sperm sample (or fraction).

Results Recovery rate by SLC After sperm separation by SLC, the percentage of sperm recovery in the fraction containing the theoretically best spermatozoa (F3) showed no significant differences (P>0.05) between C800 and C3000 (36.1 % and 27.5 %, respectively) (Figure 2). In addition, it was observed a significantly higher percentage of isolated spermatozoa in F1 in C3000 samples than in C800 samples, in contrast with those happened in F2. No significant differences were observed between the three obtained fractions after SLC in C800 sperm samples. By contrast, C3000 samples recovered significantly higher percentage of spermatozoa in F1 than in F3.

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Figure 2: Sperm recovery rate (%) at different fractions obtained after SLC in samples containing 800 and 3000 × 106 spz/ml; (C800 and C3000)

Asterisk indicate significant differences (P≤0.05) between the same fraction in samples containing different sperm concentrations. A, B Different uppercase letters indicate significant differences (P≤0.05) between different fractions.

Sperm assessment Table 1 shows the motility values corresponding to spermatozoa isolated in the different fractions after SLC. No sperm motility differences were observed between the different fractions isolated after SLC both in C800 and C3000. Table 1: Mean (  SD) values of motility and kinematic parameters from different sperm fractions obtained after SLC in samples containing 800 and 3000 × 106 spz/ml (C800 and C3000) Item Fraction C800 C3000 FRESH TM (%)

PM (%) VCL

F1 F2 F3 Whole F1 F2 F3 Whole F1

SLC 89.0 ± 2.0 88.4 ± 6.8 89.5 ± 2.5

87.9  3.7

FRESH

SLC 86.0 ± 3.5 86.5 ± 4.0 88.5 ± 6.1

89.8  3.06 50.3 ± 7.0 41.7 ± 9.6 37.0 ± 18.4

48.8  12.2

48.2 ± 4.8 56.2 ± 12.2 48.4 ± 20.2 50.2  9.0

121.4 ± 17.6

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(µm/s)

VSL (µm/s)

VAP (µm/s)

LIN (%)

STR (%)

WOB (%)

ALH (µm)

BCF (Hz)

F2 F3 Whole F1 F2 F3 Whole F1 F2 F3 Whole F1 F2 F3 Whole F1 F2 F3 Whole F1 F2 F3 Whole F1 F2 F3 Whole F1 F2 F3 Whole

127.3 ± 12.8 133 ± 18.6 117.9  11.1

120 ± 9.7 129.9 ± 12.9 124.2  4.7

72.2 ± 13.9 66.5 ± 12.4 69.1 ± 12.3 59.9  18.6

69.7 ± 7.1 81.8 ± 11.8 71.7 ± 14.6 58.2  18.1

94.9 ± 16.5 94.2 ± 15.4 96.5 ± 14.5 80.23  18.0

91.5 ± 7.4 100.2 ± 6.9 95.1 ± 12.0 77.9  17.5

59.4 ± 6.3 52.2 ± 9.0 52.9 ± 11.2 50.0  10.2

58.4 ± 3.5 68.4 ± 12.3 56.7 ± 14.9 46.6  12.9

76.1 ± 5.5 70.5 ± 5.7 71.4 ± 6.9 72.8  6.3

76.1 ± 2.1 81.3 ± 8.7 74.7 ± 7.8 73.7  5.8

77.9 ± 4.6 73.7 ± 8.3 73.5 ± 10.6 66.7  9.4

76.8 ± 3.4 83.8 ± 7.8 74.6 ± 13.3 62.5  12.3

3.4 ± 0.4 3.8 ± 0.4 3.9 ± 0.9 3.78  0.3

3.5 ± 0.4 3.1 ± 0.5 3.9 ± 1.2 4.3  0.4

8.9 ± 3.2 8.9 ± 2.7 10.1 ± 4.0 11.9  0.9

10.3 ± 0.3 10.0 ± 0.8 10.9 ± 2.0 12.9  1.6

6

C800= Sample with 800 × 10 spz/ml; C3000= Sample with 3000 × 106 spz/ml; SLC= Single layer centrifugation; F1= top phase, F2= medium phase; F3= bottom phase; TM= total motility; PM= progressive motility; VCL= curvilinear velocity; VSL= straight-line velocity; VAP= average path velocity; STR= straightness; LIN: linearity; WOB= side to side movement of the sperm head; ALH= amplitude of lateral head displacement; BCF= beat/cross frequency.

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Table 2 represents sperm viability, morphology and membrane functionality of samples processed. Although F3 showed the higher values in all the studied parameters, no significant differences (P>0.05) were observed in relation with the other fractions or between samples with different sperm concentrations.

Table 2: Mean (  SD) values of viability, morphology, membrane functionality from different sperm fractions obtained after SLC in sperm samples Parameters

Viability (%)

Morphology (%)

Membrane functionality (%)

Fraction F1 F2 F3 Whole F1 F2 F3 Whole

C800 FRESH

89.0  8.9

SLC 81.2 92.0 17.1 8.6 95.4 5.4

± ± ±

87.6  5.1

61.0 25.9 80.7 15.5 85.3 6.6 64.5 15.8 65.5 9.9 68.3 9.8

± ± ±

F1 F2 F3 Whole

C3000 FRESH

65.4  1.7

± ± ± 89.5 14.6

90.1 3.3

80.6 4.5

SLC 91.3 93.5 10.2 8.2 94.8 5.7

± ± ±

83.5 7.1 90.3 5.9 93.5  5.1

± ± ±

75.3 7.9 78.7 2.7 80.7  3.8

± ± ±

C800= sample with 800 × 106 spz/ml; C3000= sample with 3000 × 106 spz/ml; SLC= Single layer centrifugation; F1= top phase, F2= medium phase; F3= bottom phase.

Sperm subpopulations Three sperm subpopulations were identified in a total of 20,485 individual motile spermatozoa analyzed, as shown in Table 3. Three PCs were obtained after the data reduction, which explain the 76.70 % of the variance. PC1 was associated with VCL, VSL, and VAP; PC2 was related with STR and LIN, and PC3 showed association with WOB (Table 4).

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Table 3: Mean ( SD) values of kinematic and velocity parameters used for the characterization of three sperm subpopulations identified in fresh ovine semen samples Subpop.

N

%

SP1

3906

19.1

SP2

8950

43.7

SP3

7629

37.2

Total

20485

100

VCL (µm/s) 65.5  41.4 121  36.2 154.4  35.2 122.8  48.6

VSL (µm/s) 18.5  13.4 93.1  31.7 61.4  26.7 67.1  38.7

VAP (µm/s) 38.9  27.4 106.9  34.4 96.7  26.9 90.1  39.6

LIN (%) 31  2 77  1 40  2 55  2

STR (%) 52  2 87  1 65  2 72  2

WOB (%) 60  1 88  8 63  1 73  2

ALH (µm) 2.9  1.7 3.1  1.2 5.4  1.4 3.9  1.8

BCF (Hz) 5.5  2.5 9.4  2.8 12.9  3.1 10  3.9

VC=curvilinear velocity; VSL= straight-line velocity; VAP= average path velocity; STR= straightness; LIN= linearity; WOB= Side to side movement of the sperm head; ALH= Amplitude of lateral head displacement; BCF= Beat/cross frequency.

Table 4: Principal component analysis of 8 sperm parameters, using Varimax rotation Eigenvalue Percentage Cumulative percentage VCL VSL VAP ALH BCF LIN STR WOB

PC1

PC2

PC3

2.55 31.91 31.91 0.96 0.70 0.92 0.46 0.23 0.11 0.06 0.17

2.27 28.35 60.26 0.01 0.64 0.16 -0.18 0.13 0.82 0.98 0.39

1.31 16.44 76.70 - 0.06 0.24 0.29 - 0.28 - 0.02 0.53 0.15 0.89

Loadings exceeding 0.70 are highlighted in bold.

Spermatozoa included in subpopulation 1 (SP1) showed lower velocity (based on VCL, VSL and VAP) and no progressive motility (low values for LIN, STR, WOB, ALH and BCF); a total of 19.1 % of spermatozoa came within this subpopulation. Subpopulation 2 (SP2) showed high velocity (VCL, VSL, VAP and ALH), high progressivity (high LIN, STR and WOB) and good ALH and BCF. This subpopulation could be defined as consisting of rapid and progressive spermatozoa, with 43.7 % of the spermatozoa came within this subpopulation. Subpopulation 3 (SP3) showed high values of VCL, ALH and BCF, while LIN and STR values were low; these were defined as rapid and nonlinear spermatozoa and a total of 37.2% of spermatozoa were included in this subpopulation. In C800 samples, the SP3 was significantly higher in the F2 and F3 than in F1, while SP1 and SP2 were significantly higher in the F1 than in the others (Figure 3).

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Figure 3: Relative frequency distribution of sperm subpopulations into the different sperm fractions obtained after SLC in samples containing 800 and 3000 × 106 spz/ml; (C800 and C3000)

ab

Different uppercase letters indicate significant differences (P≤0.05) between different fractions for each concentration.

The distribution of subpopulations varied in C3000 samples. SP2 (rapid and progressive) was significantly higher in F1 than in F3 (or selective fraction) and F2. SLC in this type of samples provoked that the majority of spermatozoa contained into F3 (i.e. fraction containing the theoretically best spermatozoa) were from SP3 (rapid non progressive).

Discussion The present study evaluates the sperm separation capacity and the characteristics of the isolated sperm fractions after SLC in normospermic ram samples. These samples were prepared with a volume around 1.5 mL and containing 800 or 3000 × 106 spermatozoa/mL, in order to invest if this sperm separation procedure could be efficient on ram fresh ejaculates. In addition, by focusing on eight kinematic parameters, three different sperm subpopulations were found in whole fresh ejaculates and in separated fractions obtained by SLC. It is known that sperm centrifugation can affect motility and membrane integrity in small ruminant spermatozoa(19,20). However, the use of centrifugation combined with colloids could be an interesting option to select the best spermatozoa for improving AI results.

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The present study suggest that SLC does not offer an adequate separation of spermatozoa based on motility, viability, morphology or membrane functionality when normospermic ram semen is processed. In a recent study carried out on red deer(21), it has been demonstrated that the type of colloids affects the efficiency of the layer centrifugation technique, and DLC offers better separation ability if low-quality sperm samples were used(22). In the present study, spermatozoa isolated in F3 after SLC (where are expected the best spermatozoa were found) did not achieve higher sperm motility (total and progressive) than spermatozoa located in the other fractions after centrifugation. As far as sperm morphology is concerned, although the results showed that morphological abnormalities are reduced while sperm crosses the colloid layers, differences were not significant. These results are in line with those obtained in wild ruminants(23) and in llama(24), observing no morphological sperm differences between fresh and separated spermatozoa in good quality semen samples. In bull sperm, colloidal procedures increased the number of normal morphological spermatozoa in poor-quality samples(25). However, when SLC was used with normospermic samples, it was here observed that no advantages were obtained in terms of separating morphologically normal spermatozoa. The sperm membrane functionality did not vary after application of SLC in C800 or C3000 sperm samples. The present results showed that SLC is not able to separate spermatozoa with injured membrane functionality, morphology and viability, in agree with results reported for equine samples separated by SLC using Androcoll(26). In addition, studies of normospermic bull sperm have concluded that there was no effect on samples before and after application of SLC in comparison with untreated samples(25). To the present authors’ knowledge, this is the first study of ram sperm to analyze sperm subpopulations in different sperm fractions obtained by SLC. It has been affirmed that ejaculates have heterogeneous sperm subpopulations, which determine their fertility, i.e. their success after insemination through natural spermatozoa selection(27). And fertility can be also promoted by the different procedures for spermatozoa selection, such as centrifugation through colloids. After the evaluation of individual kinematic parameters in ram spermatozoa samples, three different subpopulations were selected with differential characteristics, in keeping with other authors(28,29). As expected in normospermic ejaculates, the subpopulation showing spermatozoa with low and non-progressive motility (SP1) was poorly represented in the sperm sample (19.1 %). By contrast, SP2 (classified as rapid progressive subpopulation) showed a total of 43.7 % of spermatozoa came within this subpopulation, being the higher subpopulation. Finally, SP3 showed high values of VLC and ALH, while LIN and STR values were low, and a total of 37.2 % of spermatozoa were included in this subpopulation, being classified as rapid and nonlinear, in line with other authors(28,29). The results obtained after centrifugation and different fractions isolation suggest that SLC does not separate the best motility quality subpopulation, whether in C800 or in C300 397


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sperm samples, not being SP2 the most abundant subpopulation in F3, as expected. It was observed that many spermatozoa belonging to SP2 (considered as the best subpopulation) were retained in the second interface; one possible explanation for this observation is that the high number of spermatozoa included in the sample may impede other optimal spermatozoa from swimming to the bottom of the tubes(30). As previously recommended(31), SLC it is better to use for processing of large volumes of semen, suggesting that the increment of the sperm concentration was an impediment to the efficient operation of this method. In keeping with others(23), the present results showed that sperm selection techniques do not improve sperm quality in non-stressed sperm samples.

Conclusions and implications In summary, colloid centrifugation is not an effective method for sperm selection when samples containing a high concentration of spermatozoa with good quality (i.e. normospermic sperm samples) are processed. Further studies should be conducted with low quality sperm samples to determine the sperm separation efficiency of colloidal centrifugation in ram sperm, and also to determine the freezability of sperm fractions separated by colloid centrifugation.

Literature cited: 1. Palacín I, Vicente-Fiel S, Santolaria P, Yániz JL. Standardization of CASA sperm motility assessment in the ram. Small Ruminant Res 2013;(1-3):128-135. 2.

Martínez-Pastor F, Garcia-Macias V, Álvarez M, Herráez P, Anel L, de Paz P. Sperm Subpopulations in Iberian red deer epididymal sperm and their changes through the cryopreservation process. Biol Reprod 2005;(2):316-327.

3.

Aalberts M, Sostaric E, Wubbolts R, Wauben MW, Nolte-'t Hoen EN. Spermatozoa recruit prostasomes in response to capacitation induction. Biochim Biophys Acta 2013;(11):2326-2335.

4.

Ou Z, Yanf L, Chen Z, Deng Y, Wang H, Sun L. Comparison of the outcomes of different human spermatozoa selection methods in assisted reproduction. Biomed Res 2018;(12):2615-2619.

5.

Kaneko S, Oshio S, Kobanawa K, Kobayashi T, Mohri H, Iizuka R. Purification of human sperm by a discontinuous Percoll density gradient with an innercolumn. Biol Reprod 1986;(4):1059-1063.

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6.

Valcárcel A, de las Heras MA, Moses DF, Pérez LJ, Baldassarre H. Comparison between Sephadex G-10 and Percoll for preparation of normospermic, asthenospermic and frozen/thawed ram semen. Anim Reprod Sci 1996;(3-4):215224.

7.

Matás C, Vieira L, García-Vázquez FA, Avilés-López K, López-Úbeda R, Carvajal JA et al. Effects of centrifugation through three different discontinuous Percoll gradients on boar sperm function. Anim Reprod Sci 2011;(1-2):62-72.

8.

Morrell JM, Johannisson A, Dalin AM, Rodriguez-Martinez H. Morphology and chromatin integrity of stallion spermatozoa prepared by density gradient and single layer centrifugation through silica colloids. Reprod Domest Anim 2009;(3):512-517.

9.

Morrell JM, Rodriguez H. Colloid centrifugation of semen: Applications in assisted reproduction. Am J Analyt Chem 2016;(7):597-610.

10. Edmond AJ, Brinsko SP, Love CC, Blanchard TL, Teague SR, Varner DD. Effect of centrifugal fractionation protocols on quality and recovery rate of equine sperm. Theriogenology 2012;(5):959-966. 11. Morrell JM. Biomimetics in Action: Practical applications of single layer centrifugation for equine breeding. J Vet Sci Technol 2011;(2):107. 12. Goodla L, Morrell JM, Yusnizar Y, Stalhammar H, Johannosson A. Quality of bull spermatozoa after preparation by single-layer centrifugation. J Dairy Sci 2014;(4):19. 13. Nongbua T, Johannisson A, Edman A, Morrell JM. Effects of single layer centrifugation (SLC) on bull spermatozoa prior to freezing on post-thaw semen characteristics. Reprod Domest Anim 2017;(4):596-602. 14. Yulnawati Y, Abraham MC, Laskowski D, Johannisson A, Morrell JM. Changes in bull sperm kinematics after single layer centrifugation. Reprod Domest Anim 2014; (6):954-956. 15. Gosalvez J, Johnston S, Lopez-Fernandez C, Gosalbez A, Arroyo F. Sperm fractions obtained following density gradient centrifugation in human ejaculates show differences in sperm DNA longevity. Asian Pacific J Reprod 2014;(3):116-120. 16. Jeyendran RS, Van der Ven HH, Perez-Pelaez M, Crabo BG, Zaneveld LJD. Development of an assay to assess the functional integrity of the human sperm membrane and its relationship to other semen characteristics. J Reprod Fertil 1984; (1):219-228. 17. World Health Organization. WHO laboratory manual for the examination and processing of human semen. 5th ed. Cambridge University Press; 2010.

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18. Björndahl L, Soderlund I, Kvist U. Evaluation of the one-step eosin-nigrosin staining technique for human sperm vitality assessment. Hum Reprod 2003;(4):813-816. 19. Ritar AJ. Control of ovulation, storage of semen and artificial insemination of fibreproducing goats in Australia: a review. Aust J Exp Agric 1993;(6):807-820. 20. Gil J, Söderquist L, Rodríguez-Martínez H. Influence of centrifugation and different extenders on post-thaw sperm quality of ram semen. Theriogenology 2000;(1):93108. 21. García-Álvarez O, Soler AJ, Maulen Z, Maroto-Morales A, Iniesta-Cuerda M, Martín-Maestro A et al. Selection of red deer spermatozoa with different cryoresistance using density gradients. Reprod Domest Anim 2016;(6):895-900. 22. Maxwell WMC, Parrilla I, Caballero I, Garcia E, Roca J, Martínez EA et al. Retained functional integrity of bull spermatozoa after double freezing and thawing using PureSperm® density gradient centrifugation. Reprod Domest Anim 2007;(5):489494. 23. Santiago-Moreno J, Esteso MC, Castaño C, Toledano-Díaz A, Rodríguez E, LópezSebastián A. Sperm selection by Capripure® density-gradient centrifugation versus the dextran swim-up procedure in wild mountain ruminants. Anim Reprod Sci 2014;(3-4):178-186. 24. Santa Cruz R, Giuliano SM, Gambarotta MC, Morrell JM, Abraham MC, Miragaya MH et al. Comparison of differents methods of sperm selection of llama raw semen. Anim Reprod Sci 2016;(173):8-12. 25. Gloria A, Carluccio A, Wegher L, Robbe D, Befacchia G, Contri A. Single and double layer centrifugation improve the quality of cryopreserved bovine sperm from poor quality ejaculates. J Anim Sci Biotechnol 2016;(7):1-9. 26. Gamboa S, Quaresma A, Castro F, Bravo P, Rebordão MR, Oom MM et al. In vivo fertilizing ability of stallion spermatozoa processed by single layer centrifugation with Androcoll-E™. Saudi J Biol Sci 2017;(7):1489-1496. 27. Holt WV, Van Look KJW. Concepts in sperm heterogeneity, sperm selection and sperm competition as biological foundations for laboratory tests of semen quality. Reproduction 2004;(5):527-535. 28. Santolaria P, Vicente-Fiel S, Palacín I, Fantova E, Blasco ME, Silvestre MA et al. Predictive capacity of sperm quality parameters and sperm subpopulations on field fertility after artificial insemination in sheep. Anim Reprod Sci 2015;(163):82-88. 29. Yániz JL, Palacín I, Vicente-Fiel S, Sánchez-Nadal JA, Santolaria P. Sperm population structure in high and low field fertility rams. Anim Reprod Sci 2015;(156):128-134.

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30. Bergstein TG, Bicudo LC, Rodello L, Weiss RR, Bicudo SD. Kinematic and spermatic recovery after selection by centrifugation in colloid solutions of ovine cryopreserved semen. Arq Bras Med Vet Zootec 2016;(6):1539-1547. 31. Morrell JM,Van Wienen M, Wallgren M. Single layer centrifugation can be scaledup further to process up to 150 ml semen. ISRN Vet Sci 2012;1-6.

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https://doi.org/10.22319/rmcp.v12i2.4918 Article

Cowpea [Vigna unguiculata (L.) Walp] herbage yield and nutritional quality in cowpea-sorghum mixed strip intercropping systems

Muhammad Aamir Iqbal a Asif Iqbal b Zahoor Ahmad c Ali Raza d Junaid Rahim e Muhammad Imran e Umer Ayyaz Aslam Sheikh e Qaiser Maqsood f Walid Soufan g Nesma M.A. Sahloul h Sobhy Sorour h Ayman El Sabagh h

a

University of Poonch Rawalakot (AJK). Faculty of Agriculture, Department of Agronomy, Pakistan. b

University of Agriculture Faisalabad, Department of Agronomy, Pakistan.

c

University of Central Punjab, Bahawalpur Campus, Department of Botany, Pakistan.

d

Fujian Agriculture and Forestry University, Fujian Provincial Key Laboratory of Crop Molecular and Cell Biology, China. e

University of Poonch Rawalakot (AJK). Faculty of Agriculture, Department of Entomology, Pakistan. f

Government College University Faisalabad, Layyah University, Department of Botany, Pakistan. 402


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g

King Saud University. Plant Production Department, Saudi Arabia.

h

Kafrelsheikh University. Faculty of Agriculture, Department of Agronomy, Egypt.

*Corresponding author: muhammadaamir@upr.edu.pk

Abstract: In traditional row and strip cowpea-sorghum intercropping systems, cowpea forage yield reduces significantly due to intense competition and dominance of sorghum in acquiring growth resources. This field study evaluated novel mixed strip intercropping systems of forage cowpea and sorghum having different number of crops rows arranged under different spatial arrangements. Cowpea was intercropped with sorghum in 8, 12 and 16 rows strips with row-row spacing of 30, 45 and 60 cm. In each strip, equal number of rows of cowpea and sorghum were maintained. Factorial arrangement of randomized complete block design with three replicates was used to execute the field trials during summer seasons of 2013 and 2014. Strips having 12 rows and 60 cm rowrow spacing positively affected all agronomic variables of cowpea which led to maximum forage yield (22.2 and 23.7 t ha-1 during 2013 and 2014 respectively) and dry matter biomass (6.63 and 6.94 t ha-1 during 2013 and 2014 respectively). In contrast, 8rows strips having line spacing of 30 cm outperformed other intercropping systems by yielding the maximum herbage yield and dry matter biomass of sorghum. The intercropping system comprising of 12-rows strips with 60 cm row-row spacing remained superior in recording the maximum crude protein, fats and total ash along with the minimum fiber content of cowpea. In addition, this intercropping system under rest of spatial arrangements also remained unmatched, while 16-rows strips under all planting geometries remained inferior to other intercropping systems. Thus, cowpea intercropping with sorghum in 12-rows strips having 60 cm spacing offers biologically viable solution to improve biomass and forage quality of cowpea in intercropping with sorghum. Key words: Animal nutrition, Planting geometries, Row intercropping.

Received: 30/05/2018 Accepted: 31/08/2020

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Introduction Food security of rapidly increasing human populace demands proportionate increment in milk and meat production globally(1,2). Under changing climate, production of forages with acceptable nutritional quality occupies central place for obtaining milk production on sustainable basis(3). Although, many cereals including sorghum provide huge tonnage of biomass but these are unable to provide balanced nutrition to dairy animals(4,5,6). Resultantly, expensive protein supplements need to be provided which result in slicing of economic returns. In addition, ruminants population is increasing globally which necessitate producing huge quantities of nutritional and cheaper forage throughout the year(7,8). Thus, intercropping cereals with legumes might lead to achieve the dual purpose of obtaining higher quantities of forage with improved nutritional quality. Row, mixed and strip intercropping of cereals with legumes have been practiced since long(9,10). Intercropping forage legumes with cereals diversified the farm resources, preserved and restored soil fertility and improved the efficiency of soil and environmental resources(11,12). However, serious consideration must be done in choosing the legume intercrops with respect to their compatibility in utilizing resources in spatial and temporal dimensions. Among legume intercrops, cowpea [Vigna unguiculata (L.) Walp] could be a good option for having potential to yield considerably higher quantity of nutritious forage in intercropping with sorghum(13,14,15). In addition, cowpea holds potential to tolerate shade and sustain moderate drought along with fixing atmospheric nitrogen which favor its utilization as an intercrop with cereals(16,17). However, cowpea intercrop suffered losses in forage yield and nutritional quality owing to dominance of cereals in acquiring growth resources(18,19). In this way, the type of intercropping becomes pivotal for achieving the added advantage of cowpea intercropping with cereal forages(20). Thus, in sorghum-cowpea intercropping systems, the real challenge lies in preventing the drastic reduction in the yield and quality of forage cowpea. Various studies have reported contrasting results about the efficacy of strip intercropping system where separate strips of component crops were maintained (8,21,22) . But, there have rarely been any field investigation regarding mixed strip intercropping system entailing rows of component crops in the same strip. In addition, spatial arrangement of component crops also determined the complementarity and competition in cereal-legume intercropping systems(2,14). However, spatial arrangements must be optimized with respect of intercropping type especially for boosting the productivity of legumes. Thus, it was hypothesized that optimization of strip intercropping systems and spatial arrangements might lead to improved yield and nutritional value of cowpea forage. The present study aimed primarily to investigate the influence of mixed strip intercropping (strips having rows of both cowpea and sorghum in the same strip) and planting geometries on forage yield of cowpea sown with forage sorghum. Furthermore, another 404


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objective was to test the agro-qualitative traits of forage cowpea as influenced by different strip intercropping systems as well as spatial arrangements.

Material and methods Description of experimental site

To evaluate the impact of mixed strip intercropping and planting geometries on the productivity of cowpea intercrops, a field experiment was conducted during summer months of 2013 and 2014 at the research area of University of Agriculture, Faisalabad (30.35-41.47°N and 72.08-73.40°E) situated at an attitude of 184 m(14). The climate of the experimental area falls into Koppen’s class of semi-arid, while the soil of the experimental site is classified as Haplic Yermosols as per FAO soil classification system. The meteorological data for crop growing seasons of cowpea were obtained from the meteorological center located closer (about 1 km) to research fields (Table 1).

Table 1: Meteorological data for crop growing seasons of cowpea in 2013 and 2014 along with 10 years mean (10YM) values

2013

2014

10YM

2013

2014

10YM

Relative humidity (%) 2013 2014 10YM

June

40.3

41.5

40.1

44

40

40

60

64

59

July

39.5

38.6

41.0

106

102

101

65

72

62

August

35.0

37.8

34.7

77

68

72

58

69

65

Mean/Total 38.2

39.3

38.6

227

210

213

61.0

68.3

65.3

Month

Temperature (°C)

Rainfall (mm)

Experimental treatments and design

Cowpea and sorghum were sown in different strip intercropping systems and three spatial arrangements as follows: T1A1= 8 rows strips (cowpea-sorghum in 4-4 rows in the same strips) with 30 cm row-row spacing, T1A2= 8 rows strips (cowpea-sorghum in 4-4 rows in the same strip) with 45 cm row-row spacing, T1A3= 8 rows strips (cowpeasorghum in 4-4 rows in the same strip) with 60 cm row-row spacing, T2A1= 12 rows 405


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strips (cowpea-sorghum in 6-6 rows in the same strip) with 30 cm row-row spacing, T2A2= 12 rows strips (cowpea-sorghum in 6-6 rows in the same strip) with 45 cm rowrow spacing, T2A3= 12 rows strips (cowpea-sorghum in 6-6 rows in the same strip) with 60 cm row-row spacing, T3A1= 16 rows strips (cowpea-sorghum in 8-8 rows in the same strip) with 30 cm row-row spacing, T3A2= 16 rows strips (cowpea-sorghum in 8-8 rows in the same strip) with 45 cm row-row spacing, T3A3= 16 rows strips (cowpeasorghum in 8-8 rows in the same strip) with 60 cm row-row spacing. In this way, a total of 9 treatment combinations were tested in factorial arrangement of randomized complete block design (RCBD) with three replications. The strip × strip distance for all intercropping systems was kept at 70 cm. Cowpea rows were adjacent to sorghum rows in subsequent strips. There was no consideration for plant × plant distance. In total, there were 27 experimental plots which were homogeneously maintained for testing the proposed treatments.

Agronomic management plan

In order to formulate the soil fertility management plan, pre-sowing physico-chemical analysis was performed from soil samples collected from 15 and 30 cm depth (Table 2). The seedbed preparation was started with a pre-sowing irrigation of 12 cm and 3 tractor mounted cultivations each followed by planking was done. Cowpea (cv. P-51840 at kg ha-1) and sorghum (cv. Hegari at 80 kg ha-1) were intercropped in 30 cm spaced rows using a hand drill. Recommended dose of nitrogen (50 kg ha-1) (urea) was applied in two splits (at the time of sowing and with first irrigation 12 d after sowing) while total phosphorous (single super phosphate) (40 kg ha-1) was applied as basal dose. Three flood irrigations were applied at 12, 33 and 50 d after sowing. Manual hoeing was done thrice (12, 22 and 32 d after sowing) to keep weed infestation at bay. Cowpea intercrops were harvested using hand sickle at complete flowering.

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Table 2: Pre-sowing physico-chemical analysis of experimental soil in 2013 and 2014 Soil characteristics Mechanical analysis: Sand, % Silt,% Clay, % Textural class Chemical analysis: Ph EC, dSm-1 Organic matter, % Available nitrogen, ppm Available phosphorous, ppm Available potassium, ppm

2013

2014

57.0 17.5 25.5 Sandy clay loam

54.5 19.3 26.2 Sandy clay loam

7.9 1.68 0.75 6.1 0.96 117

7.6 1.64 0.78 6.4 0.91 112

Data recordings

All agronomic attributes of cowpea were recorded at the time of harvesting by following the prescribed methods. Ten plants were harvested from middle rows of each replication and then their average was taken. Plant height was recorded with the help of tailor’s measuring tape from base of the plant to the tip of the highest leaf. Stem girth was taken by using vernier caliper. Electric balance was used to take fresh weight per plant while spring balance was used to record green forage yield per plot which was then converted into tons per hectare. The agro-qualitative attributes of forage cowpea were determined by using methodologies given in Table 3.

Table 3: Procedure adopted for measuring agro-qualitative traits of cowpea as suggested by AOAC (2003) Quality attributes

Methodology

Crude protein

Macro-KJeldahl method and subsequently multiplying nitrogen percentage with a constant of 6.25

Crude fiber

H2SO4 and NaOH digestion method

Ether extractable fat Soxhlet extraction method Total ash

Ashing at 600 °C using muffle furnace technique

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Statistical analysis

Statistical analyses of the recorded data were done through employing analysis of variance (ANOVA) using the statistical program “Statistix 8.1”. The means were grouped for conducting orthogonal contrasts on following basis; (a) intercropping system versus year, (b) spatial arrangement versus year, (c) intercropping system versus spatial arrangement and (d) intercropping system versus spatial arrangement versus year at 5% probability level. The data were also subjected to correlation analysis in order to sort out the relationship (linear or inverse) between yield attributes and forage yield of cowpea.

Results and discussion Plant height and stem diameter

The agronomic variables of forage cowpea were significantly improved during 2014 probably owing to higher precipitation and moderate temperatures in comparison to 2013. The interactive effect of strip intercropping systems and spatial arrangements was significant for plant height (189** and 203** during 2013 and 2014 respectively) and stem girth (88* and 98** during 2013 and 2014 respectively) of cowpea (Table 4). The tallest cowpea plants (110.3 ± 0.57 and 117.9 ± 0.83 cm during 2013 and 2014 respectively) with greatest stem girth (2.87 ± 0.67 and 2.94 ± 0.69 cm during 2013 and 2014 respectively) were recorded by cowpea sown in 12-rows strips with 60 cm spaced rows (T2A3), while 16-rows strips having 45 cm line-line spacing (T3A2) resulted in the lowest plant height (78.0 ± 0.38 and 83.1 ± 0.82 cm during 2013 and 2014 respectively) as well as stem girth (2.32 ± 0.81 and 2.53 ± 0.41 cm during 2013 and 2014 respectively) (Table 5). Correlation analysis revealed that there was linear correlation between plant height and stem girth of cowpea as depicted in Figure 1. These results are in complete confirmation with another study(23), where legumes plant height and stem diameter were influenced planting geometries of cereal-legume intercropping systems. Simultaneous cultivation of component crops in row and mixed intercropping systems intensified inter-species competition for farm applied resources which led to reduced plant height and stem girth of legumes compared to their monocultures. But when cowpea was sown in 12-rows strips (cowpea-sorghum in 6-6 rows), it might have reduced sorghum dominance in acquiring growth resources. Varied root lengths of cowpea and sorghum might be attributed as the probable reason for reducing competition for growth resources which was further supported by wider strip spacing(24).

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Number of leaves and leaf-stem ratio

The interactive effect of intercropping systems and spatial arrangements was significant for the number of leaves (93* and 112* during 2013 and 2014 respectively) and leafstem ratio (83* and 96* during 2013 and 2014 respectively) (Table 4). Sorghum and cowpea 12-rows strip intercropping in 60 cm spaced lines (T2A3) resulted in higher number of leaves per plant (29.1 ± 0.57 and 29.9 ± 0.31 during 2013 and 2014 respectively) and leaf to stem ratio (0.59 ± 0.19 and 0.69 ± 0.21 during 2013 and 2014 respectively) (Table 5). These results corroborate with the findings of other studies(2,3,25), where it was concluded that closely spaced rows of legumes recorded minimum number of leaves and leaf-stem ratio despite exploring varied soil horizons for absorbing moisture and nutrients by sorghum and legumes, still the intra-species competition was severe enough to drastically reduce the growth of legume intercrops. Furthermore, shading effect rendered by sorghum was also found to be an important factor in reducing photosynthesis of legume plants particularly in adjacent rows with sorghum which leads to less number of leaves per plant.

Plants fresh and dry weights, green forage yield and dry matter biomass

The interactive effect of intercropping system and spatial arrangements was also significant for fresh weight (274** and 297** during 2013 and 2014 respectively) and dry weight (187** and 257** during 2013 and 2014 respectively) per plant of cowpea along with green forage yield (266** and 287** during 2013 and 2014 respectively) as well and dry matter yield (134** and 120** during 2013 and 2014 respectively). The highest fresh weight (188.6 ± 0.67 and 190.5 ± 0.61 g during 2013 and 2014 respectively) and dry weight (59.1 ± 0.67 and 66.3 ± 1.19 g during 2013 and 2014 respectively) per plant (Table 5) were rendered by 12-rows strip having 60 cm apart rows (T2A3). Correlation analysis depicted a linear relationship for fresh and dry weights per plant with green forage and dry matter yields (Figure 1). The same intercropping system (T2A3) was instrumental in yielding the maximum green forage yield (22.2 ± 0.28 and 23.7 ± 0.34 t ha-1 during 2013 and 2014 respectively) and dry matter biomass (6.63 ± 0.26 and 6.94 ± 0.19 t ha-1 during 2013 and 2014 respectively) of forage cowpea (Table 6), while it was followed by 12-rows strips sown in 45 cm spaced rows (T2A1). In contrast, sorghum-cowpea 8-rows strips having 30 cm row-row spacing (T2A1) remained superior as far as green forage biomass and dry matter yield of sorghum were concerned. It was followed by the same intercropping system having row-row spacing of 45 cm, while sorghum-cowpea intercropping systems comprising of 16-rows strips with 60 cm row-row spacing (T3A3) remained inferior to rest of intercropping systems and spatial arrangements (Table 6). The T2A3 intercropping 409


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system resulted in superior agronomic attributes including plant height, stem girth, fresh and dry weights per plant which ultimately enhanced green forage biomass as well as dry matter yield. These findings are in line with others(22,26), who inferred that productivity of cowpea in narrowly spaced (30 and 45 cm) intercropping systems remained below-par to solo cowpea despite well-developed nodulation and fully functional biological nitrogen fixation (BNF). Similar findings were also reported by other researchers(10,27), where cowpea remained recessive in acquiring nutrients and moisture compared to cereals. In addition, legume intercrops suffered losses in productivity owing to their dependence on soil solution for nitrogen before the initiation of BNF after 27-35 d of sowing. Moreover, in strip intercropping systems, cowpea rows adjacent to sorghum confronted lesser competition for growth resources by exploiting different soil horizons but had to face shading effect rendered by taller sorghum plants. Similarly, inner rows of cowpea faced lesser shading effect but competition for growth resources intensified owing to having same root length which led to reduced herbage yield(28).

Crude protein and crude fiber contents

All quality traits were significantly influenced by intercropping systems and spatial arrangements including crude protein (120** and 135** during 2013 and 2014 respectively), crude fiber (142* and 169** during 2013 and 2014 respectively), ether extractable fat (200** and 225*during 2013 and 2014 respectively) and total ash (101* and 109* during 2013 and 2014 respectively) (Table 4). Protein content occupies vital position in determining the nutritional quality of forage while agronomists as well as animal nutritionist recommend protein-rich forages for boosting the performance of dairy animals. Cowpea-sorghum intercropping in 12-rows strips having 60 cm row-row spacing (T2A3) effectively improved crude protein (19.9 ± 0.21 and 19.6 ± 0.37 during 2013 and 2014 respectively) of cowpea forage with the minimum crude fiber (26.1 ± 0.51 and 26.0 ± 0.90 during 2013 and 2014 respectively) contents (Table 6). This was followed by 12-rows strips having 45 cm spacing (T2A1), while strips having 16-rows performed below par under all spatial arrangements. Earlier research works(1,14) are in conformity with these findings, as it was reported that substantial enhancement in crude protein of mixed forage could be achieved by intercropping cowpea with cereal forages under optimized spatial arrangements. It was suggested that type of intercropping could influence nitrogen fixed by cowpea which might be attributed for improved crude protein content and reduced fiber as the absorbed nitrogen and protein content were linearly correlated. Type of intercropping and planting geometries as in our research have also been reported to improve the efficacy of applied nutrients which imparted a significant influence on protein and crude fiber contents of forages(14,29). 410


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Ether extractable fat and total ash contents

Fats are pivotal quality attribute of forages as these secrete higher amounts of energy during metabolism than proteins. Similarly, mineral constituents of forages required to perform various metabolic processes are measured as ash. The intercropping system (T2A3) resulted in the maximum fat (1.91 ± 0.17 and 1.95 ± 0.29 % during 2013 and 2014 respectively) and total ash (11.78 ± 0.16 and 11.7 ± 0.21 % during 2013 and 2014 respectively) (Table 6), 16-rows strips registered the minimum fat and ash contents without any regard to spatial arrangements. Strips having 8-rows under all planting geometries performed better in terms of forage quality than 16-rows strips but it remained below par to cowpea sown with forage sorghum in 12-rows strips. These findings also match with a previously conducted study(30), which revealed that considerably higher herbage yield with improved quality attributes could be obtained by optimizing intercropping type and spatial arrangement of component crops.

Conclusions and implications This study reports novel mixed strip intercropping systems to check the drastic reduction in forage yield cowpea while in intercropping with forage sorghum. As far as green forage yield and agro-qualitative traits of cowpea were concerned, it could be inferred that 12-rows strips (cowpea-sorghum in 6-6 rows) (T1A2) remained unmatched particularly when row-row spacing was maintained at 60 cm. Moreover, better growth of cowpea was observed in rows adjacent to sorghum rows in subsequent strips in comparison with cowpea rows adjacent to sorghum rows in the same strip. Strips having 16-rows irrespective of planting geometry could not come at par to rest of the strips probably due to higher intra-species competition for growth resources. However, these encouraging results necessitate further field investigations regarding mixed strip intercropping of cereal forages and legumes for boosting legumes yield under varied agro-climatic and agro-ecological conditions.

Acknowledgements

The research support under Researchers Supporting Project number RSP/2021/390, by King Saud University, Riyadh, Saudi Arabia, is thankfully acknowledged. Additionally, Higher Education Commission of Pakistan support Under Indigenous Fellowship (2AV1-215) is also acknowledged.

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Iqbal MA, Iqbal A, Ali K, Khan RD, Ahmad B, Raza A, Nabeel F. Integration of forage sorghum and by-products of sugarcane and sugar beet industries for ruminant nutrition: A Review. Global Vet 2015a;(14):752-760.

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Motha NK, De R. Intercropping maize and soybean. J Agric Sci 2009;(95):117122.

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Iqbal MA. Agronomic management strategies elevate forage sorghum yield: A Review. J Adv Bot Zoo 2015;(3):1-6.

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Rudra SG, Shruti S, Jha SK, Rajeev K. Physico-chemical and functional properties of cowpea protein isolateas affected by the dehydration technique. Leg Res 2016;(39):370-378.

9.

Mucheru MM, Pypers P, Mugendi D, Kungu J, Mugwe J, Merckx R, Vanlauwe B. A staggered maize-legume intercrop arrangement robustly increases crop yields and economic returns in the highlands of Central Kenya. Field Crops Res 2010;(115):132-139.

10. Crusciol CAC, Mateus GP, Nascente AS, Martins PO, Borghi E, Pariz CM. An innovative crop-forage intercrop system: early cycle soybean cultivars and palisade grass. Agron J 2012;(104):1085-1095. 11. Sanchez DGR, Silva JET, Gil AP, Corona JSS, Wong JAC, Mascorro AG. Forage yield and quality of intercropped corn and soybean in narrow strips. Span J Agric Res 2010;(8):713-721. 12. Tracy BF, Zhang Y. Soil compaction, corn yield response, and soil nutrient pool dynamics within an integrated crop-livestock system in Illinois. Crop Sci 2008;(48):1211-1218.

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13. Iqbal MA, Iqbal A, Ali K, Khan RD, Ahmad B, Raza A, Nabeel F. Integration of forage sorghum and by-products of sugarcane and sugar beet industries for ruminant nutrition: A Review. Global Vet 2015;(14):752-760. 14. Iqbal MA, Iqbal A, Ayub M, Akhtar J. Comparative study on temporal and spatial complementarity and profitability of forage sorghum-soybean intercropping systems. Cust Agroneg 2016;(12):2-18. 15. Singh V, Singh P. Effect of intercropping of guara and cowpea with forage sorghum on yield and nutrient uptake during summer season. Haryana J Agron 2004;(20):97-98. 16. Yadav NS, Solanki. Effect of intercropping of forage legumes with pearl millet and sorghum in arid region. For Res 2002;28:77-79. 17. Oseni TO, Aliyu IG. Effect of row arrangements on sorghum-cowpea intercrops in the semi-arid savannah of Nigeria. Int J Agric Biol 2010;(12):137-140. 18. Singh A, Singh YV, Asheesh S, Amit V, Mithilesh KS, Surendra S. Genetic analysis of quantitative traits in cowpea [Vigna unguiculata (L.) walp.] using six parameters genetic model. Leg Res 2016;(39):502-509. 19. Keating BA, Carberry PS. Resource capture and use in intercropping: solar radiation. Field Crops Res 1993;(34):273-301. 20. Surve VH, Patil PR, Arvadia MK. Performance of fodder sorghum (Sorghum bicolor L.); maize (Zea mays L.) and cowpea (Vigna unguiculata (L.) Walp.) under sole and intercropping systems. Madras Agric J 2011;(98):372-374. 21. Ahmad AH, Ahmad R, Mahmood N. Production potential and quality of mixed sorghum forage under different intercropping systems and planting patterns. Pak J Agric Sci 2007;(44):87-93. 22. Langat MC, Okiror MA, Ouma JP, Gesimba RM. The effect of intercropping groundnut (Arachis hypogea L.) with sorghum (Sorghum bicolor L.) on yield and cash income. Agric Trop Subtrop 2006;(39):88-96. 23. Zhang FS, Li L. Using competitive and facilitative interactions in intercropping systems enhances crop productivity and nutrient-use efficiency. Plant Soil 2003;(248):305-312. 24. Dapaah HK, Asafu-Agyei JN, Ennin SA, Yamoah C. Yield stability of cassava; maize; soya bean and cowpea intercrops. J Agric Sci 2003;(140):73-82. 25. Ibrahim M, Ayub M, Tanveer A, Yaseen M. Forage quality of maize and legumes as monocultures and mixtures at different seed ratios. J Anim Plant Sci 2012;(22):987-992.

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26. Akhtar MF, Ahmad AUH, Zamir MSI, Khalid F, Mohsin AU, Afzal M. Agroqualitative studies on forage sorghum (Sorghum bicolor L.) sown alone and in mixture with forage legumes. Pak J Sci 2013;(65):179-185. 27. Patel JR, Rajagopal S. Production potential of forage maize (Zea mays) with legumes under intercropping system. Indian J Agron 2001;(46):211-215. 28. Sharma NK, Misra OR, Khushwaha SS, Pachilanya NK. Response of sorghum based intercropping system to chemical fertilizers; FYM and crop residues. Res Crops 2000;(1):289-291. 29. Iqbal MA, Siddiqui MH, Sher A, Zahoor A, Qaiser M, Rana DK. Forage productivity of cowpea [Vigna unguiculata (L.) Walp] cultivars improve by optimization of spatial arrangements. Rev Mex Cienc Pecu 2018;(9):203-219. 30. Hakan G, Avcioglu R, Soya H, Kir B. Intercropping of corn with cowpea and bean: Biomass yield and silage quality. Afr J Biotechnol 2008;(22):4100-4104.

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Table 4: Analysis of variance (ANOVA) for all experimental variables under study of cowpea sown with sorghum under different spatial arrangements during 2013 and 2014 Plant height Stem girth Leaves per Fresh weight Dry weight per Cowpea green forage Leaf-stem ratio (cm) (cm) plant per plant (g) plant (g) yield (t ha-1) SOV 2013

2014

2013

2014

2013

2014

2013

2014

2013

2014

2013

2014

2013

2014

T

213**

288**

73*

85*

109*

100*

74*

89*

287**

234**

166**

183**

244**

280**

A

134**

111**

66*

71*

81*

123*

33*

57*

132**

141**

211**

137**

112*

89*

T×A

189**

203**

88*

98**

93*

112*

83*

96*

274**

297**

187**

257**

266**

287**

SOV

Cowpea DMY (t ha-1)

Sorghum GFY (t ha-1)

2013

2014

2013

2014

2013

2014

2013

2014

2013

2014

2013

2014

2013

2014

T

123**

116**

97

110**

88*

104**

91**

109**

237**

250**

233**

240*

134*

103*

A

91*

75*

132

103*

145*

74*

51*

74*

88*

122**

75*

111*

90*

87*

T×A

134**

120**

114

139*

137*

92*

120***

135**

142*

169**

200**

225*

101*

109*

T×Y=NS

A×Y=NS

Sorghum DMY (t ha-1)

Crude protein (%)

Crude fiber (%)

Ether extractable fat (%)

Total ash (%)

T×A×Y=NS

SOV= source of variance; T= Type of strip intercropping, A= Spatial arrangements, Y=Year. *(P<0.05)

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** (P<0.01).


Rev Mex Cienc Pecu 2021;12(2):402-418

Table 5: Plant height (PH), stem girth (SG), number of leaves (NL), leaf-stem ratio (LSR), fresh weight (FW) and dry weight (DW) per plant of cowpea sown with sorghum under different planting times and spatial arrangements 2013

2014

IS PH (cm)

SG (cm)

NL

LSR

FW (g)

DW (g)

PH (cm)

SG (cm)

NL

LSR

FW (g)

DW (g)

T1A1

94.5±0.27c

2.60±1.16d

22.7±0.55cd

0.50±0.18bc

172.5±0.83cd

50.8±0.21cd

96.2±0.67d

2.63±0.33e

24.3±0.27d

0.52±1.19c

173.0±0.65d

52.6±0.66de

T1A2

90.7±0.64cd

2.64±0.51cd

21.2±0.67d

0.44±0.27d

170.1±0.67d

48.4±0.37d

94.7±0.51de

2.67±0.57d

23.0±0.53de

0.50±0.35cd

173.9±0.25d

50.8±1.15e

T1A3

94.3±0.37c

2.68±0.94c

24.0±0.34c

0.52±0.30b

174.5±0.31c

52.3±0.25c

97.2±0.28d

2.71±1.17c

26.5±0.49cd

0.55±0.82bc

177.0±0.37c

54.1±0.96d

T2A1

102.7±0.29b

2.74±0.56b

28.9±0.67ab

0.53±0.28b

185.1±0.44ab

58.5±0.50a

108.4±0.19b

2.87±0.94b

29.0±0.72b

0.57±0.93b

186.2±0.24b

61.4±0.67b

T2A2

100.0±0.33b

2.70±0.42bc

26.6±0.90b

0.52±0.64b

181.5±0.58b

55.9±0.41b

101.6±0.43c

2.73±0.35c

27.3±0.60c

0.55±0.24bc

184.6±0.51b

58.3±0.29c

T2A3

110.3±0.57a

2.87±0.67a

29.1±0.57a

0.59±0.19a

188.6±0.67a

59.1±0.67a

117.9±0.83a

2.94±0.69a

29.9±0.31a

0.69±0.21a

190.5±0.61a

66.3±1.19a

T3A1

83.5±0.41d

2.35±0.31ef

21.5±0.87d

0.45±0.22cd

169.9±0.29d

44.9±0.59ef

89.9±0.67ef

2.58±0.52g

22.5±0.29e

0.48±0.17d

171.2±0.20de

46.0±0.88fg

T3A2

78.0±0.38e

2.32±0.81f

18.8±0.66e

0.41±0.37e

164.2±0.21e

41.7±0.32f

83.1±0.82f

2.53±0.41h

21.9±0.40f

0.45±0.29e

165.3±0.19f

43.8±0.60g

T3A3

91.1±0.24cd

2.39±0.92e

21.4±0.37d

0.48±0.40c

166.0±0.34de

46.2±0.19e

92.4±0.97e

2.60±0.60g

24.4±0.69d

0.51±0.33cd

170.9±1.11e

48.7±0.37f

LSD0.05

3.80

0.06

2.93

0.04

4.23

3.89

5.29

0.15

0.47

0.03

4.01

3.87

Data presented here is average of 3 replications. IS= Intercropping systems, T1= 8-rows strips (cowpea+sorghum in 4-4 rows), T2= 12-rows strips (cowpea+sorghum in 6-6 rows), T3= 16-rows strips (cowpea+sorghum in 8-8 rows) A1= 30 cm spaced strips, A2= 45 cm spaced strips, A3=60 cm spaced strips. abcdef

Values followed by different letters within columns differ (P<0.05), ± represents standard deviation increase or decrease.

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Figure 1: Correlation analysis for yield attributes with green forage yield and dry matter yield of cowpea (combined analysis of pooled data of 2013 and 2014)

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Table 6: Green forage yield (GFY), dry matter yield (DMY), crude protein (CP), crude fiber (CF), ether extractable fat (EEF) and total ash (TA) of cowpea sown with sorghum under different planting times and spatial arrangements in 2013 and 2014 2013

2014

IS

T1A1

GFY (t ha-1) 18.4±0.18d

DMY (t ha-1) 5.36±0.18e

CP (%) 18.8±0.41bc

CF (%) 26.2±0.72e

EEF (%) 1.79±0.24cd

TA (%) 11.00±0.15d

GFY (t ha-1) 18.8±0.58d

DMY (t ha-1) 5.59±0.16d

CP (%) 18.9±0.33c

CF (%) 26.0±0.98d

EEF (%) 1.82±0.18c

TA (%) 11.33±0.11c

T1A2

17.7±0.53e

5.29±0.37ef

18.6±0.22c

26.9±0.15cd

1.76±0.17d

11.07±0.37d

17.9±0.28e

5.51±0.34d

18.8±0.92c

26.6±0.62c

1.79±0.11cd

11.07±0.24e

T1A3

19.9±0.91c

5.52±0.25d

19.0±0.34b

26.6±0.37d

1.81±0.18c

11.13±0.17c

20.7±0.67cd

5.72±0.84c

19.3±0.53b

25.4±0.37e

1.84±0.23c

11.39±0.15bc

T2A1

21.0±1.23b

5.93±0.53b

19.6±0.55ab

26.1±0.51e

1.86±0.29b

11.29±0.28b

22.2±1.09b

6.09±0.50b

19.4±0.20b

26.0±0.90d

1.90±0.15b

11.45±0.37b

T2A2

20.4±0.44bc

5.78±0.47c

19.0±0.67b

26.7±0.18d

1.84±0.33bc

11.08±0.34d

21.0±0.77c

5.91±0.77b

19.3±.37b

26.7±1.17c

1.87±0.26bc

11.23±0.38d

T2A3

22.2±0.28a

6.63±0.26a

19.9±0.21a

25.9±0.91f

1.91±0.17a

11.78±0.16a

23.7±0.34a

6.94±0.19a

19.6±0.37a

21.5±0.32f

1.95±0.29a

11.78±0.21a

T3A1

17.8±0.37e

5.26±0.38ef

18.2±0.79d

27.6±0.27b

1.73±0.23de

10.93±0.28e

18.5±0.59d

5.29±0.61e

18.5±0.40d

27.3±0.67b

1.75±0.20d

11.05±0.16e

T3A2

16.1±0.41f

5.16±0.82f

18.1±0.62d

27.9±0.67a

1.70±0.29e

10.55±0.27f

16.7±0.44f

5.10±0.94f

18.0±1.11e

27.8±0.85a

1.71±0.10e

10.58±0.44f

T3A3

17.2±0.30ef

5.18±0.21f

18.6±0.63c

27.1±0.41c

1.74±0.37de

11.07±0.18d

17.8±0.69e

5.48±0.26d

18.9±0.91c

27.1±0.71bc

1.79±0.17cd

11.46±0.27b

LSD0.05

1.38

0.19

0.40

0.33

0.05

0.13

1.08

0.21

0.20

0.36

0.04

0.10

Data presented here is average of 3 replications. IS= Intercropping systems: T1= 8-rows strips (cowpea+sorghum in 4-4 rows), T2= 12-rows strips (cowpea+sorghum in 6-6 rows), T3= 16-rows strips (cowpea+sorghum in 8-8 rows) A1= 30 cm spaced strips, A2= 45 cm spaced strips, A3=60 cm spaced strips. abcd Values followed by different letters within columns differ (P<0.05); ± represents standard deviation increase or decrease.

418


https://doi.org/10.22319/rmcp.v12i2.5459 Article

Prevalence of bovine leukosis virus in water buffaloes in West-central Colombia

Juan Carlos Rincón Flórez a,b* Edgar Antonio Peláez Peláez a Nathaly Trejos Marín a Juan Carlos Echeverry López a Juan Carlos González Corrales a

a

Universidad Tecnológica de Pereira. Grupo de Investigación Biomolecular y Pecuaria (BIOPEC), Carrera 27 N 10-02, 660003, Pereira, Colombia. b

Universidad Nacional de Colombia sede Palmira. Carrera 32 N 12 - 00, 763352. Palmira, Colombia.

*Corresponding author: jcrincon@unal.edu.co

Abstract: Bovine viral leukosis (BVL) is a disease with a high morbidity and low mortality. There are reports of natural infection in some bovine species, but it has been little studied in buffaloes. In Colombia, buffalo production is growing rapidly, and, so far, there are no reports of the disease. The objective of this study was to characterize buffalo production in the coffeegrowing region and to determine, by PCR, the prevalence of BVL in buffaloes, as well as its presence in humans, cattle, and sheep near the coffee-growing region. Blood samples from 140 buffaloes and 10 buffalo milk samples were collected, and so were 58 samples from bovines, 35 samples from sheep, and 9 samples from humans that had been in contact with buffaloes. Hematological analyses were performed. Subsequently, DNA was extracted for PCR evaluation. Production information was gathered, and the results were processed and analyzed using the R software. The majority of animals were Mediterranean breed females,

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with a birth weight of 33.39 kg, a weaning weight of 202.93 kg, a calving interval of 491.77 d, a time to peak of 67.26 d, and 381.59 L of milk (adjusted to 305 d at two teats). A prevalence of 33.6 % and of 3.4 %, respectively, was detected in buffaloes and in bovines; no milk, sheep or human samples were positive. No risk factors associated with the infection were found; neither were significant alterations of the blood count or factors of production. These results constitute the first molecular report of the bovine leucosis virus (BLV) in the Americas and one of the first in the world. Key words: BLV, Deltaretrovirus, Bovine Leukemia, Lymphosarcoma, PCR.

Received: 25/07/2019 Accepted: 14/05/2020

Introduction Bovine viral leukosis (BVL) is a malignant systemic viral neoplastic disease with high morbidity and low mortality involving a characteristic accumulation of neoplastic lymphocytes in various organs, which leads to immunosuppression and predisposition to secondary pathologies. This has resulted in economic losses, due not only to the increase in the occurrences of diseases but also to the evident negative effect of the infection on milk production. Leukosis is caused by a type "C" RNA virus of the family Retroviridae, subfamily Orthoretrovirinae, and genus Deltaretrovirus, which causes lymphomas, lymphosarcomas, and leukemia. The virus can be transmitted horizontally or vertically, i.e., between bovines or from mother to fetus(1-3). There are reports of leukosis in several species; however, it has been found to occur naturally only in bovines, buffaloes, and capybaras(4), having been little studied in buffaloes(5). Sheep have been determined to be highly susceptible to inoculation, showing tumors rapidly; other species of goats, deer, rabbits, cats, monkeys, pigs, and chimpanzees have exhibited persistent antibodies after experimental inoculation(4), which seems to suggest that the virus can cross the species barrier. However, further research is still needed, especially since one study has shown a link between the presence of the virus and breast cancer in humans(6). Water buffaloes have been considered to be resistant to various diseases transmitted by such vectors as ticks, hemoparasites, and certain nematodes(7). However, a few reports suggest that the bovine leukosis virus naturally infects buffaloes. In the literature, there are reports of

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experimental infection(1), but very few reports of natural infection, and although some studies show prevalences, these are close to zero and have been detected using tests that may have allowed that percentage of false positives(1). In Pakistan and Cambodia, there are reports of 0 % prevalence of leukosis in buffaloes evaluated by Western blotting. Other studies have suggested the same percentage, based on serological analyses(1,8,9). Recently, a study in southeastern Brazil showed a prevalence of 0 % using agar immunodiffusion (AGID), PCR, and ELISA (ELISA-gp51), which reinforces the idea of a possible absence of natural infection in water buffaloes. In the same study, performed with a commercial ELISA kit (ELISA-BLV) on the same samples, 24.4 % of the animals were seropositive; this points to the diagnostic problems associated with this ELISA test, which has a high false positive rate(1,5). As a result of these studies, PCR has been proposed as a reference test, despite the fact that AGID is considered to be the Gold Standard test(5). In a study conducted in the Philippines, a prevalence of 27 % was detected by PCR; however, in a group of unknown origin, the prevalence rate was found to be 0 %(7). This again opens the question of natural infection of buffaloes, especially in the case of production animals, because although there are multiple case reports of lymphosarcoma in buffaloes in the world(10,11), many of these cases have been reported as negative for bovine leukosis virus(5,11), a fact that raises more questions about this disease in buffaloes. Thus, it is necessary to adequately clarify whether natural infection exists in buffaloes, particularly if it is present in the Americas, and specifically in Colombia, where there are no reports of the disease in buffaloes(12). It is estimated that there are 3'800,000 buffaloes on the American continent; the American countries with the largest buffalo populations are Brazil with 3'500,000, Venezuela with 350,000 and Colombia with 308,580(13-15). In Colombia, this is one of the livestock populations that have grown the most in recent years, given the buffaloes' ability to adapt and maintain their performance in difficult conditions where cattle cannot(14,15). For this reason, buffalo breeding is becoming an increasingly important economic activity, and the study of the diseases that these animals may suffer is an important factor of production. Thus, the objective of this work was to characterize buffalo production in the coffee-growing region, to determine the prevalence of bovine leukosis virus by PCR in buffaloes, and to detect the presence of the virus in humans, cattle and sheep that are in contact or close to the buffaloes.

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Materials and methods Sample size

According to the 2017 national livestock census of the Colombian Agricultural Institute (ICA), the coffee-producing axis includes 34 farms with approximately 3,105 animals(15). Based on this information, the sample size was estimated at 94 animals, taking into account a heterogeneity of 50 %, a margin of error of 10 % and a confidence level of 95%. However, it was possible to perform the evaluation on a larger number of animals; therefore, 140 blood samples were obtained from buffaloes of different breeds including the Murrah, Mediterranean and Bufalypso, most of the animals being in the productive stage. The buffaloes were sampled in eight herds of the coffee-producing axis during the years 20162017. Samples were also taken from 58 cattle, 35 African sheep, and 9 humans that were in the same production system or very close to it. In the case of the humans, they were people involved in the handling of the animals. These species were considered because they have been reported to be susceptible to natural BTV infection (4-6).

Data collection

In the sampled herds, information was collected on those production and risk factors that may be associated with the presence of leukosis. However, productive information was available only for three herds because there were few or no records for the others. The production information collected included birth weight, weaning weight, weaning weight gain, calving interval, milk production at two teats adjusted to 305 d (considering that two teats are left for the calf), production at peak and days to the peak; while the risk factors considered were breed, herd and age group divided into buffaloes at productive age (3 yr or older) and buffaloes at non-productive age (less than 3 yr old)(16). The farms where the buffalo samples were taken were located in the central-western region known as the coffee-growing region, mainly comprising the departments of Caldas, Quindío and Risaralda. The farms were located at an average altitude between 917 and 1,575 m asl and an average temperature between 18 and 30 °C. The municipality with the highest number of animals sampled was Marsella, with 44, followed by Chinchiná and Calarcá, with 32 each; Pueblo Rico, with 29; Cerritos, with 18; Pereira, with 8, and Cartago, with 4. The exact origin of 47 of the samples was not determined because they were collected at a slaughterhouse.

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The municipality of Cartago was included because, although it is located in the north of the department of Valle, it is considered part of the coffee-growing region.

Sampling and hematological analysis

The project was endorsed by the bioethics committee of the Technological University of Pereira (Universidad Tecnológica de Pereira) in Act 17 of 2015 (code CBE-SYR-172015). Blood samples were taken with BD vacutainer tubes with EDTA as anticoagulant and No. 18 needles, after disinfecting the area with antiseptic alcohol. The buffalo and sheep were sampled from the jugular vein, and the cattle, from the coccygeal vein. In the case of humans, a bacteriologist collected samples after the participants signed an informed consent form. In addition to the blood samples, 10 samples of milk from commercially sold buffaloes were collected. The milk and blood samples were transported in portable coolers at approximately 4 °C to the multiple laboratory of Animal Sciences of the Universidad Tecnológica de Pereira, where the hematological analysis was performed using a URIT 2900Vet plus automated analyzer (URIT®, Guilin, China) in the option for buffaloes, and the following variables were assessed: white blood cell (WBC), red blood cell (RBC), hemoglobin (HGB), hematocrit (HCT), and platelet (PLT) counts. The remaining blood was used for DNA extraction.

DNA extraction from blood and milk

The blood DNA was extracted with the GE® Illustra Blood GenomicPrep Mini Spin Kit (GE Healthcare Bio-Sciences, Pittsburgh, PA, USA) according to the manufacturer's recommendations. Once the samples were obtained, their purity was evaluated by absorbance ratio analysis using two wavelengths (260/280 nm), with the NanoDrop 2000c (Thermo scientific®, Wilmington, USA). Only DNA samples with an absorbance ratio of 1.8 to 2 and an absorbance concentration above 1.8 were considered 10 ng/mL. The samples were stored in Eppendorf tubes at -20 °C until PCR analysis. The DNA from milk somatic cells was extracted with the modified salting out method, taking into account two different approaches considering the amount of fat present in buffalo milk. In the first protocol, 14 mL samples of raw milk were collected in Falcon tubes; they were allowed to stand in the refrigerator at 4 ºC for 1 h and centrifuged at 3,500 rpm for 8 min; then, the fat layer was broken and removed using a Pasteur pipette, and the supernatant was discarded without disturbing the cell button. Subsequently, 5 mL of saline solution were

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added and shaken vigorously until the cell button was dissolved. The solution was centrifuged again (2 to 3 times more until the colorless supernatant could be observed) at 3,500 rpm during 8 min, and the supernatant was discarded without disturbing the cell button. Subsequently, 5 mL of lysis solution (10 mM Tris HCl pH 8.2, 400 mM NaCl, 2 mM Na2EDTA), 26.5 µL of proteinase K enzyme (2 mg/mL), and 300 µL of SDS solution were added and resuspended by gentle vortexing for 1 min, and the solution was added to the sample. This was then incubated in a water bath at 55 ºC for 6 h, after which it was refrigerated at 4 ºC for 5 min and allowed to cool, and 1.5 ml of saturated saline solution (6 M) was added. After this, the sample and the solution were mixed in a vortex and centrifuged for 10 min at 3,500 rpm. The supernatant was taken to a 15 mL tube to add 100% ethanol at -20 °C until reaching 14 mL, after which the tube was gently shaken by inversion in order to observe the DNA skein. The sample was washed with 1 mL of 70% ethanol and then centrifuged at 4,000 rpm; the supernatant was discarded and the tube was inverted, allowing the contents to dry. Finally, the button was resuspended in 300 µL of 1X TE buffer pH 8.0 (1 M Tris HCl and 0.5 M EDTA) and stored at 4 °C until analysis. Protocol 2 was the same as protocol 1, except that in this case the cream layer was not broken, nor was the saline solution added; only the centrifugation of the raw milk was followed directly by the addition of the lysis buffer. For both protocols, DNA quantification was performed using a 2000c NanoDrop (Thermo scientific®, Wilmington, USA) using 2 µl of the sample from each extraction protocol. The 260/280 and 260/230 ratios were also taken into account as indicators of DNA purity. The data were stored for further statistical analysis.

Evaluation by PCR

A highly conserved region of the proviral env gene was evaluated using the nested PCR technique. We used DNA samples from leukosis positive and negative bovines, which were provided by the Biodiversity and Molecular Genetics Group (BIOGEM) of the National University of Colombia in Medellín, Colombia. The controls provided were obtained from animals that had been previously confirmed by PCR and direct ELISA for the env gene of the provirus. The first PCR was performed on a final volume of 25 µL containing approximately 150 ng of DNA, with a final concentration of 0. 4 µM of each BLV forward (5′-ATGCCCAAAGAACGACGGACGG-3′) and BLV reverse (5′CGACGGGACTAGGTCTGACCC-3′) oligonucleotide, 200 µM of each dNTP, 2.5µl of 10X Top Taq PCR buffer containing 15mM MgCl2, and 1U of Top Taq DNA polymerase (Qiagen®, Germantown, Germany). In the second PCR reaction, 5µl of the PCR product of the first amplification were used as template DNA, with the same conditions as the previous one, but with the Env5032 forward (5′-TCTGTGCCAAGTCTCCCAGATA-3′) and Env5608 Reverse (5′-AACAACAACCTCTGGGAAGGGT-3′) oligonucleotides. The

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primers had been reported previously(17), but standardization was carried out on a Labnet TC9610 MultiGene OptiMax Thermal Cycler TC9610 Thermal Cycler (Labnet®, Northlake, IL, USA). The PCR profile included an initial denaturation step at 95 °C for 5 min, followed by 25 cycles of 95 °C for 30 sec, 60 °C for 30 sec and 72 °C for 1 min, followed by a final extension at 72 °C for 8 min. For the second PCR, a denaturation step was performed at 95 °C for 5 min, followed by 35 cycles of 95 °C for 30 sec, 60 °C for 30 sec and 72 °C for 45 sec, and finally an extension at 72 °C for 10 min(18). The products of the second PCR were observed using agarose gel electrophoresis at 2.5% (Amresco, Cochran Road, OH). 5 μL of PCR product mixed in 2 μL of EZ vision stain were poured in (AMRESCO, Sidney, Aus). In each run line, 2 μL of 100 bp molecular weight marker (low range Fermentas, Glen Burnie, MD) were used, along with two 2 μL of EZvision. The gels were documented using an ENDUROTM GDS photodocumenter (Labnet, NJ, USA) for photographic evidence. A 598-bp band indicated the presence of provirus in one individual. In all cases, a negative and a positive bovine control were used in the PCR, and so were positive and negative buffalo controls found in this work.

Statistical analyses

Based on the information collected in the herds, descriptive statistics were performed in order to summarize the production and risk factors in the sampled herds. A descriptive analysis of the hematological, DNA quantification, and purity data for milk samples was also performed, and the protocols were compared using a t-student test for DNA concentration, and the 260/280 and 260/230 ratios of the milk samples. Finally, prevalence and their respective 95% confidence intervals were estimated for each of the species sampled. Using the data collected for the buffaloes, a generalized linear model (GLM) was developed to evaluate the effect of infection on the productive characteristics and on the hematological variables white blood cells, red blood cells, hemoglobin, hematocrit and platelets. Subsequently, a logistic regression model was performed to determine whether any risk factors were statistically significant for the presence of the virus in individuals.

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Results Description of herds and productive characteristics

In this study, most of the buffaloes sampled in this study came from the departments of Risaralda (46 %), Quindío (17 %), Caldas (15 %), and others (22 %). Most of the buffaloes were of the Mediterranean breed (29 %), followed by Murrah (19 %), Bufalypso (13 %), and indeterminate crosses (39 %). Taking into account young animals of non-productive age (under three years old) and adult animals of productive age (over three years old), 21.6 % of young animals and 78.4 % of adults were sampled according to their age group. As for the productive parameters, it was found an average birth weight of 33.39 kg, a weaning weight of 202.93 kg, a weaning weight gain of 136.27 kg, a calving interval of 491.77 d, 381.59 L of milk adjusted to 305 d, and 67.29 d to peak of (Table 1). Table 1: Productive characterization of water buffaloes in the central-western region of Colombia Characteristic Mean Standard error Standard deviation Birth weight, kg Weaning weight, kg Kg since weaning, kg Interval between births Milk 305 days, L Days at peak Production at peak

33.89 202.93 136.27 491.77 381.59 76.26 2.15

0.17 2.22 3.75 5.20 28.79 6.30 0.12

4.31 53.43 96.33 63.87 345.49 62.38 3.07

Hematological description

Regarding the hematological evaluation of the samples, it was found that the white blood cells count (WBC x 103 µL) was higher in positive animals, but did not differ statistically from uninfected ones; as for red blood cells (RBC x 103 µL), these were significantly higher in the positive animals, while hemoglobin (HGB%) and hematocrit (HCT%) were similar in positive and negative ones. Platelets (PLT x 103 µL) were lower in positive samples, but not significantly so (Table 2).

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Table 2: Description of hematological variables in water buffaloes positive and negative for bovine enzootic leukosis Characteristic Statistic 3

WBCx10 µL

RBCx103µL*

HGB%

HCT%

PLTx103µL

Mean±SE Standard deviation Min Max Mean±SE Standard deviation Min Max Mean±SE Standard deviation Min Max Mean±SE Standard deviation Min Max Mean±SE Standard deviation Min Max

Total

Negative (n=93) Positive (n=47)

32.94±1.85 39.84 126 125 46.93±3.11 26.84 80 79 27.74±1.59 22.26 68 67 43.94±2.32 32.71 97 96 38.78±2.47 32.3 99 98

30.12±3.16 20.72 78 77 66.67±6.06 39.75 125 124 20.09±2.47 16.2 66 65 46.07±4.39 28.81 87 86 45.91±4.89 32.09 98 97

33.45±2.80 13.14 9 55 85.64±4.13 19.37 45 117 21.82±3.96 18.56 68 65 46.77±3.57 16.76 17 74 46.32±6.33 29.69 5 98

WBC= white blood cells; RBC= red blood cells; HGB= hemoglobin; HTC= hematocrit; PLT= platelets. = *Statistically significant difference (P<0.05) between negative and positive.

DNA extraction

It was possible to establish a method for DNA extraction from buffalo milk, enabling the obtainment of average amounts above 50 ng/µL, which is the recommended level. Given that the buffalo milk samples have a high concentration of fat; a method was proposed with the extraction of this fat. However, protocol 2 without fat removal showed the best results, with an average concentration of 165.7 ng/µL vs 20.5 ng/µL in protocol 1 (P<0.05). The 260/280 ratio of the protocol was 1.74. For DNA extraction from blood using a kit, concentrations above 10 ng/ml were obtained with a 260/280 ratio of 1.8 to 2.

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BTV DNA detection

Successful detection of BTV DNA was possible using the leukosis PCR test (Figure 1), and 33.6 % of the 140 tested buffalo samples and 3.4 % of the 58 bovine samples were found to be positive. None of the buffalo milk samples yielded positive results (Table 3); neither the samples from sheep nor those from humans in contact with buffaloes were positive. In all cases, the tests were validated with the respective positive and negative controls mentioned above.

Figure 1: Agarose gel electrophoresis for a fragment of the Env gene of bovine enzootic leukosis provirus in buffalo whole blood samples

Lane 1= negative control, lane 2= positive control, lane 3= a positive sample, lanes 4-6 negative samples.

Table 3: Leukosis positivity in buffaloes and other production animals in the centralwestern region of Colombia Total No./ Species Prevalence (%) Confidence interval 95% Positive Buffaloes - Blood 140/47 33.6 26 - 42.1 Buffaloes - Milk 12/0 0.0 0.0 - 60.4 Bovines 58/2 3.4 0.5 - 12.9 Humans 9/0 0.0 0.0 - 37.1 Sheep 35/0 0.0 0.0 - 12.3

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Risk factors

The effects of factors such as municipality, herd, age, and breed on the presence of the virus were evaluated by logistic regression, but no significant effect was found in any of the cases (P>0.05), so there is no evidence to assume that these are risk factors for leukosis infection in buffaloes. Finally, no relationship was found between BLV positivity and milk production or other productive parameters. Nevertheless, it is important to clarify that the information was not collected homogeneously and completely, since there were not enough records in the buffalo-milk production units.

Discussion Given the characteristics of water buffaloes for adapting to different climates including tropical conditions, the climate between 18 and 30 °C in which the study animals were found in the central western region, is suitable for dairy, meat or dual purpose production(19). In this study, the Mediterranean breed was the most frequent, as in Argentina(20) and Brazil, although the most common dairy breed there is the Murrah(21,22), and in Costa Rica, the Bufalypso(23). With respect to sex, a larger number of females was found, given the dairy focus of the predominant breed, consistently with a previous study conducted in the coffee-growing region of Colombia(24) and in Venezuela(25). Birth weights were similar to those found in other regions of Colombia with weights between 35 to 40 kg and 30 to 37 kg(12,26). The weaning weight of 202.93 kg was also similar to the weaning weight found in Costa Rica, of 160 to 220 kg(23), and within the range reported in Colombia (204.17 to 356.45 kg) in Murrah females. The calving interval of 491.77 d was higher than that found in Córdoba (Colombia), which was 414 d(27). Lactation at 305 d of 381.59 L from two teats was lower than that reported in the same area, which was 1,098 L, but from all four quarters(24). It is important to point out that, in the area, it is common practice to milk two teats and leave the other two for the calf, which is why yields tend to be lower than those reported in other studies. Similarly, the production at peak was 2.15 L, which is lower than the 5.0 L reported for the zone, but from the four quarts. It is important to note that most of the production data in this study were obtained from a single herd. With respect to the extraction of DNA from buffalo milk, in protocol 2 the best method was found to be not to extract the fat layer, since it allowed obtaining higher DNA concentrations with an average of 165.78 ng/µL with a 260/280 ratio of 1.74 that allows it to be classified as DNA of acceptable purity. In addition, a 260/230 ratio of 0.41 was found, which suggests

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that this method leaves some degree of contamination with phenols. The above results coincide with those found in a study that used six extraction methods in sheep milk(28), which included different extraction kits, phenol-chloroform, and lysis with guanidine hydrochlorate; the 260/280 ratio ranged between 1.55 and 1.80, and the 260/230 ratio ranged between 1.43 and 1.80 and had the highest contamination with the lysis solution. The amount of DNA obtained is within the range obtained from goat milk using the salting out method, which was 2.12 ng/µL to 610.12 ng/µL, although in that study the initial fat layer after centrifugation was discarded(28). Finally, the samples were taken and analyzed by PCR to evaluate the possible presence of BLV; upon analysis of these was obtained, with the respective validation of the positive and negative control mentioned previously. This is important, as certain authors suggest a relationship with breast cancer in humans(6). The diagnosis of leukosis prior to the use of serological and molecular tests was based on hematological findings, which were supported by the presence of persistent lymphocytosis, in the preclinical phase and in the leukocytic or tumor phase, in up to 30 % of the positive animals(29). In this work, although without statistically significant difference, an increase in white blood cells was found in positive animals compared to negative ones, but without discriminating cell lines, so that no specific alterations in lymphocytes can be evidenced. A similar result was found in Brazil in Holstein cows where the white line was 10.3 x 103 µL in negative and 27.96 µL in positive(30). Regarding hemoglobin, it has been reported to be low in positive animals; however, in the present study, there were no differences in this aspect between positive and negative animals. Yet, there were differences in red blood cells, which were significantly higher in positive animals, possibly due to problems of poor regulation in the differentiation and maturation of blood cells after infection with the virus. With respect to the cattle sampled in this study, no statistically significant differences were found in any of the hematological parameters evaluated, although it should be noted that the number of animals was too small to have sufficient statistical power. Although the buffalo is considered one of the species susceptible to infection by the bovine leukosis virus, there is little concrete evidence of this, since few reports prove the presence of the virus naturally, and those that do base their diagnosis on such tests as ELISA, AGID and Western blot, which detect antibodies, but not proviral DNA. Furthermore, according to some literature reports(1,5), these tests have a significant percentage of false positives, which, in view of the low prevalence rates, might cast a doubt regarding the true presence of the virus. On the other hand, buffalo have been considered as susceptible in some studies in which the animal is inoculated with the virus in order to monitor its infection and its pathophysiological development. Some reports of bovine lymphosarcoma in buffaloes have tried to associate the presence of this type of lesion with the presence of bovine leukosis virus. Even in one case report they describe the clinical, hematological, and cellular findings attributing the etiology to BLV, but 430


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without laboratory confirmation(10). Another case of lymphosarcoma was reported in Brazil in a female buffalo that tested negative when diagnosed with a nested PCR test(11). In 2016, a study was conducted in buffaloes from the Amazon and southeastern Brazil, searching for the presence of the virus by agar immunodiffusion (AGID), ELISA and PCR. In this study, 24.6 % of animals were found positive by ELISA, but none positive by AGID which is the test considered as the Gold standard. No positive results were obtained by PCR, so it was concluded that there was no presence of the virus in the animals evaluated; however, in 2000, in the same Amazon region, the presence of antibodies to BTV was found in buffaloes. The tests performed were AGID and two types of ELISA for gp51 antigen and immunoglobulin G detection. The conclusion of this study was the natural presence of the virus in buffaloes(31) with 87, 81 and 69 positive serum samples for each test, respectively. All of the above suggests non-specific test results and evidences the few findings of natural infection. One of the few cases reported by PCR is in the Philippines, where a positivity of 27.6 % for BTV was found, which is the only confirmatory report of the virus in buffaloes found in the literature by this method(7). As in the Philippine study, this work demonstrated the natural occurrence of BTV in water buffaloes in the coffee-producing axis region of Colombia, detected by PCR, being the first report in the Americas, and one of the first worldwide, to use this technique. In the Philippine study, the virus was identified in a total of 272 samples of the Murrah breed (70 positive), Philippine Carabao (5 positive), and undetermined breed (0 positive). In the present study, there were no significant differences between breeds. In bovines, a positivity of 3.4 % was found; this value is lower than those found in the literature, and even lower than that found in buffaloes in this study, which was 33.6 %. The analysis of bovine samples was also performed with nested PCR. This may explain the difference in regard to studies carried out in Montería, with prevalences of 24 %, and in Mesa de Los Santos, Colombia, with 73 %, as well as in several regions of Chile with 34.7 % where the diagnosis was made with ELISA, with the possible false positives discussed above(32–34). In spite of the results found, the transmission of BTV virus between species cannot be ruled out, although it is yet to be confirmed whether the viruses that produce the disease in susceptible species are genetically the same. The risk factors associated with the presence of the disease may be similar in bovines and buffaloes. These factors are the reuse of needles in tasks such as vaccination, reuse of palpation sleeves in reproductive check-ups, dehorning with saws, and lack of fly control. In the present work, these data were not available; therefore, other factors such as herd, buffalo age, and breed were taken into account. None of these factors was correlated with the presence of BTV. In Montería (Colombia), positive associations have been found in cattle

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with respect to the presence of BTV and age, breed and type of production, being higher in females, dual purpose cattle, and crossbreeds of Zebu and European(32). On the other hand, following the identification of the presence of the virus in humans and its possible association with mammary cancer, it has been suggested that the route of infection is the consumption of raw milk and meat from infected cattle. In this study, 12 samples of buffalo milk purchased in local commerce were analyzed by PCR, of which none tested positive for the presence of the virus. Some studies carried out in Colombia and in Argentina(35,36) have demonstrated the presence of the leukosis virus in fresh bovine milk with 49 and 59 % positivity respectively; however, there are no reports of similar findings in buffaloes. Regarding the results of positivity in sheep, these have been considered to be a species susceptible to BTV infection. Although few reports exist, a seropositivity of 0.077 % (2 out of 2,592) was obtained in Brazil. The positive animals were a female of the Santa Inés breed and another female of unknown breed(37). In another case, a sheep with lymphoma was tested with AGID, with negative results(38). In another study conducted in Iran in 2015, 7.04 % of 95 sheep evaluated by nested PCR tested positive. In this study, samples from 35 African sheep (Camuro) were tested by nested PCR, and none of them proved positive. In this study, nine blood samples were also collected from personnel who are or have been in contact with cattle and buffalo during their professional practice. None of the samples were positive. Although, as mentioned, it seems that the virus is transmitted to humans through contaminated food, it cannot be ruled out that, as in bovines, the virus is transmitted by needle puncture or in some other way, as in the case of another retrovirus, the HIV virus. In 2003, Buehring and collaborators detected the presence of antibodies to BTV by immunoblot in humans, obtaining positive results in 39 % of 257 volunteers. It should be noted that the volunteers were not agricultural workers(39).

Conclusions and implications The presence of BTV was found in 33.6 % of the buffaloes in the central-western region of Colombia, a value much higher than that found in bovines in the same area (3.4 %). No presence of provirus was found in commercial buffalo milk samples, nor were there hematological or productive alterations in the positive animals. Since this is the first report in Colombia of the presence of BTV in buffaloes, no BTV control programs have been established for this species. When positive cases are found, the programs could be similar to those used in bovines, which are focused on the identification of positive animals, use of

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needle per animal, change of palpation sleeves, disinfection of the tattoo machine, and chemical dehorning. These systems have avoided the selective slaughter of positive animals(40). In addition, disease control reduces economic losses due to lower production and veterinary care, and is fundamental in a potential future export of buffalo meat and dairy products.

Acknowledgments

The authors thank the Vice Rector's Office for Research, Innovation and Extension for the financial and logistical support for this work. The authors declare that they have no conflict of interest. Literature cited: 1. Feliziani F, Martucciello A, Iscaro C, Vecchio D, Petrini S, Grassi C, et al. Bovine leukemia virus: Experimental infection in buffaloes and evaluation of diagnostic test reliability. Res Vet Sci 2017;(114):450–454. 2. Ooshiro M, Konnai S, Katagiri Y, Afuso M, Arakaki N, Tsuha O, et al. Short communication: Horizontal transmission of bovine leukemia virus from lymphocytotic cattle, and beneficial effects of insect vector control. Vet Rec 2013;(173):527. 3. Bartlett PC, Norby B, Byrem TM, Parmelee A, Ledergerber JT, Erskine RJ. Bovine leukemia virus and cow longevity in Michigan dairy herds. J Dairy Sci 2013;96(3):1591–7. https://linkinghub.elsevier.com/retrieve/pii/S0022030213000428. 4. Organización Mundial de Sanidad Animal. Leucosis bovina enzoótica. En: Manual de las pruebas de diagnóstico y de las vacunas para los animales terrestres. 8th ed. Paris, Francia: OIE; 2018:1–12. 5. De Oliveira CHS, Resende CF, Oliveira CMC, Barbosa JD, Fonseca AA, Leite RC, et al. Absence of Bovine leukemia virus (BLV) infection in buffaloes from Amazon and southeast region in Brazil. Prev Vet Med 2016;129:9–12. http://dx.doi.org/10.1016/j.prevetmed.2016.05.002. 6. Buehring GC, Shen HM, Schwartz DA, Lawson JS. Bovine leukemia virus linked to breast cancer in Australian women and identified before breast cancer development. PLoS One 2017;12(6):e0179367.

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20. Crudeli GA, Patiño EM, Maldonado VP, Konrad JL. Pasado, presente y futuro del búfalo en Argentina. Rev Vet 2014;25(2):140–145. 21. Mendes MCH, Mendes MAC, Ramos AA, Carneiro SPL, De Souza JC, Pala A. Genetic parameters for milk yield, lactation length and calving intervals of Murrah buffaloes from Brazil. R Bras Zootec 2013;42(8):565–569. 22. Rosa BRT, Ferreira MMG, Avante ML, Filho DZ, Martins IS. Introdução de búfalos no brasil e sua aptidão leiteira. Rev Cient Eletrônica Med Vet 2007;(8):1–6. http://faef.revista.inf.br/imagens_arquivos/arquivos_destaque/vDXNCfZHc6Lxtn8_20 13-5-21-17-2-38.pdf. 23. Rosales R. Situación del búfalo de agua en Costa Rica. TM 2011;24(5):19–24. https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/162. 24. Henao SS, López JC. Caracterización productiva y su relación con el color del pelaje en búfalos de agua de diferentes hatos lecheros del Eje cafetero [tesis pregrado]. Pereira, Risaralda: Universidad Tecnológica de Pereira; 2017. 25. Menéndez-Buxadera A, Verde O. Componentes de (Co)varianza de la producción de leche de un rebaño bufalino venezolano estimados con modelos de lactancia completa o del día de control. Zootec Trop 2014;32(1):63–75. 26. Dumar JK, Romero JD, Velásquez JC. Evaluación de parámetros productivos y reproductivos en la bufalera El Marañón en la Dorada en el departamento de Caldas [tesis de pregrado]. Bogotá, Colombia: Universidad de la Salle; 2014. 27. Bedoya C, Mira T, Guarín J, Berdugo J. Reproductive parameters of water buffalo (Bubalus bubalis) in the south of Cordoba, north coast of Colombia. Proc VI World Buffalo Congres. Maracaibo. 2001:271–275. 28. D’Angelo F, Santillo A, Sevi A, Albenzio M. Technical note: A simple salting-out method for DNA extraction from milk somatic cells: investigation into the goat CSN1S1 gene. J Dairy Sci 2007;90(7):3550–3552. 29. Romero H, Miranda A, Gauna C, Trincheri M, Minatel L, Giménez H. Caso reportado de síndrome vestibular o parálisis facial en la provincia de La Pampa, Argentina. Vet Arg 2014;31(318):1-12. 30. Rezende ST, Godoi BH, Batista C, Souza F, Azedo M, Blagitz M, et al. Correlação entre a atipia linfocitária e o perfil imunológico de vacas leiteiras infectadas pelo vírus da leucemia bovina. Semin Cienc Agrar 2013;34(1):293-300. 31. Molnár E, Molnár L, Guedes VT, de Lima ES. Naturally occurring bovine leukosis virus in water buffalo (Bubalus bubalis) in Brazil. Vet Rec 2000;146(24):705–706. 435


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https://doi.org/10.22319/rmcp.v12i2.6050 Article

Effect of model and construction material of the brood box and brood comb coating on the thermoregulation and development of Scaptotrigona mexicana colonies

Juan Antonio Pérez-Sato a Hugo Rodolfo Salazar-Vargas a Juan Valente Hidalgo-Contreras a* Natalia Real-Luna a Héctor Debernardi-De La Vequia a Roberto De La Rosa-Santamaría a

a

Colegio de Postgraduados, Campus Córdoba, Km. 348 Carretera Federal CórdobaVeracruz, Congregación Manuel León, 94946, Amatlán de los Reyes, Veracruz, México.

*Corresponding author: jvhidalgo@colpos.mx

Abstract: In meliponiculture, the artificial division of S. mexicana bee colonies is one of the activities where the greatest loss of colonies is reported. One of the various causes of this mortality is the difficulty of the new colony to maintain the thermoregulation of its nest, given the traditional use of clay pots for this purpose, which render it difficult to maintain a stable temperature. The objective of this study was to analyze the interactions between the model of the box, its construction material and the brood-comb coating on the inner temperature of the nest and the development of colonies obtained by artificial division. The development of the nests was quantified based on their final and initial weight gain, the number of cells built, colony activity, and the capacity of the design to maintain the inner temperature of the nest. The results show that the best internal temperature ranges were achieved in nests transferred to Portugal-Araujo (P<0.05) and Ailton-Fontana (P<0.05) model rational boxes whose

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original designs were modified to include expandable polystyrene sheets. In addition, colony temperature and development were favored when the newly transferred combs were lined with Apis mellifera L. beeswax using a mold. The positive interaction between these factors provided an optimal temperature range (27.9 to 31.0 °C) for the development of the colonies, which obtained weight gains between 0.149 and 0.289 kg, and the number of brood cells constructed ranged between 3,511 and 4,956. Key words: Thermoregulation, Cavity, Stingless bee, Artificial partitioning, Insulating material, Involvement substitute.

Received: 10/09/2018 Accepted: 17/02/2020

Introduction The artificial division of colonies is a method used in meliponiculture and consists in obtaining several daughter colonies over the years(1) from a mother colony of bees(2). After the division, the survival of the daughter colony becomes critical if it is not provided with adequate conditions(3,4) because parts of the nest are destroyed(5), and the brood of the new colonies are exposed to external temperature fluctuations and do not regain stability until the nest structures are rebuilt(6-9). The optimum nest temperature is between 31 and 35 °C(10,11); in order to attain this temperature, the workers line the brood area with small sheets of cerumen known as involucrum(12,13), and subsequently the storage area, and they coat the peripheral walls with batumen (a mixture of cerumen produced by the bees and tree resin). Inadequate nest thermoregulation can have serious consequences for the colony(14), ranging from slow growth to death(15,16,17). Under conditions of poor nest thermoregulation, the bees invest most of their energies in building insulation structures, and less effort in collecting nectar and pollen that are essential for colony development and survival(12,18). Another key factor contributing to nest thermoregulation is the type of cavities in which S. mexicana nests are housed(12); those commonly used in the traditional way are natural cavities such as logs and earthenware pots. The logs have thick walls (>10 cm) that allow them to adequately conserve the inner temperature of the nest(19). However, in the rational boxes, there is a greater fluctuation in the inner temperature of the nest because they have a greater volume, height, and lower wall thickness than natural cavities(20).

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Due to the importance of thermoregulation in the development of a colony, it is necessary to build rational boxes that will favor the maintenance of optimal temperature ranges for the development of the brood(21). The cavities commonly used for rearing S. mexicana are wooden boxes and earthenware(17,22). However, these materials do not have the best thermal insulating properties to help the nest maintain its optimum temperature, especially when the colonies are small. Currently, rational wooden boxes have been designed to facilitate colony management and provide better thermoregulation of the nest(6,23,24). The most commonly used model for S. mexicana is the Portugal-Araujo(23), whereas the Ailton-Fontana model is used for Tetragonisca angustula and Nannotrigona testaceicornis(24). The latter box model can be modified to accommodate S. mexicana successfully. Both models can be greatly improved to provide greater thermoregulation to the stingless bee nest if an insulating material such as polyurethane(6) or expandable polystyrene foam is included in their design and construction. During the artificial division of stingless bee colonies, nest structures essential to provide adequate nest thermoregulation are destroyed during this activity. This renders the new daughter colonies vulnerable to sudden changes in ambient temperatures. A proposal to counteract this situation would be to design and build rational boxes with materials with thermal insulating properties and to line the rearing area with a material that will fulfill the functions of the enclosure. The objective of this research was to analyze, in small colonies obtained by artificial division, the effect on inner nest temperature and colony development of S. mexicana; covering their brood combs with a material that replaces the involucrum, and housing them in rational box models built with conventional materials and materials with thermal insulating properties.

Material and methods The study was carried out in the Meliponarium located in the Permaculture area of the College of Postgraduates (Colegio de Postgraduados), Campus Córdoba, Amatlán de los Reyes, Veracruz, Mexico, located between the parallels 18° 46' and 18° 58' N; meridians 96° 49' and 96° 58' W, at an altitude of 600 m asl. The climate is warm humid (88 %) and semiwarm humid (12 %), with abundant rains in the summer, a temperature range between 20 to 24 °C, and a rainfall of 1,900 to 2,600 mm(25). The study period was from June to August 2016, once the experimental material was available and the experimental area was built, and seeking to avoid the rainy season, which in the case of Amatlán de los Reyes is from June to September. The experiment was planned for brief dry period that took place during this season and performed out under a canopy, in order to prevent fly infestation by

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Pseudohyphocera spp. Another aspect to be considered for the study period was the availability of food to carry out the division; therefore, it had to be performed during the flowering period within the Permaculture area, where bees have access to flora that provided food (nectar and polen) during the months in which the division was carried out(3). Thirty six (36) daughter colonies of S. mexicana were used in this experiment; they were obtained as follows: based on 107 colonies from two meliponariums of the College of Postgraduates (Colegio de Postgraduados), 36 mother colonies were established with an average weight of 5 kg per colony (range=4.52 to 5.86 kg). These were initially housed in earthenware pots, in order to facilitate handling. Only the brood and involucrum combs with an average weight of 265 g (range=118 to 384 g) were transferred to the Ailton Fontana rational box constructed of wood and polystyrene. The newly transferred colonies were fed Apis mellifera honey for 19 d, until the colonies were organized. After 84 d, the mother colonies were artificially divided(26) in order to obtain 36 daughter colonies, providing the same post-transfer management, and 35 d after the division they all had a fertilized queen. Before placing the combs in the box, they were weighed on a digital scale (OHAUS®), and the initial weight of the combs in each daughter colony at the time of artificial division was recorded. This was within the range of 0.077 to 0.335 kg(27). The new colonies were each composed of combs of young brood and cocoon brood, worker bees and a fertilized queen. The experimental design was carried out under a randomized complete block design (RCBD) with a full factorial arrangement in the treatments (Table 1) and initial colony weight as a covariate. The factorial arrangement consisted of three factors (2x2x3), the first of which was the Ailton-Fontana model (AFM) and the Portugal-Araujo model (PAM). The second factor was the material used in the construction of the rational cavities: boxes made of wood (BMW) and boxes made of wood on the outside, with a layer of expanded polystyrene in the middle and another layer of wood on the inside, joined together to form a sandwich (BMW+PS). The third factor was the type of material used to coat the newly transferred brood combs to the boxes, with three levels: uncoated transferred brood combs (UTBC) (control), transferred brood combs coated with Apis mellifera beeswax (TBCCAMBW) and expandable polystyrene foam-coated transferred brood combs (EPSFCTBC). The beeswax used was from Apis mellifera L.

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Box model

Table 1: Factorial arrangement of treatments Material Honeycomb Factorial arrangement of of the box material treatments

AFM

BMW

UTBC

AFM- BMW - UTBC

T1 *

AFM

BMW

TBCCAMBW

AFM - BMW - TBCCAMBW

T2

AFM

BMW

EPSFCTBC

AFM - BMW - EPSFCTBC

T3

AFM

BMW +PS UTBC

AFM - BMW +PS- UTBC

T4

AFM

BMW +PS TBCCAMBW

AFM BMW TBCCAMBW

AFM

BMW +PS EPSFCTBC

AFM - BMW +PS- EPSFCTBC T6

PAM

BMW

UTBC

PAM- BMW - UTBC

T7 *

PAM

BMW

TBCCAMBW

PAM - BMW - TBCCAMBW

T8

PAM

BMW

EPSFCTBC

PAM - BMW - EPSFCTBC

T9

PAM

BMW +PS UTBC

PAM - BMW +PS- UTBC

T10

PAM

BMW +PS TBCCAMBW

PAM BMW TBCCAMBW

PAM

BMW +PS EPSFCTBC

PAM-BMW+PS- EPSFCTBC

+PS-

+PS-

Code

T5

T11 T12

AFM= Ailton-Fontana model, PAM= Portugal-Araujo model, BMW= box made of wood, BMW+PS= + expandable polystyrene, UTBC = unlined transferred brood combs, TBCCAMBW = transferred brood combs lined with Apis mellifera wax, EPSFCTBC = transferred brood combs covered with expandable polystyrene. * Control treatments: T1 for Ailton-Fontana Model (AFM) and T7 for Portugal-Araujo Model (PAM).

Because the initial colony weight was highly variable for all split colonies, it was introduced as a covariate to the statistical model. The statistical model of the experiment was a mixedeffects model with analysis of covariance, represented as follows:

𝐲𝐢𝐣𝐤𝐥 μ + block l + αi + βj + γk + (αβ)ij + (αγ)ik + (βγ)jk + (αβγ)ijk + δ(xijkl − x̅… ) + eijkl with i = 1,2; j = 1,2; k = 1,2,3 and l = 1,2,3

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Where: 𝐲𝐢𝐣𝐤𝐥 is the response variable of the ith effect of the box model with the jth type of building material and the kth type of brood comb coating in the lth block; μ is the overall mean; block_l is the random effect of the lth block with mean 0 and variance σ2block ; 𝛂𝐢 is the fixed effect of the ith fixed effect of the box model; 𝛃𝐣 is the fixed effect of the box construction material; 𝛄𝐤 is the fixed effect of the kth type of brood comb coating; (𝛂𝛃)𝐢𝐣 , (𝛂𝛄)𝐢𝐤 , (𝛃𝛄)𝐣𝐤, and (𝛂𝛃𝛄)𝐢𝐣𝐤 are the interactions of the fixed effects; 𝛅(𝐱 𝐢𝐣𝐤𝐥 − 𝐱̅ … ) is the covariate whose linear regression coefficient is δ with respect to the initial weight xijkl ; 𝐞𝐢𝐣𝐤𝐥 is the random experimental error, which is assumed to be independent and identically normally distributed with mean zero and variance σ2 . The multiple comparison analysis of means was performed using the GLIMMIX procedure of the SAS version 9.4 statistical package. The means were compared using Fisher's LSD test. The response variables (temperature) analyzed under this design were classified as follows: daytime ambient temperature (DAT), nighttime ambient temperature (NAT), average ambient temperature (AAT), inner nest temperature in the daytime (INTD), inner nest temperature in the nighttime (INTN) and average internal temperature (AIT). With respect to colony size, the following measurements were made: initial colony weight (ICW), final colony weight (FCW), colony weight gain (CWG), number of brood cells built (NBCB), number of total pots built (NTPB). Finally, in order to observe the relationships between the response variables, a Pearson correlation analysis was performed. For this study, 18 AFM boxes with a volume of 5.3 L and 18 PAM boxes with a volume of 4.2 L were built. In the AFM model, nine of the boxes were made entirely of wood (2.54 cm thick), and nine, of wood (2.54 cm thick) and expandable polystyrene. As for the PAM model boxes, they were built under the same conditions as described for AFM. On the other hand, the brood combs transferred to the 36 boxes built with the aforementioned characteristics were lined with the following types of materials: an Apis mellifera wax mold (TBCCAMBW) (Figure 1) with a diameter of 12 cm by 6 cm high and a thickness of 0.2 mm, 4 ventilation holes, a diameter of 1 cm on each of the edges, and an expandable polystyrene foam mold (EPSFCTBC) (Figure 2) that had similar characteristics to TBCCAMBW and also included nests without this treatment as a control.

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Figure 1: Preparation of the Apis mellifera wax coating for transferred brood combs (TBCCAMBW)

A) Measurement tracing on a stamped European honeybee Apis mellifera L. wax sheet B) Cutting of sheets. C) Size adjustment (6 x 30 cm). D) Production of ventilation holes with punch with a diameter of 1 cm. E) Finished sheet with ventilation holes. F) Cylinder for placing the newly transferred brood inside the cylinder. Source: Developed by the authors. Photo: H.R. Salazar-Vargas.

Figure 2: Processing of the coating for transferred brood combs using an expandable polystyrene container

A) View of the bottom of the expandable polystyrene container B) Plotting measurements on the container. C) Cut with scissors from the lower part of the container. D) The lower part of the container is removed. E) Production of ventilation holes with punch with a diameter of 1 cm. F) Finished coating with ventilation holes. G) Transferred brood honeycombs lined with expandable polystyrene (EPSFCTBC). Source: Developed by the authors. Photo: H.R. Salazar-Vargas.

Table 1 shows the 12 treatments (three replicates each) resulting from the combinations of three factors (box model, construction material of the boxes, nest-coating materials) and their respective levels. In order to facilitate the identification of the combination, a key was assigned to each combination. During 41 d prior to the start of the experiment, periodic revisions were made where all colonies were fed with honey and pollen and control measures were taken: cleaning of the box and use of internal traps with the use of attractant (5% acetic acid), in colonies that were positive for vinegar flies (Pseudohypocera spp.). When the colonies showed similar behavior, they were placed in the Meliponarium of the Permaculture Area of the CórdobaCP Campus. These were randomly distributed in three blocks of 12 colonies with each of the combinations, the first block was placed at a distance of 2 m from the floor; the second, at a distance of 1.5 m, and the third, at a distance of 1 m from the floor. Nest entrances were oriented to the north. In order to evaluate the interaction of box pattern, box construction material, and nest coating material on internal temperature, a digital thermometer sensor was placed on the last brood disk of each colony (VA-DT-1H Avaly®). For 12 wk, the inner nest

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temperature and ambient temperature were recorded every 4 h. Temperature data were collected during the day at 0900 h, 1300 h, and 1700 h, while during the night, the times were 2100 h, 0100 h and 0500 h. In order to estimate the weight increase of the daughter colony, its initial and final weights were quantified. A portable scale (EQB-100 Torrey®) was used for this purpose. In addition, the number of brood cells was calculated, indirectly, by measuring the height and diameter of the nest, relating it to the estimated number of cells per square centimeter according to a previous count, and the number of total pots was visually counted(5).

Results During the study period, the average daytime ambient temperature was 27.3 °C (range= 26.7 to 28.4 °C) and the average nighttime ambient temperature was 21.2 °C (range= 20.8 to 22.4 °C). The interaction between box model, box construction material and nest coating material for daytime internal nest temperature (DINT) shows significant difference (P<0.05), but not for the nighttime internal nest temperature (NINT) (P>0.05). For the DINT between treatments, the highest adjusted mean corresponds to T11 with an adjusted mean of 31.5 °C (Table 2), and the lowest, to T4. The treatments with the highest adjusted mean for the variable TINN were T1, T5 and T11, and the lowest was T4. No significant differences (P>0.05) were observed between the control treatment T1 and T5. However, were significant differences (P>0.05) were found between treatments T7 and T11. Table 2: Adjusted means (±SD) for the variables DINT, NINT and NIT of the nest of S. mexicana Nest inner temperature (°C) Treatment In the daytime (DINT) At night (NINT) Mean (NIT) T1

29.598 ± 0.715 abc

27.896 ± 1.012 a

28.745 ± 0.837 ab

T2

29.391 ± 0.726 abc

27.058 ± 1.03 ab

28.222 ± 0.851 ab

T3

28.361 ± 0.714 c

25.386 ± 1.011 ab

26.872 ± 0.836 bc

T4

25.929 ± 1.024 d

23.395 ± 1.504 b

24.655 ± 1.223 c

T5

30.132 ± 0.69 abc

27.973 ± 0.972 a

29.052 ± 0.807 ab

T6

29.497 ± 0.697 abc

27.178 ± 0.984 ab

28.339 ± 0.815 ab

T7

28.736 ± 0.69 bc

25.323 ± 0.971 ab

27.029 ± 0.806 bc

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T8

29.771 ± 0.741 abc

26.484 ± 1.054 ab

28.13 ± 0.87 ab

T9

28.811 ± 0.73 bc

24.895 ± 1.037 ab

26.855 ± 0.856 bc

T10

30.292 ± 0.698 ab

27.198 ± 0.985 ab

28.746 ± 0.816 ab

T11

31.358 ± 0.761 a

28.137 ± 1.088 a

29.75 ± 0.896 a

T12

30.148 ± 0.772 abc

26.741 ± 1.106 ab

28.448 ± 0.91ab

abcd

Different letters indicate significant difference between treatments (P˂0.05).

The graph of the adjusted mean NIT of the treatments over a 24 h period (Figure 3) shows similar oscillations between treatments. The highest mean oscillations correspond to T11 and T5, and the lowest, to T4. Figure 3: Adjusted mean temperature (±SD) of S. mexicana nests

T1(AFM-BMW-UTBC), T2(AFM- BMW-TBCCAMBW), T3(AFM- BMW- EPSFCTBC), T4(AFM- BMW +PS- UTBC), T5(AFM BMW +PS- TBCCAMBW), T6(AFM- BMW +PS- EPSFCTBC), T7(PAM- BMWUTBC), T8(PAM- BMW-TBCCAMBW), T9(PAM- BMW- EPSFCTBC), T10(PAM- BMW +PS- UTBC), T11(PAM- BMW +PS- TBCCAMBW), and T12 (PAM- BMW +PS- EPSFCTBC), during 24 h.

Table 3 shows the results of the adjusted means for the final colony weight (FCW), colony weight gain (CWG), as well as the number of built breeding cells (NBBC) and the total number of built pots (TNBP). Significant differences were observed for the variables analyzed: FCW (P=0.0224), CWG (P=0.0224), NBBC (P=0.0036), but not for TNBC (P=0.1509).

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Table 3: Adjusted means (±SD) of the ICW, FCW, and CWG of S. mexicana nests after 12 weeks of the experiment Weight of the colony (kg) Treatments

Initial weight (ICW)

Final weight (FCW)

Weight gain (CWG)

T1

0.2021± 0.0293

0.308 ± 0.0515 abc

0.1499 ± 0.0515 abc

T2

0.2112 ± 0.0293

0.294 ± 0.0524 abc

0.1358 ± 0.0524 abc

T3

0.2015 ± 0.0293

0.368 ± 0.0514 ab

0.2099 ± 0.0514 ab

T4

0.3352 ± 0.0293

0.17 ± 0.0768 c

0.0113 ± 0.0768 c

T5

0.1653 ± 0.0293

0.308 ± 0.0495 abc

0.1491 ± 0.0495 abc

T6

0.1344 ± 0.0293

0.307 ± 0.05 abc

0.1481 ± 0.05 abc

T7

0.1594 ± 0.0293

0.188 ± 0.0494 c

0.0295 ± 0.0494 c

T8

0.0953 ± 0.0293

0.233 ± 0.0537 bc

0.0748 ± 0.0537 bc

T9

0.1026 ± 0.0293

0.195 ± 0.0528 c

0.0369 ± 0.0528 c

T10

0.1333 ± 0.0293

0.254 ± 0.0501 bc

0.0953 ± 0.0501 bc

T11

0.083 ± 0.0293

0.448 ± 0.0554 a

0.2893 ± 0.0554 a

T12

0.077 ± 0.0293

0.258 ± 0.0563 bc

0.0991 ± 0.0563 bc

abc

Different letters indicate significant difference between treatments (P˂0.05).

Comparisons between treatments revealed that for the FCW and CWG variables, T3 (AFMBMW-EPSFCTBC) and T11 were the highest (Table 3), and T4 (AFM-BMW- EPSFCTBC) were the lowest. With respect to the NBBC variables, the highest values correspond to T5 and T11, and for TNBP, the highest values correspond to treatments T4, T5 and T11 (Table 4). There is a significant correlation between BIT and NBBC (P˂0.0001), between ICW and TNBP (P˂0.0001), and between FCW with NBBC (P˂0.0001) and TNBP (P˂0.0001). T3 and T11 had higher FCW and CWG compared to the other treatments (Figure 3).

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Table 4: Adjusted means (±SD) of NBBC and TNBP of S. mexicana after 12 weeks of the experiment Number of built breeding cells Total number of built pots Treatments (NBBC) (TNBP) T1 2372.1 ± 819.66 bc 32.801 ± 8.6603 abc T2 3029.8 ± 829.78 abc 26.189 ± 8.7897 bc T3 2158.8 ± 819.01 bcd 18.558 ± 8.6521 c T4 -496.44 ± 1110.6 d 36.3 ± 12.286 abc T5 3511.5 ± 797.54 ab 43.688 ± 8.3764 ab T6 1950.6 ± 803.82 bcd 31.724 ± 8.4572 abc T7 1293.7 ± 796.98 cd 21.184 ± 8.3692 c T8 2189.1 ± 843.39 bcd 31.932 ± 8.9632 abc T9 1245.2 ± 833.41 cd 25.555 ± 8.8359 bc T10 2739.2 ± 804.48 bc 30.551 ± 8.4657 bc T11 4956.8 ± 862.5 a 52.006 ± 9.2057 a T12 1784.7 ± 872.76 bcd 32.846 ± 9.3355 abc abcd

Different letters indicate significant difference between treatments (P˂0.05).

Discussion In this study, the best treatments providing average nest inner temperature (NIT), DINT and NINT suitable for the development of S. mexicana broods were the following treatments: T5 (AFM- BMW+PS- TBCCAMBW) and T11 (PAM-BMW+PS- TBCCAMBW). This is partly explained by the positive interactions resulting from adding a material with thermal insulating properties (expandable polystyrene) in the construction of rational boxes (28), and coating the newly transferred brood combs with a material that mimics the function of the involucrum, such as Apis mellifera L. beeswax. The interactions of these combinations had a positive impact on the inner temperature of the nest, which in turn influenced the development of the colony by improving the following aspects: NBBC, TNBP, FCW, and CWG. As in the case of Melipona subnitida(29), which was provided with the most favorable conditions, such as high temperature and food, which led to an increase in brood cells. It has also been observed that Nannotrigona testaceicornis, housed in artificially heated boxes during the winter period, maintains brood production and reduces the thermoregulatory activities of the bees during the day or night(30). When comparing the results obtained in the nest temperatures (DINT, NINT, NIT) in treatments T5 (29.052 ± 0.807) and T11 (29.75 ± 0.896), although there were no significant differences (P>0.05) between these two treatments, T11 showed the best results in terms of nest inner temperature and colony development expressed in a higher number of brood cells

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(4,956 ± 862) and storage pots (52 ± 9). These results confirm that internal nest thermoregulation is important for social insects, since the development and survival of the colony depends on it(8,9). The temperature range attained (28.137 to 31.35 °C) with this treatment was attributed to the fact that the PAM rational box was designed from the beginning for S. mexicana and has the appropriate volume (4.3 L) for the species. The interaction between the internal volume of the PAM, the material with thermal insulating properties, and the protection of the brood using a wax mold of Apis mellifera L. render this treatment one of the best for breeding S. mexicana. The temperature range for good brood development in native bees is 31 to 32.3 °C(11), and the optimal temperature is 35 °C(10). The nest temperature result obtained with this treatment lies within the range that has been calculated as adequate for the development of this species. Including a material with insulating properties (expandable polystyrene foam) in the rational box models (AFM, PAM) and covering the transferred brood combs is crucial for providing an adequate temperature range for the development of the small-sized colony obtained by artificial division. The interaction between these two factors plays an important role in nest thermoregulation. This is clearly verified in the results obtained in treatments T7 (27.029 ± 0.806 °C) and T11 (29.75 ± 0.896 °C); where the rational box model PAM was the same for both treatments. The difference is that, in T7, the rational box does not include a material with insulating properties in its design, nor is the brood covered with any type of material. These differences in the treatments resulted in significant differences in the internal nest temperature (P<0.05). Other stingless bee species respond in a similar way, as is the case of Melipona colimana, which maintains a homogeneous temperature regardless of the ambient temperature, if the conditions inside the box are favorable(31). In the case of the AFM rational box, which was designed for the species T. angustula and N. testaceicornis(24), its dimensions were modified in order to adapt it to the behavior of S. mexicana. Its final volume due to the modifications was 5.3 L, slightly higher than that of the PAM box. Due to its larger volume, the results showed that the modified AFM works adequately to house S. mexicana, but the transferred brood combs must be coated with an A. mellifera L. beeswax mold. The modified, all-wood, AFM rational box also provided adequate nest temperature when the brood combs were coated with beeswax. The treatment with the lowest nest NIT was treatment T4 (AFM- BMW+PS- UTBC). The NINT was 23.395 ± 1.504 and had a negative effect on the NBBC (-496.44 ± 1110.6). An inadequate internal temperature range causes the bees to spend most of their energies on building insulation structures, and less time collecting nectar and pollen that are essential for colony development and survival(11,32). In the case of Scaptotrigona depilis, temperatures between 26 and 34 °C do not affect brood survival; however, temperatures below 22 °C or above 38 °C cause brood mortality; therefore, it is very likely that small colonies will be lost under these conditions(14). 448


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It is important to note that the Ailton-Fontana Model (AFM) was designed for T. angustula and N. testaceicornis (small-sized species), although in this study the model was modified by adding expandable polystyrene foam sheets to its original design. However, this action was not sufficient to provide an optimal temperature for the development of small-sized colonies of S. mexicana obtained by artificial division. Due to the larger volume size (5.3 L) of the AFM box, in the case of S. mexicana the brood combs must be coated with beeswax in order to obtain better results, as was observed in the T5 treatment (AFM- BMW+PSTBCCAMBW) where one of the best NITs was achieved. Colonies housed in the AMF modified with expandable polystyrene foam sheets and without comb coatings had the lowest values for the following variables: final brood weight, brood weight gain, and number of built breeding cells. This is attributed to the relationship that these variables have with nest thermoregulation. As for the total number of pots, this variable was similar to the rest of the treatments; this is explained by the fact that, during the study period (spring-summer), the food supply is not affected because the nectar flow is abundant and is favored by the ambient temperature during the day. In other studies with Trigona carbonaria, it was observed that, for these colonies, low temperatures in the nest produced a good weight gain; due to the excessive construction of involucrum or batumen; however, there was little brood development(33). The results showed that the AMF rational box constructed exclusively of 3.74 cm (2.54 cm + 1.2 cm) wood provides adequate temperature ranges (27.896 to 29.598 °C) for the brood housed inside it. In the case of M. colimana, internal temperature control is better with greater wall thickness within the box(22). The combination of using the AMF and coating the combs with the Apis mellifera L. wax mold further improves the internal temperature range of the nest. The combinations of treatments T3, T6, T9 and T12 are not recommended because the bees reject the covering of the brood combs with expandable polystyrene foam molds: at the end of the study period, bites were observed on this material, which the bees were trying to manipulate in order to carry out the passive thermoregulation of the nest.

Conclusions and implications The modified Portugal Araujo model box (PAM) provides a suitable temperature range (25,323-28,736°C) for the development of small-sized colonies of S. mexicana obtained by artificial division. However, colony development and temperature range is slightly improved when the brood combs are coated with Apis mellifera L. beeswax. The modified PAM brood

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box built with wooden walls and expandable polystyrene foam sheets provided a better temperature range (27.198-30.292 °C). The Ailton-Fontana model box (AFM), although not designed for breeding S. mexicana, showed that the modified model provides adequate temperature ranges (27.896-29.598 °C) for the development of this species. This temperature range was improved when the AFM box was modified by adding polystyrene foam sheets to its design and coating the brood combs with European beeswax (T5). The use of modified AFM rational brood boxes with expandable polystyrene is not recommended unless a coating of Apis mellifera L. beeswax is applied to the newly transferred brood combs, because their volume makes it difficult for the bees to maintain an adequate temperature range for their development. Literature cited: 1.

Cortopassi-Laurino M, Imperatriz-Fonseca VL, Roubik DW, Dollin A, Heard T, Aguilar I, Nogueira-Neto P. Global meliponiculture: challenges and opportunities. Apidologie 2006;37(2): 275–292.

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Jaffé R, Pope N, Carvalho AT, Maia UM, Blochtein B, Carvalho CAL, ImperatrizFonseca VL. Bees for development: Brazilian survey reveals how to optimize stingless beekeeping. PLoS ONE 2015;10(3).

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Halcroft MT, Spooner-Hart R, Haigh AM, Heard TA, Dollin A. The Australian stingless bee industry: a follow-up survey, one decade on. J Apic Res 2013;52(2):1–7.

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Villanueva-Gutiérrez R, Roubik DW, Colli-Ucán W, Güemez-Ricalde FJ, Buchmann SL. A critical view of colony losses in managed Mayan honey-making bees (Apidae: Meliponini) in the heart of Zona Maya. J Kan Ent Soc 2013;86(4):352–362.

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Lóriga-Peña W, Álvarez-López D, Fonte-Carballo L, Demedio-Lorenzo J. Población inmadura y reservas de alimentos en colonias naturales de Melipona beecheii Bennett (Apidae: Meliponini) como factores básicos para su salud. Rev Sal Anim 2015;37(1):47–51.

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Pisté-Mukul MJ. Caracterización y termorregulación del nido de la abeja sin aguijón Scaptotrigona mexicana alojado en cavidades artificiales [tesis maestría]. Campeche, México: Colegio de Postgraduados; 2011.

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Quezada-Euán JJ. Biología y uso de las abejas sin aguijón de la península de Yucatán, México (Hymenoptera: Meliponini). Edi Univ Aut Yuc 2005;(16).

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Engels W, Rosenkranz P, Engels E. Thermoregulation in the nest of the Neotropical Stingless bee Scaptotrigona postiça and a hypothesis on the evolution of temperature homeostasis in highly Eusocial bees. Stud Neo F Env 1995;30(4):193–205.

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Moritz RFA, Southwick EE. Bees as superorganisms - An evolutionary reality. Heidelberg, Germany: Springer; 1992.

10. Márquez-Luna JM. Meliponicultura en México. Dugesiana 1994;1(1):3–12. 11. Roubik DW, Peralta JA. Thermodynamics in nests of two melipona species in Brasil. A Amaz 1983;13(2):453–466. 12. Jones JC, Oldroyd BP. Nest thermoregulation in social insects. Adv Ins Phys 2006;33:153–191. 13. Roubik DW. Stingless bee nesting biology. Apidologie 2006;37(2):124–143. 14. Vollet-Neto A, Menezes C, Imperatriz-Fonseca VL. Behavioural and developmental responses of a stingless bee (Scaptotrigona depilis) to nest overheating. Apidologie 2015;46(4):455–464. 15. Quijano E, González-Acereto J, Quezada-Euán JG. Desarrollo de divisiones de colonias de Melipona beecheii (Hymenoptera, Meliponini) a partir de tres tamaños de población. Bioagrociencias 2008;1(1):4–11. 16. Quezada-Euán JJ. Biología y uso de las abejas sin aguijón de la península de Yucatán, México (Hymenoptera: Meliponini). Edi Univ Aut Yuc 2005;(16). 17. Quezada-Euán JJ, May-Itzá W, González-Acereto JA. Meliponiculture in Mexico: problems and perspective for development. Bee World 2001;82(4):160–167. 18. Biesmeijer JC, Slaa EJ. Information flow and organization of stingless bee foraging. Apidologie 2004;35(2):143–157. 19. Macias-Macias JO, Quezada-Euan J, Tapia-González JM, Conteras-Escareño F. Nesting sites, nest density and spatial distribution of Melipona colimana Ayala (Hymenoptera: Apidae: Meliponini) in two highland zones of western, Mexico. Sociobiology 2014;61(4): 423-427. 20. Moo-Valle H, Quezada-Euán JJ, Navarro J, Rodríguez-Carvajal LA. Patterns of intranidal temperature fluctuation for Melipona beecheii colonies in natural nesting cavities. J Apic Res 2000;39(2):3–7. 21. Macías-Macías JO, Quezada-Euán JJ, González JM. Effect of lodging type on the internal temperature and humidity of colonies of Melipona colimana (Hymenoptera: Meliponini) from a Mexican temperate zone. J Apic Res 2011;50(3):235–241. 22. Ayala R. Revisión de las abejas sin Aguijón de México (Hymenoptera: Apidae: Meliponini). Fol Ento Mex 1999;106.

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23. Guzmán-Díaz M, Balboa C, Vandame R, Albores ML, González-Acereto J. Manejo de las abejas nativas sin aguijón en México. Primer ed: El Colegio de la Frontera Sur; 2011. 24. Barbieri C. Caracterização da meliponicultura e do perfil do meliponicultor no estado de São Paulo: ameaças e estratégias de conservação de abelhas sem ferrão. [tesis maestría]. São Paulo, Brasil: Universidad de São Paulo; 2018. 25. INEGI. Prontuario de información geográfica municipal de los Estados Unidos Mexicanos, Amatlán de los Reyes, Veracruz de Ignacio de la Llave. México; 2009. 26. Kwapong P, Aidoo K, Combey R, Karikari A. Stingless bees, importance, management and utilization. A training manual for stingless beekeeping. First Ed. Accra North, Ghana, Africa: Unimax Macmillan LTD; 2010. 27. Arzaluz A, Obregón F, Jones R. Optimum brood size for artificial propagation of the stingless bee, Scaptoptrigona mexicana. J Apic Res 2002;41(1–2):62–63. 28. Horvath JS. Expanded Polystyrene (EPS) geofoam: An introduction to material behavior. Geo Geomembranes 1994;13(4):263–280. 29. Maia-Silva C, Hrncir M, da Silva CI, Imperatriz-Fonseca VL. Survival strategies of stingless bees (Melipona subnitida) in an unpredictable environment, the Brazilian tropical dry forest. Apidologie 2015;46(5):631–643. 30. Vollet-Neto A, Menezes C, Imperatriz-Fonseca VL. Brood production increases when artificial heating is provided to colonies of stingless bees. J Apic Res 2011;50(3):242– 247. 31. Macías-Macías JO, Quezada-Euán JJ, Contreras-Escareño F, Tapia-González JM, MooValle H, Ayala, R. Comparative temperature tolerance in stingless bee species from tropical highlands and lowlands of Mexico and implications for their conservation (Hymenoptera: Apidae: Meliponini). Apidologie 2011;42(6):679–689. 32. Marshall AG. Ecology and natural history of tropical bees. J Trop Eco 1989;9(2):248– 248. 33. Norgate M, Boyd-Gerny S, Simonov V, Rosa MG, Heard TA, Dyer AG. Ambient temperature influences Australian native stingless bee (Trigona carbonaria) preference for warm nectar. PLOS ONE 2010;5(8).

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https://doi.org/10.22319/rmcp.v12i2.5652 Article

Analysis of beekeeping profitability by strata in Aguascalientes, Mexico

José Inés Zavala Beltrán a Marco Andrés López Santiago b* Ramón Valdivia Alcalá a Blanca Margarita Montiel Batalla a

a

Universidad Autónoma Chapingo (UACh). División de Ciencias EconómicoAdministrativas, Carretera México-Texcoco Km 38.5, Texcoco, Estado de México. b

UACh. Unidad Regional Universitaria de Zonas Áridas, Durango, México.

*

Corresponding author: marcoandres@chapingo.uruza.edu.mx

Abstract: The present research focused on analyzing the cost structure and profitability in the beekeeping production process. Sampling techniques were utilized to randomly select 56 beekeepers from a total of 230; they were grouped into three strata: producers with 20 to 50 hives (small), 51 to 200 hives (medium), and more than 200 hives (large). The total economic cost of production was found to be mainly composed of the variable cost, with an average relative share of 55.4 % in the three strata. Feed expenditure is the primary concept, considering that 90.0 % of beekeepers feed sugar or fructose when there are no blossoms to sustain the hive. The fixed cost represents 14.0 % of the total. The largest expenditure was due to the depreciation of machinery and field equipment. Opportunity costs represent 30.6 % on average for the three strata. The average yield per hive was 25.4 kg/year. In conclusion, considering the economic analysis, the activity is not viable for stratum I, since it does not consider the value of all the resources involved in the productive process (opportunity costs). Likewise, in this stratum the main income comes from other activities. In financial terms, the activity is viable in all three strata, which indicates that it has the

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capacity to cover both the fixed and the variable costs. When opportunity costs are included, the fixed and variable costs decrease. Key words: Bees, Productivity, Competitivity.

Received: 26/03/2020 Accepted: 11/09/2020

Introduction In Mexico, beekeeping is of great socioeconomic and ecological importance and is considered one of the main livestock activities generating foreign exchange(1). Generally, this activity is associated only with the production of honey, pollen, royal jelly, and propolis; however, bees are also essential to the balance of the environment, due to their collaboration in pollination. It is estimated that, out of the 90 % of pollination that occurs in flowering plants worldwide, 67 % is carried out by insects, which constitute the most important group of pollinators for both wild and cultivated plant species(2). According to figures from the livestock sector, Mexico ranks between fifth and sixth in the world as a producer of honey, having produced 62,320 t in the year 2018(3). The value of exports for 2018 increased by 15 % over the previous year(3), and the volume was 60 % higher than that of 2017(1). The state of Aguascalientes is located in the Mexican highlands. In this region, due to the semi-arid climate, a large number of shrubs such as mesquite (Prosopis laevigata) bloom, and the Arizona beggarticks (aceitilla, Bidens spp.) flower in the rainy season. In 2018, Aguascalientes had an inventory of 15,312 hives(4). According to the Beekeeping Product System of Aguascalientes (2018)(5), 230 beekeepers depend on bee production with only two bloomings per year: that of aceitilla in November, and that of mesquite in April. In the study area, more than 60 % of the honey is harvested in spring, with the mesquite (Prosopis laevigata) as a source of wild nectar. Unlike in the studied region, in southeastern Mexico there is such a great diversity of flowers that we cannot analyze their influence on honey production under the corresponding agroclimatic conditions(6). Aguascalientes has a competitive advantage in honey because it is of the monoflora type, which means that it has relatively homogeneous characteristics(6), as evidenced by the difference in price with respect to the national average(7).

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However, although there is a competitive advantage, there are factors that have caused a large number of beekeepers to abandon the activity or lower their production levels. A first adverse factor is low rainfall, which results in low grazing activity and a shortage of food(8). Additional factors are low producer prices in the honey market (there is a wide variation between producer and final consumer prices), deficient technical training in production, and high input costs(9). Other important apicultural products in this area are propolis, royal jelly, pollen, wax, biological material, queen bees, and genetic material(10). In this scenario, the competitiveness of any production system or process in the domestic market is determined by its level of profitability. Profitability is estimated by deducting the costs incurred in order to obtain the product from the sales value of a certain amount of product(9). In this sense, it is necessary to carry out a cost-benefit analysis and calculate the equilibrium prices in the region for the different types of beekeepers. Therefore, the objective of the present work was to estimate the cost structure, as well as a cash flow, and a financial and economic analysis(11) of the beekeeping production in the state of Aguascalientes, in order to determine the level of unit profits or profitability of the system. The hypothesis was that the cost of equipment, tools and inputs utilized in the production process have an inverse relationship with the profits obtained by the beekeeper in this region.

Material and methods Location of the area

The state of Aguascalientes is located at the following coordinates: 22°27'35" N, 21°37'20" S, north latitude, and 101°50'07" E, 102°52'27" W, west longitude, and is bordered to the north, northeast and west by Zacatecas, and to the southeast and south, by Jalisco. It represents 0.3 % of the country's surface area(12).

Sampling

The sample was calculated based on the population of beekeepers that are members of the beekeeping product system of the state of Aguascalientes. According to data from 2018, the register consisted of 230 beekeepers(5). Field information was collected through

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questionnaires; these were applied directly to the producers in the study area. The data presented come from the 11 municipalities of the state of Aguascalientes. It was used the stratification criteria provided by Vélez(13) and Fachini(14), where the beekeepers were classified into three categories according to the number of their hives: Small (10 to 50), Medium (51 to 200) and Large (more than 200). The stratified random sampling technique was used. The variable that was associated with the sampling procedure for variance estimation was the number of hives per beekeeper, and the error limit was 5%. The final sample size was estimated based on the following formula: 𝑁 ∗ 𝑍𝛼2 ∗ 𝑝 ∗ 𝑞 𝒏= 2 𝑑 (𝑁 − 1) + 𝑍𝛼2 ∗ 𝑝 ∗ 𝑞 Where: n= final sample size; Z=1.96 (confidence level); p= expected ratio (0.05); q= 1-p; N= total number of producers (230); d= accuracy (0.05). The sample consisted of 56 beekeepers included in the State Beekeeping Product System. The first stratum accounted for 11 % (7) of the final sample; the second stratum, for 40 % (22), and the third stratum, for 49 % (27). The information was processed using an Excel spreadsheet.

Content of the survey

The questions included in the questionnaire were divided into the following aspects: Technical handling: 1) Level of the beekeepers' knowledge of production activities; 2) Level of technical expertise; 3) Control of the percentage of Africanization in the zone; 4) Genotype; 5) Queen bee change frequency; 6) Frequency of hive replacement; 7) Feeding of the apiaries; 8) Disease and pest control; 9) Time invested in beekeeping. Costs: 1) Feed costs, 2) Pests and diseases, 3) Change of queen, 4) Labor, 5) Transfer, and 6) Other costs. Production: 1) Number of producers; 2) Number of hives; 3) Total production; 4) Location of the hives. Income: 1) Price of honey and by-products; 2) Production; 3) Sale.

Method

For the description and analysis of the social aspects related to beekeeping production, the following variables were considered: the importance of the genetic factor, technical

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management and the environment, organization for production and technical assistance. The elements considered for the processing and analysis of the technical coefficients were as follows: labor, number of apiaries, number of hives, food implements, disease control, number of harvests, among others. Labor and input costs were calculated considering the following variables: the number of day laborers used for the various activities and the expenses incurred to purchase sugar, vitamins, varroa control, among others. A cost analysis was performed as by Sagarnaga et al(11) with the methodology used by the United States Department of Agriculture (USDA), whose theoretical and methodological bases conform to the standards recommended by the Working Group on Costs and Returns of the American Agricultural Economics Association (AAEA). Within this context, the USDA classifies costs into two types: operating costs and allocated overhead. Washington State University classifies the costs into fixed and variable costs and disaggregates them into economic, financial, and disbursed costs. Financial costs include only fixed and variable costs; disbursed costs include, in addition to fixed and variable costs, the cash required to pay down the principal on long-term loans and to cover the producer's household expenses. Economic costs include financial costs and the opportunity cost of production factors(11). Opportunity costs were calculated: land, labor, capital and business management. The value of all resources in the production process was used, regardless of whether they represented disbursed or undisbursed expenses. Once the production costs were quantified, the target price was determined for each of the strata, where the minimum price was identified to ensure profitability(15).

Results Investments in hives and equipment

The beekeeping production units in Mexico are classic standard beehives. In Aguascalientes, the beekeepers build the hive with a support (mostly made of bricks), a floor, a brood chamber (langstroth type), and a roof, with two elevations. Table 1 shows the investment by each producer stratum. Regarding the investment in field equipment, its total value increases as the producer increases the number of hives; this is due to the need for greater installation capacity (core holders, brood chambers, and supers, mainly). The second and third strata increase considerably in work equipment, due to their greater capacity; some of the necessary

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components are the extractor, sedimentation tank, and uncapping bench. Producers of the first stratum (80 %) do not have the necessary technology; therefore, they opt to rent these serv ices mainly during the harvest. Table 1: Investment by the beekeeper ($) Producer strata by number of hives 1-50

51-200

Over 200

Work team

15,805.6

150,000.0

165,050.0

Field material

25,900.0

140,535.0

400,800.0

Total investment

41,705.6

290,535.0

565,850.0

38.9

14.9

19.46

Coefficient of variation (%)

Source: Prepared by the authors with data from the survey to beekeepers, 2018.

The difference between the strata was the investment in field and warehouse equipment and the quality of the equipment; i.e. an extractor for 80 frames is almost five times the value of one for 32 frames, or 10 times the value of one for galvanized sheets. The high costs cause beekeepers in stratum I to resort to renting equipment (cellars) for harvesting.

Cost structure

The production, economic, financial and disbursement costs were estimated by stratum, according to the number of hives, based on the information gathered from the surveys. The percentage structure of total costs is mainly composed of variable costs. Considering opportunity costs, the variable cost for stratum I is 51.9% (Table 2); 54.1 % for the second stratum (Table 3), and 60.2 % for the third stratum (Table 4).

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Table 2: Production cost structure ($) of Stratum I (1-50 hives) Concept of costs Economic Financial Disbursed Variable costs Food

12,801.78

12,801.78

12,801.78

Medications

182.14

182.14

182.14

Maintenance

1,000.00

1,000.00

1,000.00

Purchase of queens

3,295.25

3,295.25

3,295.25

Fuel

6,988.89

6,988.89

6,988.89

24,268.07

24,268.07

24,268.07

Land rentals

-

-

-

Indirect labor

-

-

-

Family labor

-

-

-

Equipment depreciation

2,000.00

2,000.00

-

Depreciation of field material

3,000.00

3,000.00

-

Other fixed costs

1,445.00

1,445.00

1,445.00

Total fixed costs

6,445.00

6,445.00

1,445.00

Opportunity cost of land (rent)

1,500.00

-

-

Working capital

4,170.56

-

-

Producer/family labor

5,600.00

-

-

Business management

4,800.00

-

-

Total opportunity costs

16,070.56

-

-

Total costs

46,783.63

30,713.07

25,713.07

Total variable costs Fixed costs

Opportunity costs

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Table 3: Production cost structure ($) of Stratum II (51-200 beehives) Concept of costs Variable costs Food Medications Maintenance Purchase of queens Fuel Labor Total variable costs Fixed costs Land rentals Indirect labor Family labor Equipment depreciation Depreciation of field material Other fixed costs Total fixed costs Opportunity costs Opportunity cost of land (rental) Working capital Producer/family labor Business management Total opportunity costs Total costs

Economic

Financial

Disbursed

40,319.07 1,008.00 1,500.00 14,182.08 13,640.00 4,008.18 74,657.33

40,319.07 1,008.00 1,500.00 14,182.08 13,640.00 4,008.18 74,657.33

40,319.07 1,008.00 1,500.00 14,182.08 13,640.00 4,008.18 74,657.33

3,000.00 7,260.00 4,840.00 2,080.00 17,180.00

3,000.00 7,260.00 4,840.00 2,080.00 17,180.00

3,000.00 2,080.00 5,080.00

1,500.00 29,053.50 8,400.00 7,200.00 46,153.50 137,990.83

91,837.33

79,737.33 Source: Prepared by the authors with data from the survey to beekeepers, 2018.

With respect to fixed costs, it was found that the participation is 13.8 %, 12.5 % and 15.8 %, respectively. Continuing with the fixed costs, a direct relationship was observed in the second and third strata. That is, by having more hives, the beekeeper chooses to acquire higher capacity technology. On the other hand, there is a need to increase the number of apiaries, which would entail higher land rental costs.

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Table 4: Production cost structure ($) of Stratum III (more than 200 beehives) Concept of costs Variable costs Food Medications Maintenance Purchase of queens Fuel Labor Total variable costs Fixed costs Land rentals Indirect labor Family labor Equipment depreciation Depreciation of field material Other fixed costs Total fixed costs Opportunity costs Opportunity cost of land (rent) Working capital Producer/family labor Business management Total opportunity costs Total costs

Economic

Financial

Disbursed

115,475.36 3,000.00 3,600.00 38,124.45 23,335.00 9,963.03 193,497.84

115,475.36 3,000.00 3,600.00 38,124.45 23,335.00 9,963.03 193,497.84

115,475.36 3,000.00 3,600.00 38,124.45 23,335.00 9,963.03 193,497.84

6,000.00 9,963.03 19,380.00 12,920.00 2,625.00 50,888.03

6,000.00 9,963.03 19,380.00 12,920.00 2,625.00 50,888.03

6,000.00 9,963.03 2,625.00 18,588.03

3,000.00 51,717.50 10,200.00 12,000.00 76,917.50 321,303.37

-

-

244,385.87

212,085.87

Source: Prepared by the authors with data from the survey to beekeepers, 2018.

Within the variable costs, the item with the highest participation is feed, in the state of Aguascalientes beekeepers feed the bees sugar and fructose. Feed is provided when there is no flowering and is important for the survival of the bees; in this sense, this variable cost increases progressively as the producer increases the number of hives. The second item with the highest share is the cost of transportation, which basically refers to the fuel used to carry out the technical management of each apiary. The third item corresponds to the labor required to carry out beekeeping activities; the largest number of day laborers is required during the harvest season (March-April). Fixed costs are mainly composed of the depreciation of field infrastructure, followed by the depreciation of work and protection equipment. In the case of the depreciation of working equipment (extractor, uncapping bench, stainless steel drum, etc.), it has an inverse relationship to the number of hives. 461


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Opportunity costs represent 34.3 % for stratum I, 33.4 % for stratum II, and 24.0 % for stratum III, with the cost of working capital making the largest contribution. For the calculation of opportunity costs of the producer's labor, the daily wages were quoted at 200 as a reference of the price of a daily wage in the region. Respondents in the first stratum consider that they require 28 d of labor per year to operate their hives; those in the second stratum consider that it takes them 42 d of labor, and those of the third stratum reported requiring 51 d of labor. The beekeepers in the region consider that the land has an opportunity cost of $1,500, with the understanding that, if the land is not used, it can be rented to other beekeepers at the aforementioned cost. In order to assess business management, producers in stratum I considered that they work one hour a week to manage the apiaries; those of stratum II work 3 h per week, and those of stratum III reported working 5 h a week to plan their activities. The estimated financial cost per kilogram of honey produced is $45.92, $31.54 and $25.49, respectively, for each stratum.

Revenues and profitability

When beekeepers depend mostly on beekeeping, they have more hives; on the contrary, when beekeepers have fewer hives, they tend to choose to engage in other income-generating activities. In order to estimate their income was estimated as follows, according to survey data: an average yield of 19.6 kg per hive at a price of $65 was considered for stratum I; 26.4 kg per hive at a price of $50.9, for stratum II, and 30.2 kg per hive at a price of $50.45, for stratum III. Table 5: Percentage contribution to total income Strata by number of hives Concept 20 to 50

51 to 199

200 or more

Economic contribution of beekeeping 9.6

32.5

62.8

Honey

97.2

87.0

88.0

Beeswax

1.0

1.6

3.9

Polen

0.0

0.0

0.3

Nuclei

0.0

3.7

2.4

Others

1.8

7.7

5.5

Total

100.0

100.0

100.0

Source: Prepared by the authors with data from the survey of beekeepers, 2018.

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As beekeepers acquire more hives, the income generated from beekeeping increases its share of the total income (Table 5). In this sense, it was noted that honey is the main product commercialized in the market. In financial terms, beekeeping is viable in all three strata, i.e. it has the capacity to cover both fixed and variable costs (Table 6). On the other hand, in economic terms, the activity is not viable in stratum I; this indicates that the factors of production are not adequately remunerated. In strata two and three, the activity is viable in economic terms because it remunerates fixed costs, variable costs, the producer's labor, the cost of investment and business management, and the depreciation. Table 6: Costs, revenues and profitability ($) Economic Financial Total costs 46,783.63 30,713.07 Total revenues 44,096.67 44,096.67 Stratum I Net income 2,686.96 13,383.60 Profitability ratio, % -5.7 43.6 Total costs 137,990.83 91,837.33 Total revenues 148,275.20 148,275.20 Stratum II Net income 10,284.37 56,437.87 Profitability ratio, % 7.5 61.5 Total costs 321,303.37 244,385.87 Total revenues 483,711.50 483,711.50 Stratum III Net income 162,408.13 239,325.63 Profitability ratio, % 50.5 97.9

Disbursed 25,713.07 44,096.67 18,383.60 71.5 79,737.33 148,275.20 68,537.87 86.0 212,085.87 483,711.50 271,625.63 128.1

Source: Prepared by the authors with data from the survey to beekeepers, 2018.

The prices of honey are differentiated by the type of nectar available in the region. In this case, the largest production comes from the mesquite flower(16), which is among the best listed at the international level(17). An inverse relationship was identified between the volume of production and the respective price, because the producer of stratum I sells his product to the local market, while strata II and III sell wholesale at a lower price in the national and international market (Table 7). Although small beekeepers achieve a higher price, they obtain lower profitability due to factors such as marketing channels, technical management, economy of scale, added value and limited governmental support.

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Stratum I Stratum II Stratum III

Table 7: Bee honey markets (%) Local National 92.78 7.22 34.50 23.00 24.38 27.50

International 0.00 43.50 47.12

Source: Prepared by the authors with data from the survey to beekeepers, 2018

Break-even price

The break-even point indicates the magnitude of production and the price at which the honey must be sold or produced in order to prevent a loss (Table 8).

Stratum I Stratum II Stratum III

Table 8: Break-even prices by stratum ($) Economic Financial Disbursed 69.95 45.92 38.45 47.39 31.54 27.38 33.51 25.49 22.12 Source: Prepared by the authors with data from the survey to beekeepers, 2018.

In stratum I, $69.95 is the price necessary to cover the cost of all resources, including family labor of the production unit, business management and net invested capital costs. Prices above $69.95 generate a return to risk assumed by the producer; below this amount they imply a return to the producer's labor, business management and a return on net invested capital that is lower than what could be generated with the best alternative use of resources. Also in the same stratum, the equilibrium price of $45.92, which the necessary price to cover the financial costs according to the accounting systems, implies zero retribution to the producer's labor. Prices below the break-even price imply a decrease in retained earnings. A price of $38.45 covers the cash costs of the production process. For strata II and III, the economic, financial and disbursed equilibrium prices are lower than that of the first stratum.

Discussion Based on the information gathered from the study area, it is clear that the need to acquire work equipment (increased capacity of the extractor, uncapping bench, mini-spinner, wax recuperator, sedimentation tank) and field equipment (supers, brood chambers, nuc frames, 464


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etc.) increases as the beekeeper acquires more hives. Thus, beekeepers in stratum II and III who operate with more than 51 hives have a production of more than one and a half tons, which leads them to choose to increase the capacity of machinery installation (stainless steel), thus favoring the safety of the products. The findings are consistent with studies(18) where they mention that the percentage of implements increases directly with the number of hives. In another similar study, it was stated that the inventory or possession of complementary equipment, such as extractors, uncapping tools and benches, funnels, knives, among others, increased progressively with the size of the apiary(19). Similarly, other authors(20) conclude that the greater the number of hives, the greater the investment in the hives. As beekeepers increase their hives, investment in field equipment is outpacing investment in machinery. This is consistent with what was reported for the state of Morelos, Mexico(13), where investments in machinery and equipment for beekeeping are said to be minimal; therefore, beehives represent the largest investment in absolute terms. According to the results of the study region, in the first stratum, the investment per hive was $933.33 (coefficient of variation of 20 %); $819.98 (coefficient of variation= 23.7 %) in the second, and $768.51 (coefficient of variation 32 %) for the third stratum, with an average of $830.60, which is lower than what was reported in the Mayan communities of the central coast of Yucatan, where the overall average investment per hive was $1,201.3 pesos(19). Regarding the cost structure in general for Mexico(9) it is estimated that the production costs of the beekeeping activity are composed mainly of variable costs, with a relative share of 67.1 %, while fixed costs represent a proportion of 32.9 % of the total cost. On the other hand, with respect to total cost, Yucatan reported a contribution of 77.9 % for variable cost and 22.1 % for fixed cost(19). With respect to the breakdown of the financial costs mentioned above, the estimated average at the national and state level was lower than the estimate for Aguascalientes. Thus, in the study area, for stratum I the variable financial cost contributed 79.0 % of the total; it was 81.3 % for stratum II, and 79.2 % and for stratum III. As for variable costs specifically, sugar represented 53.0 % of total variable costs for the first stratum; 54.4 %, for the second stratum, and 60.0 %, for the third stratum, with a total average of 55.8 %. These estimated percentages present a significant difference compared to the results of other studies(19) that report an average of 38.7 % for the first stratum, 54.4 % for the second stratum, and 60.0 % for the third stratum, with a total average of 55.8 %. A probable cause of this percentage difference may be due to the fact that the intervals between one flowering and the next are longer in the studied area (given the climatic conditions); therefore, the cost of feeding is increased. On the other hand, for the state of Nayarit, producers with fewer hives (stratum I) were found, through a model for the generation of costs in beekeeping enterprises, to have a greater 465


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expenditure in transportation; for the second (stratum II), the greatest expense is in the production material, and for the third stratum, it is labor(21). In the particular case of fixed costs, depreciation (depreciation in infrastructure, protection equipment and equipment) represented 63.0 % of total fixed costs. This was lower than that reported by other authors(19), of 88.4 % in average. When the analysis is made by adding opportunity costs (economic analysis), there is a decrease in the fixed and variable cost items. When beekeeping is the main economic activity, this is manifested by the possession of a larger number of apiaries. In contrast, when there are few hives, beekeepers diversify their economic activities(20). For this reason, in strata II and III of this study, a larger number of producers depended primarily on beekeeping. Also, little diversification was found to exist in beehive production; 90.7 % of beekeepers produce only honey, which is their main source of income. This percentage coincides with that observed in Argentina, which is 82 % in average(21), while in some regions of Mexico it is 99.5 %(19). The estimated break-even prices at the financial level ($45.92 per kilogram of honey for the first stratum, $31.54 per kilogram of honey for the second, and $25.46 for the third) were similar to those reported for some regions of Mexico(22). In Nayarit, the break-even point for income among beekeepers with 100 hives was found to be $14,865.00; $73,715.00 among beekeepers with 450 hives, and $52,642.00 among beekeepers with 600 hives(23).

Conclusions and implications The economic profits of small producers were observed to be negative, while those of the second and third strata are positive. The positive profitability for medium and large producers may be due to the scale of production, as these reduce input costs by purchasing in large volumes and assured sales prices. Based on the above results, it can be deduced that, in the state of Aguascalientes, stratum II and III practice medium- and high-scale beekeeping, while stratum I practices low-scale beekeeping, characterized by traditional management, which does not take into account administrative costs. In order to attain their consolidation, small producers must invest capital and purchase the technology necessary for the formation of small businesses, so that they may increase their production and thus be able to negotiate in the market. Based on the analyzed data, it can be concluded that there is a potential for the diversification of apicultural by-products in high demand in the market, such as royal jelly, propolis, pollen, wax, bee nuclei, and queens. 466


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Literature cited: 1. SIAVI. Sistema de Información Comercial Vía Internet. http://www.economiasnci.gob.mx/. Consultado Sep 12, 2019. 2. García GM, Ríos OLA, Álvarez-Castillo J. La polinización en los sistemas de producción agrícola: Revisión sistemática de la literatura. Idesia, 2016;34(3):53–68. 3. SIAP. Sistema de Información Agropecuaria y Pesquera. Produccion Pecuaria. Resumen nacional. https://www.gob.mx/siap/acciones-y-programas/produccion-pecuaria. Consultado 20 Oct, 2019. 4. SIACON-NG. Sistema de Información Agroalimentaria de Consulta. Consultado 20 Oct, 2019. 5. Rodriguez S. Gana miel de aguascalientes primer certificado TIF. NW aguascalientes. (12 de febrero de 2018). Recuperado de https://newsweekespanol.com/2018/02/gana-mielde-aguascalientes-primer-certificado-tif/ 6. Medina CSE, Álvarez JM, Portillo VM, Terrazas GGH. Influencia de los factores ambientales y de manejo en la segunda temporada de producción de miel de abeja en Aguascalientes, México. Rev Esp Estud Agrosoc Pesq 2014;(238):65–80. 7. Martínez BHA, Hernández AEG. Análisis de brechas tecnológicas e identificación de oportunidades de vinculación con organizaciones y empresas del sector apícola en Aguascalientes.. 1ra ed. (versión electrónica). Aguascalientes, México. Universidad Autónoma de Aguascalientes; 2017. 8. Castellanos PBP, Gallardo LF, Sol SA, Landeros SC, Diaz PG, Sierra FP, Santibañez JL. Impacto potencial del cambio climático en la apicultura. Rev Iberoam Bioecon Cambio Clim 2016;2(1):1-19. 9. Magaña MA, Leyva CE. Costos y rentabilidad del proceso de producción apícola en México. Contad Adm 2011;(235):99–119. 10. Franco VH, Siqueiros ME, Hernández EG. Flora apícola del estado de aguascalientes. 1ra ed. México. Universidad Autónoma de Aguascalientes; 2012. 11. Sagarnaga VLM, Salas GJM, Aguilar AJ. Ingresos y costos de produccion. Unidades representativas de produccion. Trópico humedo y mesa central. Centro de Investigaciones Economicas, Sociales y Tecnologicas de la Agroindustria y la Agricultura mundial (CIESTAAM) 2014;1 (1): 19-47. 12. Instituto Nacional de Estadística y Geografía (México). Anuario estadístico y geográfico de Aguascalientes: INEGI; 2017. 467


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13. Vélez IA, Espinosa GJA, Amaro GR, Arechavaleta VME. Tipología y caracterización de apicultores del Estado de Morelos, México. Rev Mex Cienc Pecu 2016;7(4):507–524. 14. Fachini C, Firetti R, Cardoso-Oliveira E, Assiz-Caravalo A. Perfil da apicultura em Capão Bonito, Estado de São Paulo: aplicação da análise multivariada. Rev Econom Agríc 2010;57(1):51-63. 15. Baca UG. Evaluación de proyectos. 7a ed. México. McGraw-Hill/Interamericana Editores, SA de CV; 2013. 16. Medina CSE, Tirado GDN, Portillo VM, López SMA, Franco OVH. Environmental implications for the production of honey from mesquite (Prosopis laevigata) in semiarid ecosystems. J Apic Res 2018;57(4):507–515. 17. Soto MLE, Elizarra BR, Soto MI. Situación apícola en México y perspectiva de la producción de miel en el Estado de Veracruz. Rev Estrateg Desarro Empresarial 2017;3(7):40–64. 18. Contreras-Uc LC, Magaña MA, Sanginés JR. Características técnicas y socioeconómicas de la apicultura en comunidades mayas del Litoral Centro de Yucatán. Acta Univ 2018;28(1):44–86. 19. Contreras- Uc LC, Magaña MA. Costos y rentabilidad de la apicultura a pequeña escala en comunidades mayas del Litoral Centro de Yucatán, México. Invest cien 2017;25(71):52-58. 20. Contreras EF, Perez AB, Echazarreta CM, Cavazos AJ, Macias JO, Tapia GJM. Características y situación actual de la apicultura en las regiones Sur y Sureste de Jalisco, Mexico. Rev Mex Cienc Pecu 2013;4(3):387–398. 21. Ulmer J, Travadelo M, Caporgno J, Castignani H. Caracterización de los modelos de producción apícola representativos de la zona central de la provincia de Santa Fé. Cienc Agron 2011;(XVIII):043–049. 22. Dolores MG, Santiago MDJ, Arana CJJ, Utrera QF. Estudio del impacto de la actividad apícola en el Istmo de Tehuantepec, Oaxaca, México. Agric Soc Desarro 2017;14(2):187-203. 23. Ulloa CRR, Anzalo VJE, Martínez VM, Martínez GS, Lenin OJL. Generacion de un modelo para la determinación de costos de empresas productoras de miel en el estado de Nayarit. Rev Mex Agroneg 2014;35(2014):1072–1081.

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https://doi.org/10.22319/rmcp.v12i2.5811 Article

Type and characterization of rabbit farmers in Mexico's central states

Alejandra Vélez Izquierdo a José Antonio Espinosa García a* Francisco Aguilar Romero b

a

Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias (INIFAP). Centro Nacional de Investigación Disciplinaria en Fisiología y Mejoramiento Animal. Km 1 Carretera a Colón, Ajuchitlán, 76280.Colón, Querétaro, México. b

INIFAP. Centro Nacional de Investigación Disciplinaria en Salud Animal. Palo Alto, Ciudad de México, México.

*Corresppnding author: espinosa.jose@inifap.gob.mx

Abstract: This study aimed to identify and characterize the type of rabbit farmers in Mexico's central states based on social, productive, technological, economic, and efficiency factors; this information could help outline recommendations that support cuniculture practices. A survey was designed and applied to 155 rabbit production units (RPU) to obtain information about their socioeconomic, productive, and economic status; this survey also evaluated their use of facilities and technological components. Fourteen original variables were defined and helped stratify rabbit farmers through multivariate methods. The resulting groups were characterized and compared by analyzing variance following a completely randomized model for the continuous variables and a test of homogeneity for the categorical variables. Four factors accounted for 67.5 % of the total variation. Due to the factor loadings of the analyzed variables, these factors were identified as 1) productive capacity of the RPU, 2) technical capacity of the RPU, 3) farmer's capacity, and 4) technical efficiency of the RPU. Three types of producers were identified: small-scale family rabbit farmer (37 %), medium-scale family rabbit farmer (50 %), and business rabbit farmer (13 %). This typology could contribute to

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the outline of cuniculture-specific public policies to increase the efficiency and productivity of RPU in Mexico's central states. Key words: Cuniculture, Stratification, Livestock technology, Technical efficiency.

Received: 21/09/2020 Accepted:03/12/2020

Introduction Livestock production entails breeding animals for food or commercial purposes. In cuniculture, rabbits (Oryctolagus cuniculus) are used for their meat(1), which has nutritional characteristics with the potential to satisfy society's demand for meat with less fat and more protein. Rabbit's meat is lean, with a higher proportion of protein than other meats (2). In Mexico, the federal government and academic institutions have encouraged cuniculture by creating promoting centers, distributing rabbit packages, and promoting rabbit meat consumption(3). These activities have contributed to developing cuniculture practices in most Mexico's states, Michoacán, Mexico City, Puebla, and Hidalgo being the most important(4). However, rabbit is a marginally exploited species(5). In 2000, Mexico had 1'300,000 rabbits and produced 4,160 t of meat; by 2018, there were 1'407,000 rabbits and 4,483 t(6), with an average annual growth rate (AAGR) of 0.004 % from 2000 to 2018. Worldwide, Mexico ranks 13th and 19th in rabbit stock and production, respectively(6). The rabbit meat per capita consumption in the country has been estimated at 100 g(4). Countries like Portugal, France, Spain, and Italy consume two or more kilograms per person. In Mexico, cuniculture offers advantages that can be used in some regions to face the nutritional problems that affect low-income populations(5). However, cuniculture depends on agro-ecological conditions, specific production systems, and the social, economic, and technological factors of the farmers. It is crucial to study these characteristics to understand their effect on productive processes and generate information supporting decision-making that contributes to cuniculture development. There is a broad spectrum of methods and techniques to characterize and classify agricultural and livestock production systems. Among these techniques, multivariate analysis, such as the principal component analysis, factor analysis(7), and cluster analysis(8), stand out. However, few studies have evaluated the cuniculture activity in Mexico. A previous study with rabbit

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farmers from Tlaxcala reported the predominance of an extensive system, combined with characteristics from semi-intensive and business systems. Additionally, this study exposed some alternatives to improve the commercialization of rabbit meat(9). Another study interviewed consumers to identify their attribute preferences regarding the quality of rabbit meat. The authors reported that the most preferred attributes were organic, safety, freshness, and price(10). Other studies show experimental productive parameters using different diets in a rabbit farm in Hidalgo(11) and the economic outcomes with varying diets in a farm in Yucatán(12). In Mexico, no previous studies have applied multivariate methods to evaluate cuniculture activities, such as the ones used to analyze the structure of sheep production systems and the type of sheep production units in Puebla and Tlaxcala(13), or the one used to characterize cattle production systems in the XIV Tulijá-Tseltal-Chol indigenous region in Chiapas(14), or the type of apiculturists in Morelos(15). Therefore, this study aimed to identify and characterize the type of rabbit farmers in Mexico's central states based on social, productive, technological, economic, and efficiency factors; this information could assist in the outline of recommendations that support cuniculture production.

Material and methods Area of study and information source

The study was carried out in nine central states, characterized by a temperate climate and an altitude of more than 1000 masl: these states were: Mexico City, Guanajuato, Hidalgo, Jalisco, Mexico State, Morelos, Puebla, Querétaro, and Tlaxcala, which are the states with the highest number of rabbit female breeding stock(3). The information was obtained by designing and applying a survey to a significant sample of rabbit farmers. The survey included the following sections: i) socioeconomic data from the farmer and the RPU, which included the ten variables in Table 1; ii) technical -productive data from the RPU that included 12 variables shown in Table 1; iii) facilities, equipment, management variables, and technological components, integrated by the 24 variables shown in Table 2. The sample was taken from the PROGAN 2015 Register of SAGARPA (now SADER)(16). The sample size was determined following the maximum variance proportion sampling design(17): n=

N p(1 - q) æ b ( N - 1)çç è Z1-a

2

ö ÷÷ + p(1 - q) ø

Dónde: n = T amaño de la muestr a 471la población objetivo N = T amaño de

b = Pr ecisión en por centaje del 10%


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Where n is the sample size; N is the population; Z represents the confidence level;  the precision level; p the probability that the sample is representative; and q the likelihood that the sample is not representative, with a confidence level of 90% (Z2= 1.65) and a precision level of 14%. The estimated sample size n was 155 surveys, which represents 15 % of the population. Furthermore, the number of production units per state, the number of farms, and the total of average rabbits reported in the 2015 PROGAN registry shown in Table 3 were considered for sample distribution.

Table 1: Socioeconomic and technical variables of rabbit farmers in the central states of Mexico Socioeconomic

Technical-productive

Gender: male and female Experience (years of being a rabbit farmer) Age (years) Schooling (years studied) Number of financial dependents Land type: small property, ejido, communal land Other economic activities: none, salaried employee, eventual, commerce, agricultural, independent Number of jobs (wages) Family labor force (percentage)

Number of breeding does Number of bucks Number of kits Number of fattening rabbits Number of kits per breeding doe per year Number of weaned kits per year Weaning age (days) Number of dead kits per year

Contribution of cuniculture to income*

Number of discarded rabbits Number of sold kits per year Area for rabbits (m2) Area for slaughter (m2)

* < 50%, > 50%, < 100%, and only income source.

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Table 2: Facilities, equipment, management, and technological variables of rabbit farmers in Mexico's central states Area Variables 1) Sanitizing mat: yes=1, no=0; 2) Warehouse: yes=1, no=0; 3) Facilities and Water pump: yes=1, no=0; 4) Scale: yes=1, no=0; 5) Vehicle: equipment yes=1, no=0; and 6) Refrigerator: yes=1, no=0. 1) Technical records: yes=1, no=0; 2) Financial records: yes=1, no=0; 3) Rabbit batching: 0 no batching, 1 by age and sex, 2 by age, Farm management sex, and productive stage; 4) Practices discarding of unproductive breeding does: yes=1, no=0; 5) Practice manure management: yes=1, no=0; and 6) Processes meat: yes=1, no=0. 1) Uses pure rabbit breeds: yes=1, no=0; 2) Uses registered studs: yes=1, no=0: 3) Evaluates bucks: yes=1, no=0; 4) Selects does: Reproduction and yes=1, no=0; 4) Selects bucks: yes=1, no=0; 5) Reproductive Genetics method: 1 Free breeding, 2 Controlled breeding; and 6) Performs gestation diagnosis: yes=1, no=0. 1) Commercial feed: yes=1, no=0; 2) Prepares feed in the Feed: production unit: yes=1, no=0. 1) Internal deworming: yes=1, no=0; 2) External deworming: Sanitation yes=1, no=0. Technical consulting 1) Technical consulting: yes=1, no=0. Use of facilities, equipment, and 1) Sum of the positive data for the facilities, equipment, and technological technological component variables with a maximum value of 26. components Table 3: Number of production units, rabbitry structure, average surface area, and surveys applied to rabbit breeders in central Mexico CM GTO HGO JAL MEX MOR PUE QRO TLX Farms 31 11 700 25 180 12 53 21 19 Breeding does 30 257 212 59 45 44 66 24 67 Kits 76 13 77 69 80 85 124 34 87 Fattening 72 13 62 69 58 95 67 58 164 Replacement 10 1 16 7 7 4 9 5 7 Bucks 5 96 17 8 7 4 6 3 9 Total 192 380 384 212 196 334 272 233 123 2 Surface area, m 0.03 4.27 0.66 2.4 9.54 0.42 6.79 2.58 4.57 Surveys 20 11 32 18 25 9 20 12 8 Source: Elaborated with data from the 2015 PROGAN Registry(16). CM= Mexico City; GTO= Guanajuato; HGO= Hidalgo; JAL= Jalisco; MEX= Mexico State; MOR= Morelos; PUE= Puebla; QRO= Querétaro; TLX= Tlaxcala.

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Information analysis

An exploratory analysis was carried out with basic and correlation statistics of the 46 variables considered for the study. Farmers were stratified with a multivariate analysis performed using factor analysis by principal components and hierarchical clusters. For the first analysis, 20 quantitative variables with positive correlation (P<0.05) were selected. Additionally, the quality, availability, and relevance criteria proposed by other studies were also applied(18,19). The principal components with eigenvalues greater than one were rotated using the Varimax method to reduce the number of variables by building factors that explain the more significant variance in the global analysis(18,20). The hierarchical cluster analysis was used to graphically identify the number of rabbit farmer clusters, based on the Ward algorithm(21,22) and the squared Euclidean distance(21,23), to recognize the cut-off point in the dendrogram (Figure 1). The factors obtained in the factor analysis by principal components were the variables employed and standardized with the mean and standard deviation. The statistical analyses were performed with the statistical program JMP® 9.0 (SAS Institute). The means and standard deviations of the quantitative variables were calculated to characterize and compare the resulting clusters of rabbit farmers; additionally, an analysis of variance was carried out following a completely randomized model to detect differences between groups. As for the qualitative variables, it was calculated their frequencies and carried out a homogeneity test to identify differences between the clusters of rabbit farmers.

Results Type of rabbit farmers in Mexico's central states

Based on the correlation matrix of the 46 variables mentioned in Tables 1 and 2, the 20 quantitative variables that had the highest correlations were selected and used in the multivariate analysis. Four factors were extracted from the factor analysis. These factors showed eigenvalues greater than one and explain 67.5 % of the total variation of the original variables. The factor loads that each variable has in the extracted factor with values greater than 0.50 allowed identifying the variables associated with said factor and thus facilitated an empirical interpretation and the assignment of a physical name.

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Factor one is highly correlated with the surface area for the production and number of breeding does, sold rabbits, studs, weaned kits, and dead animals (Table 4). This factor was named productive capacity of the rabbit production unit and explained 29.3 % of the variance of the 14 variables. Thus, Factor 1 has the most influence on the analysis and better explains the differences between the clusters of rabbit farmers and their production scale. Factor 2 is highly correlated with the labor force in the farm, the surface area for rabbit slaughter, and the use of facilities, equipment, and technological innovations (Table 4). This factor was named technical capacity of the rabbit production unit and explained 14.7 % of the variance. Factor 3 is highly correlated with the social characteristics of the rabbit farmer, such as age, schooling, and years of experience in rabbit production. These variables define the production unit's ability to produce; therefore, this factor was named capabilities of the rabbit farmer and explained 11.6 % of the variance. Finally, Factor 4 has a high correlation with the number of kits produced per breeding doe per year, which evaluates the farm's productivity. Thus, this factor was named technical efficiency of the rabbit production unit and explained 10.6 % of the variation.

Table 4: Factor loadings of the variables that integrate the factors defined for the rabbit breeders of Mexico's central states Variable Factor 1 Factor 2 Factor 3 Factor 4 Number of breeding does 0.035692 -0.032912 0.916667 0.206498 Number of sold kits/year -0.041729 0.462372 0.83149 0.228365 Number of bucks 0.167483 0.075937 -0.145468 0.816544 Number of weaned kits/year -0.062843 0.462191 0.799396 0.258606 Number of dead animals/year 0.71444 -0.046216 0.105208 0.287652 Area for rabbits -0.008589 -0.087412 0.642098 0.181289 Use of facilities, equipment, and technological components 0.343973 0.682402 -0.013021 -0.048417 Labor force in the PU -0.159698 0.670922 0.062029 0.219434 Schooling 0.171105 0.44837 0.605979 -0.072184 Area for slaughter 0.23495 0.513992 -0.125401 0.119383 Rabbit farmer's age 0.023885 -0.074193 0.831125 -0.084211 Years of experience in rabbit farming 0.141377 0.256117 0.69565 -0.003725 Number of kits per breeding doe/year 0.089981 0.098896 -0.05581 0.927394 Percentage of family labor force -0.298046 0.60223 -0.176492 0.040382 Explained variance (%) 29.3 14.7 12.9 10.6 Values in bold represent the factor loadings of the variables that integrate each factor.

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The information of the previously mentioned factors was included in the cluster analysis to identify the clusters of rabbit farmers by hierarchical analysis. Three types of rabbit breeders were graphically identified (Figure 1). The number of rabbit farmers in each group is G1=57 (37 %), G2=78 (50 %), and G3=20 (13 %). Figure 1: Dendrogram of rabbit farmers in Mexico's central states

Each group was assigned a name based on the size of the production unit, the percentage of family labor force, and the use of facilities, equipment, and technological components (Table 5). Group 1 is integrated by producers with an average of 24 breeding does, with farms in which 91.5 % of the labor force are family members and use 60 % of the 24 variables related to facilities, equipment, and technological components. Thus, this group includes small family rabbit farmers (G1) with a medium technical level. Group 2 (G2) comprises producers with an average of 52 breeding does, with farms in which 87 % of the labor force corresponds to family members and use 67 % of the facilities, equipment, and technological components; thus, G2 includes medium-scale family rabbit farmers. Group 3 (G3) is integrated by producers with 55 breeding does, 40 % of the labor force is hired, and they use 88 % of the facilities, equipment, and technological components (of the 22 shown in Table 2); thus, G3 producers are considered business rabbit farmers.

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Table 5: Mean  standard error of the variables used to characterize the rabbit farmers in Mexico's central states Smallscale MediumBusiness family scale family Factors Variables rabbit rabbit rabbit farmer (G3) farmer farmer (G2) (G1) Number of breeding does 24.0±4.1b 51.5±3.5a 54.9±28.9a Number of sold kits/year 664.7±145c 1541.7±124b 2949.2±245a 1. Productive capacity

2. Technical capacity

3. Rabbit farmer capacities 4. Technical efficiency ab

Number of bucks

2.7±0.5b

6.1±0.4a

6.1±0.9a

Number weaned kits/year Number of dead animals Area for rabbits Use of facilities, equipment, and technological components Labor force Area for slaughter Percentage of family labor force Schooling Age Years of experience as a rabbit farmer Number of kits per breeding doe/year

571.3±132c 1,353.1±113b 2,596.8±223a 93.4±23.8b 188.5±20.3a 252.4±40.1a 55.3±11.8b 124.3±10.1a 108.4±19.9ab 13.1±0.6b

14.8±0.5b

19.4±0.9a

1.5±0.1b 1.1±1.1b

1.28±0.1b 4.09±1.0ab

3.3±0.2a 8.8±1.9a

91.5±4.1a

86.5±3.6a

62.1±7.0b

9.1±3.7b 54.3±9.5a

13.4±0.4a 39.3±11.3c

13.9±0.8a 46.5±13.5b

9.3±0.8a

6.2±0.7b

12.0±1.5a

29.5±1.7b

30.36±1.4b

52.0±2.8a

Different letters indicate differences based on an ANOVA and Tukey test (P0.05).

Characterization by type of rabbit farmer

After defining the type of rabbit farmers, it was proceeded to characterize them based on the previously defined factors to identify the specific characteristics of each type of rabbit production unit, as previously carried out for other production systems(15,18,19). Of the six variables included in Factor 1, Productive capacity of the RPU, two showed statistical differences (P<0.01) between the three types of producers. As for the remaining four variables, at least one of the groups was significantly different from the other two (P<0.05)

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(Table 5). G1 producers show the lowest number of breeding does and studs and the smallest area for rabbit production. These data are directly related to the production scale of the RPU, reflected on the average of weaned and sold rabbits. The number of weaned kits per year differed significantly between the three groups (F=31.7; gl=2, 152; P<0.01). The average value of G3 was significantly higher than the value of G2 (P<0.05), with a difference of 1,243 kits. Similarly, the value of G2 was significantly higher than the average value of G1 (P<0.05), with a difference of 782 rabbits (Table 5). Regarding the number of dead animals, it was observed significant differences (F=7.5; gl=2, 152; P<0.01) between groups. The average values of G2 and G3 were significantly higher than G1 (P<0.05). The area for rabbits showed the same behavior (F=10.8; gl=2, 152; P<0.01). Rabbit farmers in G2 and G3 had a significantly higher number of square meters than those in G1 (P<0.05). The number of breeding does significantly differ between groups (F=15.1; gl=2, 152; P<0.01). The average values of G2 and G3 were significantly higher than G1 (P<0.05) (Table 5), with the double amount of breeding does. The number of rabbits sold per year differed significantly between the three groups (F=30.8; gl=2, 152; P<0.01); the average value of G3 was significantly higher than the value of G2 (P<0.05), with a difference of 1,308 rabbits. Similarly, the value of G2 was significantly higher than the average value of G1 (P<0.05), with a difference of 877 rabbits (Table 5). As for the number of bucks, it was observed significant differences between groups (F=13.1; gl=2, 152; P<0.01); the average values of G2 and G3 were significantly higher than G1 (P<0.05) (Table 5). Regarding Factor 2, Technical capacity of the RPU, it was observed significant differences between groups in the use of facilities, equipment, and technology (F=16.5; gl=2, 152; P<0.01). The average value of G3 was significantly higher than the value of G1 and G2(P<0.05); there were no differences between these two groups (P<0.05) (Table 5). After analyzing the facilities and equipment included in this variable, it was found that two of the six explored concepts behaved differently between the groups; 70 % of the producers in G3, 31 % of G2, and 17.5 % of G1 use sanitizing mats (Xi2=19.1; n=155; P<0.01). Similar behavior was observed regarding storage; 60 % of the rabbit farmers in G3 and less than 26 % of those in G1 and G2 had storage (Xi2=14.5; n=155; P<0.01) (Figure 2).

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Figure 2: Use of facilities, equipment, and technological components by rabbit farmers in Mexico's central states.

* Indicates statistical difference Prob > Chi-square 0.05. ** Indicates statistical difference Prob > Chi-square 0.01.

As for the technological components used by rabbit farmers, it was observed that 8 of the 18 analyzed activities behaved differently between groups. These components were: financial records, used by 65, 42, and 26 % of producers in G3, G2, and G1, respectively (Xi2=9.9; n=155; P<0.01); rabbit batching, applied by 95, 74, and 65 % of producers in G3, G2, and G1, respectively (Xi2=21.4; n=155; P<0.01); pure breeds, used by 85, 68, and 56 % of farmers in G3, G2, and G1 (Xi2=5.8; n=155; P<0.05); registered studs, used by 40, 26, and 9 % of producers in G3, G2, and G1, respectively (Xi2=10.4; n=155; P<0.01); stud evaluation, done by 45, 36, and 14 % of farmers in G3, G2, and G1 (Xi2=10.5; n=155; P<0.01); internal deworming, carried out by 70, 54, and 39 % of farmers in G3, G2, and G1, respectively (Xi2=7.3; n=155; P<0.02); external deworming, carried out by 90, 64, and 53 % of producers in G3, G2, and G1 (Xi2=8.9; n=155; P<0.01); and technical consulting, received by 60, 38, and 26 % of producers in G3, G2, and G1 (Xi2=7.4; n=155; P<0.02) (Figure 2).

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Significant differences were also observed between groups in the total labor force variable (F=43; gl=2, 152; P<0.01). The average value of G3 was significantly higher than the value of G1 and G2 (P<0.05), and there were no differences between these two last groups (P<0.05) (Table 5). As for the area for slaughter, there were significant differences between the three groups (F=6.2; gl=2, 152; P<0.01). The area of G3 was greater than that of G2 (P<0.05), which was higher than the area of G1 (P<0.05). Furthermore, it was observed significant differences in family labor force (F=6.6; gl=2, 152; P<0.01); the average value of G3 was significantly lower than the values of G1 and G2 (P<0.05), and there were no differences between these last two groups (P<0.05) (Table 5). Regarding the variables included in Factor 3, rabbit farmer capacities, it was observed significant differences between groups (F=25.5; gl=2, 152; P<0.01). The average value of G1 was significantly lower than the value of G2 and G3 (P<0.05), and there were no differences between these two groups (P>0.05) (Table 5). After analyzing the age variable (F=30.7; gl=2, 152; P<0.01), it was observed that producers in G1 were significantly older than those in G3 (P<0.05); moreover, G3 producers are older than those in G2 (P<0.05), more schooling and years of experience. Furthermore, it was observed significant differences (F=7.7; gl=2, 152; P<0.01) regarding the year of experience. Producers in G2 had significantly fewer years of experience than those in G1 and G3 (P<0.05), and there were no significant differences between G1 and G3. Factor 4, Technical efficiency of the RPU, only includes one variable, production of kits per breeding doe per year, which was significantly different between groups (F=26.3; gl=2, 152; P>0.01). The average value of G3 was significantly higher than the value of G1 and G2 (P<0.05), and there were no differences between these two last groups.

Discussion The four factors obtained from the factor analysis and identified as 1) Productive capacity of the RPU, 2) Technical capacity of the RPU, 3) Rabbit farmer capacities, and 4) Technical efficiency of the RPU explain 67.5% of the variation observed between the production units included in this study. This value is considered acceptable because, in social sciences, it is possible to consider solutions that represent 60 % of the total variance(24). Additionally, this value is similar to that previously reported in Argentina (68 %) for the typification of farmers(25). Therefore, these results can be considered reliable for inference.

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The three categories used to classify rabbit farmers (small-scale family rabbit farmers, medium-scale family rabbit farmers, and business rabbit farmers), is pertinent, based on the participation of the family members in farm-related activities and the farm size(26). However, this classification differs from that reported for rabbit farmers in the state of Tlaxcala. This classification considers three production systems: backyard or extensive, semi-intensive, and intensive or businesses; the extensive rabbit production system predominate(9). Three of the variables included in Factor 1 (Productive capacity of the RPU) are related to the size of the production unit; the remaining three variables are associated with rabbit production. Although these variables have not been previously studied, previous reports mention that the productive capacity of a production unit is mainly determined by its inventory(27), which includes machinery, equipment, constructions, and breeding female specimens. In the case of rabbit farming, this inventory is mainly constituted by breeding does and bucks. Thus, the amount of rabbit meat produced on a farm depends on the number of breeding does. This has been previously reported on other livestock species, such as dualpurpose cattle in the tropical region of Mexico(27) or beekeeping in Switzerland(28), in which the size of the production unit, measured as the number of colonies, was the factor that most affected honey production. Other factors affecting production are the technological activities and components incorporated into the production unit(29). In rabbit farming, these innovations can include facilities, equipment, and technological components. The latter has been previously evaluated due to their effects on rabbit production. Rabbit batching has been studied by grouping, by age, litters of up to eight kits, which reduces mortality(30). These results have been acknowledged by the rabbit farmers in the central states of Mexico, as demonstrated by the percentage of batching use in the three groups of farmers (Figure 2). Additionally, similar results were observed regarding use of technical records in the producers of Tlaxcala (74 %)(9) and the rabbit farmers in the central states of Mexico. The technological practices related to nutrition and reproduction are among the most evaluated in rabbit farming; this includes the use of commercial feed by itself or with diets added with local forage in the fattening of rabbits. No significant differences have been observed in productive parameters(11,31). This is why most of the producers in this study use commercial feed in their diets; this has also been reported for rabbit producers sin Tlaxcala. Together, these reports indicate that the basis of rabbit diets is commercial feed (9). The producers in G3 use pure breeds, although there is a technological margin because farmers are still not using registered bucks or evaluating them, especially farmers in G1. This situation matches the practices reported for the producers in Tlaxcala, where only 9.5 % selects breeding does(9).

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It seems, no previous studies have quantified the presence of diseases and pests in rabbit farms. These studies only report the presence of viruses(10), although they do mention that the most frequent problems are pneumonia, mange, and enteritis. Therefore, 76.2 % of the producers in Tlaxcala carry out external deworming, similar to what was observed in the rabbit producers in central Mexico, especially those in G3, which indicates that this practice has already been incorporated into their production process. The rabbit farmer and their family constitute the human capital of the RPU; this is considered a promoting factor for financial growth and development. The average values of the variables included in Factor 3 (Rabbit farmer capacities) were different for the three groups. The average age of the rabbit farmers in the three groups indicates that they are adults. Their age also influences the use and adoption of innovations; it is also an important factor to consider in the administrative and technical management of the production unit(15). Education level of rabbit farmers in G2 and G3 is upper secondary education (13 yr); farmers in G1 have secondary education (9 yr). These results are similar to the ones observed in previous studies(15). Still, they differ from the national situation, which indicates that 78.5 % of the rural population has no formal education, incomplete elementary school, or only elementary school(32). This situation stimulates the development of activities oriented to strengthen the production capacities of rabbit farmers in the three groups. As for experience in rabbit farming, farmers in G3 had on average 12 yr of experience, those in G1 had nine years, and farmers in G2 had six years. G2 farmers are the youngest, with fewer years of experience and more years in education, which shows that rabbit farming is considered as an activity with potential(3,4). Although no previous studies have demonstrated the importance of social variables, such as age, schooling, or experience in the use of innovation and rabbit farming, various authors have reported(8,15,18) the importance of these variables as elements that favor or prevent the use of innovations. The variables associated with Factor 4, Technical efficiency of the RPU, indicate both the productive and the technical capacities. The results reported for G1 and G2 are below the average values, 36 kits per breeding doe per year, reported for the rabbit production units in temperate regions(33). These results represent an opportunity for improvement if more technological components are incorporated, such as gestation diagnosis, registered bucks, buck evaluation, rabbit batching, and implementation of financial records.

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Conclusions and implications Three types of rabbit farmers were identified in Mexico's central states: small-scale family rabbit farmers (37 %), medium-scale family rabbit farmers (50 %), and business rabbit farmers (13 %). Farmers were classified and stratified based on the production unit's productive capacity, technical capacity, and technical efficiency, in addition to the farmer's capacity. The productive capacity of small-scale family rabbit farmers is lower than that of the other two groups because the number of breeding does is on average half of what the other groups have. However, their technical capacity and efficiency are similar to that of the medium-scale family rabbit farmers, which is less than observed in business farmers. Similarly, the percentage of the family labor force employed in the production unit predominates in the first two groups. These results will help propose recommendations to improve the productive capacity and the development of small-scale family rabbit farmers in central Mexico. Literature cited: 1. Arrechedora I. Actividades pecuarias: Producción y actividades en México. https://www.lifeder.com/actividades-pecuarias/. Consultado 14 Sep, 2020. 2. Savino L. La carne de conejo, una buena opción para adquirir hábitos alimenticios saludables. Suena a Campo. Disponible: http://suenaacampo.com/2019/10/05/. Consultado 14 Sep, 2020. 3. SAGARPA-SENASICA. Manual de buenas prácticas de producción de carne de conejo. 1ª ed. Ciudad de México. 2015. 4. Comité Sistema Producto Cunícula. Plan rector sistema producto cunícola del Distrito Federal, actualizado a 2012. Ciudad de México. 5. Jaramillo VJL, Vargas LS, Guerrero RJ de D. Preferencias de consumidores y disponibilidad a pagar por atributos de calidad en carne de conejo orgánico. Rev Mex Cienc Pecu 2015;6(1):221-232. 6. FAOSTAT. Ganadería. Organización de las Naciones Unidas para la Alimentación y la Agricultura. Disponible: http://www.fao.org/faostat/es/#data/QC. Consultado 10 Sep, 2020. 7. Duvernoy I. Use of a land cover model to identify farm types in the Misiones agrarian frontier (Argentina). Agric Syst 2000;64(3):137-149.

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8. Köbrich C, Rehman T, Khan M. Typification of farming systems for constructing representative farm models: two illustrations of the application of multivariate analyses in Chile and Pakistan. Agric Syst 2003;(76):141-157. 9. Olivares PR, Gómez CMA, Schwentesius RR, Carrera ChB. Alternativas a la producción y mercadeo para la carne de conejo en Tlaxcala, México. Región y Sociedad 2009;21(46):191-207. 10. Reynoso UE, Bautista GLG, Martínez CJS, Romero NC, García RVG, Aguado AGL, et al. Análisis de la presencia de Rotavirus en conejos del Estado de México. Rev Mex Cienc Pecu 2019;10(2):511-521. 11. Pérez MK, García VS, Soto SS, Zepeda BA, Ayala MM. Parámetros productivos de conejos alimentados con diferentes partes de la planta Tithonia tubaeformis. Abanico Veterinario 2018;8(2):108-114. 12. Peniche RJA, Rejón ÁMJ, Valencia HER, Pech MVC. Análisis de rentabilidad de dos alternativas de alimentación no convencionales en la producción de conejos en el municipio de Tixpehual, Yucatán, México. Rev Mex Agroneg 2010;XIV(27):411-418. 13. Vázquez MI, Jaramillo VJ, Bustamante GA, Vargas LS, Calderón SF, Torres HG, Pittroff, W. Estructura y tipología de las unidades de producción ovinas en el centro de México. ASyD 2018;(15):85-97. 14. Velázquez AJA, Raúl Perezgrovas GR. Caracterización de sistemas productivos de ganado bovino en la región indígena XIV Tulijá-Tseltal-Chol, Chiapas, México. Agrociencia 2017;(51):285-297. 15. Vélez IA, Espinosa GJA, Amaro GR, Arechavaleta VME. Tipología y caracterización de apicultores del estado de Morelos, México. Rev Mex Cienc Pecu 2016;7(4):507-524. 16.

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17. Infante GS, Zarate de LGP. Métodos estadísticos: un enfoque interdisciplinario. Colegio de Postgraduados. Mundi-Prensa España. 1990. 18. Fachini C, Firetti R, Cardoso DeOE, Assiz DeCA. Perfil da apicultura em Capão Bonito, estado de São Paulo: aplicação da análise multivariada. Rev Econom Agr 2010;57(1):49-60. 19. Gelasakis AI, Valergakis GE, Arsenos G, Banos G. Description and typology of intensive Chios dairy sheep farms in Greece. J Dairy Sci 2012;95(6):3070-3079.

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20. Castaldo A, Acero R, Perea J, Martos J, Valerio D, Pami J, et al. Tipología de los sistemas de producción de engorde bovino en la Pampa Argentina. Arch Zootec 2006;55(210):183-193. 21. García CH, Calle LM. Consideraciones metodológicas para la tipificación de sistemas de producción bovina a partir de fuentes secundarias. Rev Corpoica 2013;2(2):6-15. 22. Hair JF. Multivariate data analysis. 7th ed. Upper Saddle River, NJ, USA: Pearson Prentice Hall; 2009. 23. Cuevas RV, Loaiza MA, Espinosa GJA, Vélez IA, Montoya FMD. Tipología de las explotaciones ganaderas de bovinos doble propósito en Sinaloa, México. Rev Mex Cienc Pecu 2016;7(1):69-83. 24. Valerio D, García A, Acero R, Castaldo A, Perea J, Martos J. Metodología para la caracterización y tipificación de sistemas ganaderos. Documentos de Trabajo Producción Animal y Gestión. Córdoba (España): Universidad de Córdoba. http://www.uco.es/zootecnia-ygestion/img/pictorex/14_19_10_sistemas2.pdf , Consultado 20 Ago, 2020. 25. Coronel DeRM, Ortuño PS. Tipificación de los sistemas productivos agropecuarios en el área de riego de Santiago del Estero, Argentina. Problemas del desarrollo. Rev Latinoam Econom 2005;36(140):63-88. 26. Schejtman A. Economía campesina: lógica interna, articulación y persistencia. Rev de la Cepal 1980;11(8):121-141. 27. Rangel RJ, Espinosa GJA, de Pablos C, Rivas J, Perea J, Angón E, García MA. Is the increase of scale in the tropics a pathway to smallholders? Dimension and ecological zone effect on the mixed crop-livestock farms. Spanish J Agr Res 2017;15(2):1-22. 28. Masuko MB. Socioeconomic analysis of beekeeping in Swaziland: A case study of the Manzini Region, Swaziland. J Develop Agr Econom 2013;5(6):236-241. 29. Kalenatic D, González L, López CA, Arias LH. El sistema de gestión tecnológica como parte del sistema logístico en la era del conocimiento. Cuadernos de administración 2009;22(39):257-286. 30. González RP, Negretti P, Finzi A. Adopción de gazapos a diferentes tamaños de camada en un sistema alternativo de producción de conejos. Agrociencia 2010;44(3):275-282. 31. Bonilla VCE, Delgado ALA, Mora LRE, Herrera AAM. Efecto de niveles crecientes de follaje de Arachis pintoi en dietas para conejos sobre el desempeño zootécnico en fase de crecimiento-engorde. Rev Científica FCV-LUZ 2016; XXVI(1):41-48.

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32. FAO-SAGARPA. Diagnóstico del sector rural y pesquero de México 2012. Disponible: https://www.agricultura.gob.mx/sites/default/files/sagarpa/document/2019/01/28/1608/ 01022019-1-diagnostico-del-sector-rural-y-pesquero.pdf. Consultado 27 Nov, 2020. 33. Cruz BLE, Ramírez VS, Vázquez GM del C, Zapata CCC. Reproducción de conejos bajo condiciones tropicales, efectos negativos y posibles soluciones. Ciencia UAT 2018; 13(1):135-145.

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https://doi.org/10.22319/rmcp.v12i2.5542 Article

Intracellular survival of Mycobacterium bovis strains with high and low frequency in cattle populations in a bovine macrophage model

Alejandro Nava-Vargas a Feliciano Milián-Suazo b Germinal Jorge Cantó-Alarcón b José A. Gutiérrez-Pabello c*

a

Universidad Autónoma de Querétaro. Facultad de Ciencias Naturales, Doctorado en Ciencias Biológicas, Querétaro, México.

b

Universidad Autónoma de Querétaro. Facultad de Ciencias Naturales, Querétaro, México.

c

Universidad Nacional Autónoma de México. Facultad de Medicina Veterinaria y Zootecnia, Ciudad Universitaria, Av. Universidad #3000, Colonia, C.U., Coyoacán, 04510, Ciudad de México, México.

* Corresponding author: jagp@unam.mx

Abstract: Bovine tuberculosis is a disease caused by Mycobacterium bovis that affects cattle and other species, including humans. Mycobacterium bovis resides mainly in macrophages, so bacilli survival within macrophages is related to virulence. Isolation and strain identification are important for disease control. However, little is known about virulence of the circulating strains in cattle populations. Therefore, the aim of this study was to compare the intracellular survival of Mycobacterium bovis strains with high and low frequency genotypes in cattle in Mexico. Four high frequency genotypes and four low frequency genotypes were identified and subjected to intracellular survival assays in bovine macrophages. Results showed that the phagocytosis proportion was approximately 63 % for all strains. There were no significant differences in the average Colony Forming Units (CFUs) in phagocytosis and survival between the high and low frequency groups; however, when the CFU average of phagocytosis was compared with the survival, 487


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significant differences were found in both groups. In intracellular growth, a significant difference was observed between low and high frequency strains, and between low frequency strains. Finally, the intracellular growth average of the groups was analyzed showing no significant difference. These results suggest that the frequency of the genotype in cattle population is not related to the intracellular survival and the virulence of the M. bovis strains. Key words: Mycobacterium bovis, Bovine tuberculosis, Macrophages.

Received: 19/10/2019 Accepted: 11/08/2020

Introduction

Bovine tuberculosis (TBb) is a chronic bacterial disease caused by Mycobacterium bovis, a slow-growing obligate intracellular pathogenic bacterium, characterized by producing granulomas in different organs, especially lungs and lymph nodes of different animal species and humans(1–4). In cattle, this disease is characterized by formation of granulomas (i.e. tubers) in any body tissue, although lesions are more frequent in lymph nodes [medial retropharyngeal (29.4 %), mediastinal (28.2 %), tracheobronchial (18.0 %), mesenteric (2.9 %), parotid (2.4 %) and the caudal cervical (2.4 %)] and a lower percentage in lungs (8.0 %)(5–9). Bovine tuberculosis affects livestock causing a reduction of about 10 to 20 % of milk and meat production, and limiting markets for animals and their products. So the control of this disease becomes a priority for the national livestock industry, to develop the productive potential of cattle, and allow exportation(10,11). In Mexico, as in many other countries of the world, there is a national program for bovine tuberculosis control and eradication. In beef cattle this program has reduced the prevalence to <0.5% in 85% of the national territory; however, in dairy-cattle areas, where the prevalence is high (≈16%), the program has not been successful(12,13).

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The role of bacterial genetic variability in the infection’s outcome remains uncertain. Until the early 1990s, when DNA fingerprints were introduced, it was believed that the M. tuberculosis complex was a group of highly genetically conserved bacteria, with limited phenotypic differences that influenced pathogenesis. However, epidemiological data suggest that differences in transmissibility and virulence between strains are related to their genotypes(14–18). M. bovis is an intracellular pathogen that mainly resides in macrophages. Therefore, in vitro macrophage models can be used to determine intracellular survival, which in turn is associated with the virulence of M. bovis strains. For example, Gutiérrez-Pabello and Adams(19) demonstrated that virulent strains survive longer than avirulent strains in bovine macrophages. The in vitro model has also been validated for evaluation of the pathogenicity or virulence of mycobacteria with inactivated genes, or for the identification of genes associated with virulence(20). In addition, there are reports of cattle naturally resistant to TBb. According to Qureshi et al(21), the classification criteria of resistant animals is based on the ability of macrophages to allow the growth of the avirulent M. bovis BCG strain (Calmette-Guérin Bacillus) in vitro; when this growth is higher than 65 %, they are considered susceptible, and when the bacterial growth is lower than 65 %, they are considered resistant. In addition, these authors showed that macrophages from resistant cattle were significantly superior in the control of intracellular growth of other pathogens such as B. abortus and Salmonella dublin, when compared with macrophages of susceptible animals. These studies conclude that macrophages of resistant and susceptible animals differ in the intracellular control of M. bovis multiplication(19). Therefore, the use of the in vitro assessment of bacterial intracellular survival in macrophages from a resistant donor may be considered as a correlate of bacterial virulence. The genotyping of M. bovis for phylogenetic analysis has been carried out by different methods, Restriction fragment length polymorphisms (RFLP), random amplification of polymorphic DNA - Polymerase Chain Reaction (RAPD-PCR), spoligotyping and interspersed mycobacterial repetitive units - Variable number of tandem repeats (MIRUVNTR). These methods have demonstrated of a great diversity of strains, with low and high frecuency genotypes(22–24). The random amplified polymorphic DNA polymerase chain reaction (RAPD-PCR) method provides results comparable to those of RFLP, but it avoids use of hazardous radioactive materials, is less expensive, and easier and quicker to perform. For example, whereas RFLP may require weeks for results, RAPDPCR can be completed in <5 to 8 hours. In comparison with targeted PCR, RAPD-PCR does not require knowledge of the target sequence to develop primers. Single-stranded, 10-nucleotide oligomers of arbitrary sequence are used individually to perform the PCR(25). With the advent of molecular epidemiology, faster and more reliable methods for bTB diagnosis have been developed,

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which provide information about the genetic structure to establish relationship among strains. The most popular method for M. bovis genotyping is spoligotyping. This method has proved useful in a large number of studies with a wide range of objectives and animal species. In comparison with other methods, it is easy to perform, requires very small amounts of DNA, it is robust and highly reproducible, and it can be applied to clinical specimens. More than that, spoligotyping is very useful in strains of M. bovis with a few copies of the IS6110 insertion element, as it is the case in strains from cattle(22). MIRUVNTR is a molecular tool based on the amplification by PCR of 41 different loci of the Mycobacterium DNA sequence, which function as molecular markers obtaining fast, objective, and high resolution monitoring procedures in outbreaks or epidemiological emergencies(23). In a previous study carried out by our group, genotyping of M. bovis strains of cattle from different regions of Mexico, demonstrated the presence of genotypes (spoligotypes and MIRU-VNTR) of high and low frequency(22,23,26). These findings led to pose the following questions: Are low frequency strains less virulent than high frequency strains? And if so, is this the reason for the low frequency of some spoligotypes in the population? Isolation and strain identification are important for disease control. However, little is known about virulence of the circulating strains in cattle populations. Therefore, the aim of this study was to compare the intracellular survival of Mycobacterium bovis strains with high and low frequency of genotypes in Mexican cattle, in macrophages from naturally resistant animals.

Material and methods This project was approved by the Bioethics Committee of the Natural Sciences Department of the Autonomous University of Queretaro under registry number 47FCN2016.

Molecular characterization of strains

M. bovis strains, previously characterized genetically by spoligotyping and MIRUVNTR, were used(19,22). For the purpose of this study, four strains with a genotype of high frequency and four with genotype of low frequency were selected from a set of strains obtained from cattle in different regions of Mexico (Table 1). High-frequency spoligotypes were first selected and their frequent MIRU-VNTR´s-type were subsequently identified.

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Table 1: Spoligotype frequency and VNTR-type of the M. bovis strains used in the Code SB SB0673 SB0971 SB0669 SB0140 SB1495 SB1118 SB0290 SB0131

VNTR 023404625334 433363325242 002060703320 242352524244 403403625133 452300824234 403363525142 252252323224

study State of origin Coahuila Aguascalientes State of Mexico Hidalgo Coahuila State of Mexico Queretaro Hidalgo

ID 777 833 351 559 776 694 301 906

Frequency 155 70 124 71 1 1 1 1

High frequency

Low frequency

Inoculum preparation Experimental M. bovis strains were replicated in Middlebrook 7H9 medium (BBL™ Middlebrook 7H9 Broth Base, Becton, Dickinson Mycrobiology Systems, Cockeysville, MD USA) with OADC enrichment and 0.5 g/l of Tween 80 (Sigma Chemical CO, St. Louis, MO USA); then, incubated at 37 °C under constant stirring for 12 d. For analysis, bacteria were preserved in 1 ml aliquots in RPMI medium (RPMI Medium 1640 Invitrogen™ Corporation Grand Island, NY USA), supplemented with 0.1 mM of essential amino acids, 1 mM of sodium pyruvate, 2 mM of L-glutamine and 20 mM of sodium bicarbonate NaHCO3 (CRPMI), plus 15% of fetal bovine serum (Gibco ™ Invitrogen Corporation Grand Island NY USA) at -70 °C. For each bacterial inoculum, colony forming units (CFU) were determined by serial decuple dilutions seeded in Middlebrook 7H10 agar plates (Bacto® Mycobacteria 7H11 Agar, Difco Laboratories, Detroit MI USA) with OADC enrichment (BBL™ Middlebrook OADC Enrichment, Becton, Dickinson and Company, Sparks, MD USA).

Macrophages derived from bovine monocytes (MDMB) Peripheral venous blood was collected from the jugular vein of a healthy bovine, previously identified as resistant(27), in syringes with acid-citrate-dextrose (ACD) solution. Macrophages were obtained from peripheral blood mononuclear cells (PBMC). PBMC were isolated by gradient centrifugation on a Histopaque -1077 suspension (Sigma-Aldrich, San Luis, USA). Cell pellets were washed and suspended in CRPMI. Cells were grown in Ultra Low Adhesion Plates (Corning® Costar®, USA) at 37 °C with 5% CO2. After 2 h, non-adherent cells were removed and adherent monocytes were cultured in CRPMI, plus 12 % of autologous serum for 12 d to allow their differentiation into macrophages(28,29).

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Microbicidal assay Bactericidal assays were carried out according to Qureshi et al(21), with some modifications. Bactericidal assays have been useful for classification of cattle resistant or susceptible phenotypes using the avirulent strain M. bovis BCG using 65 % of bacterial replication as a cut-off point. Macrophage monolayers in cell culture in Terasaki plates were infected with M. bovis at a multiplicity of infection (MOI) of 10:1. Subsequently, centrifuged at 200 xg for 10 min and incubated at 37 °C with 5% CO2 for 4 h in a humidified atmosphere to allow phagocytosis. Cells were then washed five times with fresh CRPMI, plus 12 % of autologous serum to remove extracellular bacteria, and incubated again at 37 °C. This was considered as time 0 h. Cells were lysed for analysis at 0 and at 24 h (time 1) after infection. Bacterial phagocytosis was calculated by measuring the serial dilutions of live intracellular bacteria released from macrophages after treatment with 0.5% Tween 20. Bacterial growth was calculated as the ratio between the total number of intracellular bacteria at the end, and the total number of bacteria at the beginning of the assay, expressed as a proportion. Results are the average of three independent experiments, each one with three internal repetitions. Statistical analyzes were carried out with the nonparametric Friedman test and Dunn's multiple comparisons test with 10% significance and the student’s t test to compare UFCs with 5% significance.

Results

The phagocytosis proportion was around 63 % for all strains, indicating that macrophages phagocytized a similar number of bacteria from each strain. Colony forming units (CFU) were counted in the bactericidal assays that showed permissiveness of macrophages for the replication of field strains with low frequency genotypes with higher CFU/ml in the survival time (time 1). In the BCG strain, CFU decreased in survival compared to the phagocytosis time (time 0). The same scenario was observed with high frequency genotype strain the amount of CFU/ml was higher in survival; while in BCG, the amount of CFU/ml decreased (Figure 1).

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Figure 1: Colony forming units (CFU) of M. bovis strains with high (+) and low (-) frequency genotypes, quantified at 0 (T0) and 24 (T1) hours post-infection of bovine macrophages with a resistant phenotype

A comparison of the average of CFU per group was made using the student's t test. No significant differences were found (P>0.05) between the high and low frequency groups in phagocytosis and in survival (Figure 2). In addition, within each group, a statistical analysis was performed using the paired student t test to compare the average of CFU between phagocytosis and survival, significant differences were observed (P<0.05) (Figure 3). Figure 2: Comparison of CFU averages of high and low frequency strains at time 0 and time 1

Statistical analysis using Student's t test 493


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Figure 3: Comparison of CFU averages of time 0 and time 1 in high and low frequency strains

Low frequency

High frequency

6.00E+05

*

UFC/ml

* 4.00E+05

2.00E+05 0.00E+00 0

1

0

1

Time Statistical analysis using the Paired Student t test. Asterisks represent statistical significance (P<0·05).

The intracellular growth of strains with low frequency genotype was obtained. Strain 906 was the one with the highest survival score, with 214 %; whereas the strain 776 had the lowest survival score, with 153 %. Strains 694 and 301 showed 205 % and 172 % intracellular growth, respectively (Figure 4). In the high frequency groups, strain 777 had the highest growth, with 208 %; while the lowest growth corresponded to strain 833, with 169 %. Strains 351 and 559 had a growth of 207 % and 187 %, respectively. The control strain (BCG), showed a growth of 57 %, validating the trial, because it confirms the resistant bovine phenotype. Figure 4: Intracellular growth of M. bovis strains and statistical analysis by nonparametric Dunn's multiple comparisons test of the survival of low and high frequency strains and avirulent M. bovis in bovine macrophages with resistant phenotype

Asterisks represent statistical significance (P<0.1).

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In individual comparisons of strains for intracellular growth, a significant difference was observed (P<0.01) between the low frequency strain 776 and the high frequency strain 351. Strain 776 (SB1495) was collected from a bovine from the state of Coahuila, while strain 351 (SB0669) was from a bovine in the state of Mexico. There was also a significant difference between the low frequency strains 776 (SB1495) and 694 (SB1118). Additionally, a significant difference was observed between the attenuated BCG strain and the analyzed field strains (P<0.01) (Figure 4). Finally, intracellular increase averages of high versus low frequency strains were compared, where no significant differences were observed (P>0.05) (Figure 5).

Figure 5: Comparison of Intracellular Growth averages of high and low frequency strains. Statistical analysis using the nonparametric Wilcoxon test

Discussion It has been shown that mycobacteria genotype is one of the factors that contribute to the severity of the disease, and that it may play a role in the emergence of drug resistance, susceptibility, host response and transmissibility. However, the genetic factors that determine the association of different mycobacterial lineages with different levels of disease severity remain unknown(30,31). The high frequency of strain genotypes can be indicative of the movement of infected cattle without an adequate sanitary control measures. On the other hand, it is probable that the low frequency of some genotypes is 495


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due to the lack of representativeness in the sampling, that is, the number of isolates analyzed is rather a consequence of their availability due to a low prevalence in the region; therefore, it is probable that the little or null presence of certain genotypes in some regions is rather a consequence of the small amount of isolates provided, and not to a real absence(22).

The proportion of phagocytosis was no different between strains; however, statistical differences were found between field strains and the attenuated M. bovis BCG strain. BCG showed less survival, 65 %, confirming that macrophages came from a bovine with resistant phenotype, and the virulence of field strains, as described by Qureshi et al(21). In another study(28), in addition to classifying cattle as resistant or susceptible, the authors suggested that the difference in bacterial adhesion to resistant or susceptible cattle cells could be associated with cell wall components in Brucella abortus, which has mechanisms other than M. bovis to evade the immune response and elimination by macrophages. On the other hand, Gutiérrez-Pabello and Adams(19), carried out bactericidal assays using a field strain and found similar results to ours regarding the difference in survival with respect to the attenuated BCG strain, with a growth of 165 % in resistant bovine macrophages. Macrophages obtained from cattle with resistant genotype, produce a higher amount of nitric oxide (NO) compared to susceptible bovine macrophages. In bovines, NO plays an important role in the elimination of intracellular pathogens by macrophages(27,29).

Virulent M. bovis has different ways of evading the bactericidal mechanisms of the innate immune system. One of the most known and important mechanisms is the "respiratory burst" for the elimination of phagocytized bacteria, although M. bovis has the ability to evade it(32). In addition, M. bovis evades elimination by interrupting the maturation of phagosomes, preventing their fusion with the lysosomes and also appears to inhibit the presentation of antigens by reducing the expression of MHC II molecules(33,34).

Statistical differences were found in three of the eight field strains, between high and low frequencies, and within the same low frequency group. This suggests the existence of a difference between the virulence of these strains and that the frequency of the genotype in cattle is not related to strain virulence using this methodology. One limitation in the present study was the number of strains due to the lack of a representative quantity. Previous studies have tried to associate spoligotypes with virulence in cattle(30), relating the spoligotype to the number of injuries and the injury degree in the carcass. Results showed that SB0273 and SB0520 spoligotypes had high virulence and low frequency. On the other hand, Aguilar León et al(36), attempted to relate virulence to different genotypes in a model of progressive pulmonary tuberculosis in mice, finding that the genotypes of

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wild animals are more virulent than those isolated from humans or livestock; however, it is proposed that M. bovis is highly virulent in the mouse model(35,36).

In Northern Ireland herds, differences in the pathogens genotype have been identified by the size of the outbreak and the proportion of cases with visible lesions in the carcass, suggesting that closely related M. bovis genotypes may vary in terms of transmissibility. Genotypes have differences in the formation of visible lesions, immune response patterns and virulence levels; however, the genetic factors that determine the association of different genotypes of mycobacteria with different degrees of disease severity remain largely unknown. In Mycobacterium tuberculosis (M. tuberculosis), it has been found that among its 6 main genotypes there is variation in immunogenicity, virulence and pathology, together with evidence of a host-pathogen coevolution in the regions where these genotypes are established(37).

The great genetic diversity of M. tuberculosis complex (CMTB) strains supports an important natural scenario, where these strains (particularly M. bovis) have diversified, offering an interesting epidemiological and evolutionary context in which new genotypes can emerge and diversify in terms of adaptation to the host under a range of environmental and human factors(38).

In high incidence countries, the appearance of an epidemiologically successful strain has been attributed to virulence due to the characteristics encoded in the bacterial genome; however, these characteristics are related to genes other than genotyping(39). The above is because these genotyping methods cover only a small part of the approximately 4,000 genes contained in 4.4 Mb of the mycobacterial genome, and are not directly related to virulence(40).

Conclusions and implications

Results from this study contribute to understand the host-pathogen interaction. Intracellular bacteria attempt to survive the hostile environment presented by the immune response where one of the main effectors is the macrophage. The results contribute to validate the microbicidal assay, as a tool to partially evaluate the virulence of intracellular bacterial pathogens, as well as suggest that bacterial genotypes are not directly related to virulence. 497


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Acknowledgments

This research was funded by Programa de Apoyos a Proyectos de Investigación e Inovación Tecnológica (PAPIIT-UNAM) AG-200918 project.

Conflicts of interest The authors declare no conflict of interest.

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https://doi.org/10.22319/rmcp.v12i2.5509 Article Genealogy and artisanal trajectory of the criollo cheese in cocoyam leaf of Hidalgo, Mexico

Fernando Cervantes Escoto a* María Isabel Palacios Rangel a Griselda Monroy Neria a Alfredo Cesín Vargas b Abraham Villegas de Gante a

a

Universidad Autónoma Chapingo. Centro de Investigaciones Económicas Sociales y Tecnológicas de la Agroindustria y Agricultura Mundial, Chapingo, Estado de México. México. b

Universidad Nacional Autónoma de México. México.

*Corresponding author: tartalian04@gmail.com

Abstract: The objective was to provide qualitative information on criollo cheese in cocoyam leaf, in order to contribute to disseminate its presence and make its valorization and its permanence as a local gastronomic heritage possible. In methodology, a structured survey was applied to 18 cheese producers, covering all the people engaged in this activity. Focused semistructured interviews were also carried out with key persons, such as the oldest people who are still producing it today, as well as the marketers. Also utilized were the methodological tools of oral history, the genealogical method and the technological trajectory. The manufacture of this cheese was found to involve a high degree of craftsmanship, and the expertise associated with its production is the same as that was used by the ancestors of the producers, with minimal modifications in the process. It can contribute to its diffusion and valorization as a local gastronomic heritage by mentioning to the consumer that this cheese, in spite of the time, has preserved a highly artisanal character. Therefore, the peculiarities it 503


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has acquired from the physical and cultural environment are expressed in a characteristic flavor, a higher fat content, and different coloration and consistency. All of this, together with its packaging in cocoyam leaves, gives it different organoleptic characteristics from those of commercial cheeses and contributes to generate a typical cheese with attributes valued in the region where it is produced. Key words: Criollo cheese, Oral history, Genealogical method, Technological trajectory, Craftsmanship, Typicality.

Received: 11/09/2019 Accepted: 03/06/2020

Introduction

Food is an important component of social identity, in a world undergoing rapid and profound changes; therefore, it is important to highlight its role, since it constitutes an essential identity reference(1). Culinary specialties have become a bond enabling cultural rapprochement, insofar as they have become elements that speak of the life of peoples and territories. Gastronomy can therefore become an element of sustainability that improves the quality of life of the population that produces, consumes and markets them(2). In this sense, what people eat and how they eat can become a dynamic element of their culture, making it possible to establish spatial-temporal and formal patterns, which in the long run become not only eating habits but also a food technology culture(3). Society faces a complex scenario, due to the enormous symbolic and material wealth implicit in the food diversity and local gastronomy of the peoples, an aspect that needs to be made visible, since it not only represents an invaluable heritage, but also forms part of the collective memory of society as a whole(4). The industrial food transformation process generates a change in consumption patterns, as it replaces everyday foods with the indiscriminate use of highly processed ingredients. This is also the case of cheeses, whose presence throughout history bears witness to the ability of the locals to create a gastronomic product with unique characteristics that render it distinct from those of other regions. However, when inserted into the domain of mass production,

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such products tend to lose their territorial links, which had generated special attributes from a social point of view(5,6). In this sense, the mass production of imitation cheeses (those made with milk substitutes) distorts the vision that the peoples had preserved of their attributes of genuineness and community authenticity, by affecting their culinary status. In other words, the availability of new types of cheese whose intrinsic components have little relationship with the original procedures, utensils and ingredients that gave traditionally produced cheeses their communal meaning, the door is opened to their loss, as well as to that of the tacit (territorial, cultural and functional) knowledge implicit in their production(7,8). In other words, in this process, some cheeses have gradually lost part of their know-how; this, in fact, represents the disappearance of a technological culture recreated over centuries, which is no small thing. Given that local rural development is usually based on a productive activity of reference, the concept of local agro-food product(9), defined as that which emerges from the knowledge and resources that constitute a localized agro-food system (LAFS)(10), is very important for this research(9). Therefore, massive industrialization and the growing production of substitute products for original foods has become a determining factor in the generation of a consumer who is largely unaware of the nutritional and organoleptic properties contained, for example, in genuine cheeses. This translates, in fact, into an insufficient appreciation of the value contained in the traditional products, which affects their presence in high-consumption markets, almost always confining them to very specific local areas(8,11). In Mexico, there are about 40 varieties identified as genuine artisanal cheeses which are facing a gradual disappearance(12). One of these is the criollo cheese in cocoyam leaf, a little known product that is made in the high mountains of the state of Hidalgo. It is a fresh cheese with a soft consistency, sold directly to the consumer and produced only in this region, where the characteristics of the territory, the type of livestock and the transgenerational know-how render it unique. For this reason, the objective of this article was to provide qualitative information on this cheese, in order to contribute to disseminate its presence and make possible its appreciation and permanence as a local gastronomic heritage.

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Material and methods

Data collection strategies and analysis tools

The field research was developed during the summer of 2018. A structured survey was applied to 18 cheese producers, covering the whole of the people engaged in this activity, who reside in the Sierra Alta of the state of Hidalgo, Mexico, in the municipalities of Molango de Escamilla and Lolotla (Figure 1). The purpose of the questionnaire was to identify the basic external elements that determine the preservation or not of this cheese in the region. Variables used were i) gender, ii) age, iii) schooling of the producers, iv) scale, v) use of certain technologies, vi) existence of other associated activities (milk production, marketing, support management). Based on the above, it was possible to identify that gender, scale of production and use of certain technology were the three main variables required to understand the cheese system. Figure 1: Municipalities where criollo cheese in cocoyam leaf is produced

Semi-structured focused interviews with key people ―including the oldest producers and the marketers― were carried out. Notably, this type of qualitative technique was selected because it turned out to be adequate, given the particular interest in deepening the understanding of certain aspects(13). In this specific case, the questions addressed the following aspects: i) origin of the production of cheese in the region, ii) existence or inexistence of family ties between those who have preserved its production; iii) channels or means through which the know-how was transferred and preserved; iv) technological 506


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elements of the know-how (knowledge, traditions, equipment, instruments, and raw materials) preserved or disappeared through time; v) dynamics and links between those elements that make up the system; vi) levels of stability or instability among the various basic elements of cheese production. In this case, the presence or absence of technological changes over time, an aspect that was considered to confer additional value to the product, was considered a stability or instability factor. The subjects of the survey and interviewees were selected using the non-probabilistic sampling method known as “exponential discriminative snowball sampling”(14), which consists in asking the residents of the location who the individuals who have special knowledge of the phenomenon to be researched are. A pool of resources rich in information is thus collected along the way(15). Finally, all 18 cheese producers were registered in a census. One of the methodological tools employed was oral history, which offers a simple, dynamic alternative for identifying the symbolic value of certain agro-food products for the inhabitants of the communities and determining whether these are to be regarded as an ancestral legacy(16). In this case, it was used to identify the origin of the criollo cheese in cocoyam leaf through the memory and stories of the producers (cocoyam belongs to the genus Xanthosoma; it is commonly known as mafaffa, otoe, malanga, or cocoyam). The genealogical method was also utilized to inquire about the cheese-producing expertise, showing how this is passed on from one generation of producer families to another. This information was systematized and graphically represented in genealogies(17). This method is generally used in anthropological research, as it allows understanding a wide range of aspects (family systems, filiation and inheritance laws and norms, migration, magic, religion, customs and traditions), all of which are linked to social and cultural, individual or group behaviors in certain societal environments. Likewise, it is utilized for tracing kinship relationships established within a group, as well as for reconstructing the community and family history of which a traditional know-how is part. It is also used when a more detailed analysis of the production systems is required. It is particularly helpful for studying the development of artisanal cheese production, as in the present case(16). The technological trajectory approach was another methodological tool utilized with the aim of identifying the technological changes that have been incorporated into the production units over time, in order to verify the degree of persistence of the “technological tradition” in the manufacture of agro-food products through the assessment of their effects on the preservation or loss of their authenticity(18). The changes in the stages of the process and the use of raw materials and equipment for the production of criollo cheese were verified. In order to identify the technological trajectory of the cheese, the variables processed volume of milk, use of raw materials and equipment for the manufacture, use of 507


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raw materials related to the production (fluid and/or powdered milk, animal and synthetic rennet, calcium chloride), and quality testing were considered. Table 1 shows the relationships between all the utilized variables and tools. Table 1: Utilized variables and tools Tool

Variable General data Gender Age Schooling Family members engaged in the activity Oral history Antiquity of the cheese First producer Context of the event How the know-how was disseminated Genealogy Oldest family member engaged in the activity Acquaintences (not family members) engaged in the activity Who the producer learned from To whom the producer taught Years devoted to the activity Technological trajectory Use of de certain technology Processed volumen of milk Machinery, equipment, instruments for the manufacture process Use of raw materials Quality tests Production scale Changes in the manufacture process Commercialization Who sells the cheese To whom it is sold Packaging Point of sale Distance from the point of sale

Survey, focused interview Survey, focused interview Survey, focused interview Focused interview Focused interview Focused interview Focused interview Focused interview Focused interview Focused interview Focused interview Focused interview Survey, focused interview Survey Survey Survey Survey Survey Survey Survey, focused interview Survey, focused interview Survey Survey Survey

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Results and discussion

Origin of the criollo cheese in cocoyam leaf

This cheese was first produced in several communities of the municipalities of Molango and Lolotla approximately one century ago. The etymological interpretation of the word Molango is “Place of mole”, a name with Nahuatl roots given to this location by the Aztecs when they conquered the region. Lolotla, also a Nahuatl word, means “rock surrounded by thread”, an expression that refers to the topography of the place, which consists of hills, on which most dwellings stand. According to the results obtained from oral history, the criollo cheese in cocoyam leaf was first produced around the year 1916 by the Melo Quijano family. In his narrative of the facts, one of its descendants, Mr. Ángelo Crescenciano Melo Castillo, recalls that his grandparents owned a large piece of land, and they had approximately 130 heads of cattle, which, then as now, were bred on the mountain (a natural elevation covered with vegetation). For the milking, the laborers used to walk uphill, carrying a chápal ―a clay pot with a capacity of up to 20 L―, which served for storing the milk during its transfer. In order not to get hurt due to its weight, they used to carry it on their head with the aid of an interwoven piece of cloth. Once the milk had been collected, they took it to the kitchen of Doña Rafaela Pedraza Bautista, wife of Delfino Melo Quijano, the owner of the farm. After the fresh milk had been consumed or sold, the remainder was used for making the criollo cheese. In the kitchen, the milk was emptied into another earthenware chápal and sieved through a piece of cloth to prevent the proliferation of extraneous agents that might spoil or transmit an unpleasant taste to the cheese. If the milk was still warm, they added natural rennet; otherwise, they heated it on the firewood stove until it reached a temperature of approximately 37 or 38 °C, after which the rennet was added, and the mixture was let stand. Once the curd was formed, it was cut with a chamolito ―a stick in the shape of a cross―, and then gradually separated within the same chápal, until a ball was formed; this was then drawn and placed on a piece of cloth, and the process was repeated until all the curd was on cloth. Once the curd was separated from the whey, it was ground on the metate, adding salt little by little. Subsequently, the pieces were formed in wooden molds, where they were drained on a tilted plank, and each piece was then wrapped in a leaf of cocoyam (this plant abounds in the region), which contributed to its conservation and to the preservation of its organoleptic qualities.

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Characteristics of the local cheese-producing system

The marketing of the cheese

The cheese was sold directly to the consumer and marketed in some neighboring towns such as Zacualtipán, Tamazunchale, San Felipe, Huitepec, and Ixtlahuaco. It was so much in demand that, according to informants, it took longer to arrive at the site than to be sold; in addition to this cheese, the informants offered milk and cottage cheese. Some products, such as cheese, have been documented to sell better if they have consumer recognition(19). Furthermore, confidence in the quality of the food is established, among other parameters, by the personal relationships between the producer-seller and the consumer, and in this case, word-of-mouth recommendations, good or bad, contribute to build the prestige of the artisan cheese maker. Therefore, in local markets, consumer loyalty, built through constancy and by taking care of everything that makes up a harmonious relationship and for long periods, is important for the trader; however, it can be quickly lost. At this level, it is important that both parties involved in the transaction consider that they benefit from it. As was the case across the country at that time, horses, donkeys or mules were used to transport the products. Criollo cheese and cottage cheese were transported in "chiquigüites", a word of Nahuatl origin, which refers to wicker baskets of different sizes, made of scraped sticks, while milk was transported in chápales. Not all of the cheese produced was sent to the market; a considerable part was sold at home. Similarly, in the case of the Serrano cheese from Campos da Cima do Serra (Brazil), in the mid-18th century, mule caravans transported the cheese from the locality where it was produced to the neighboring state of Santa Catarina, where it was marketed and from where the taste for the product spread(20). Similar to this form of commercialization was that of Cotija cheese, which was transported by muleteers, as a product and also as food, from western Mexico to the southeast of the country; it is even mentioned that it reached some parts of Central America, resulting in the present-day production of a Cotija-style cheese in the state of Chiapas. The result of the transmission of know-how and the migration of producers derived from these initial exchanges. In the case of cocoyam leaf cheese, the form of payment was diverse, in some cases it was made by monetary transaction, in others, by barter, or even in exchange for some work done by the purchaser. Because it was produced domestically and by hand, the quantity of

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orders was small ―20 pieces at most―, which shows to not only its small scale of production, but also the fact that there were people who bought the entire production, which highlights the quality of the product. Much the same occurs in certain localities near the Italian Mediterranean, where an important quantity of artisanal cheeses with a unique and peculiar taste are manufactured as farmhouse cheeses, from raw milk(21). In the same sense, some authors mention that this is due, especially, to the fact that when the unique characteristics of a product, such as cheese, satisfy the customer, demand tends to remain loyal to the product while it also grows(22).

The need to value the cheese in cocoyam leaf

At the time of the research, the sale of raw milk in the region was minimal. Cheese makers pointed out that in 1996, around the same time, the introduction of dairy products in cartons into local stores reduced the demand for raw milk until it disappeared. Since then, all the milk produced in these communities is processed into cheese, which continues to be well known and accepted in the area. This is supported, as in the case of cocoyam leaf cheese, by the fact that artisanal cheeses have strong community and local roots, since their production is based, from their origins, on the use of indigenous natural and social resources, facilitating their integration into the local gastronomic culture. When the problem of artisanal cheeses transcends the local level, due to the different phenomena that have occurred in the rural environment ―such as loss of population due to migration, and, consequently, the risk of the disappearance of traditional knowledge linked to know-how, the increase in poverty rates, etc.―, it becomes necessary to value these traditional products, because they contribute to the development of the communities and the cheese makers, and ensure their permanence in the activity. Traditional foods are consumed frequently or in association with celebrations or specific times of the year, such as the rainy season, for example. Therefore, they are usually handed down from generation to generation. They are carefully prepared in a specific way (know-how), according to the gastronomic heritage, with little or no processing/manufacturing; differentiated and known for their sensory properties, and associated with a specific locality, region or country, and therefore deserve to be preserved or recovered, depending on their situation(23). Finally, an important aspect in the territorial appraisal of artisanal cheeses is the implementation of protocols in the cheese factories to ensure the sanitary quality of the product, as well as other types of attributes such as organoleptic attributes, which are the strengths of this type of food. On the other hand, adequate management and conservation of local natural resources must be guaranteed, as well as incentives for the participation of producers to attain the abovementioned goals(11). An example of this is related to the 511


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production of Cotija cheese in Mexico: its producers created the project "Potentiation of the cultural heritage of the Sierra de Jalmich", which made it possible to involve all the actors and make the improvement of its food and craft quality coincide with its recovery as a collective heritage (economic, social and cultural)(24). Another case is that of the queso bola (ball cheese) of Ocosingo, Chiapas, Mexico, where the producers were able to temporarily obtain a collective trademark (CTM), which gave external recognition to the local cheese culture for a considerable period of time(25). However, revaluing the local cheese culture requires developing several actions, most of them collective, which producers often fail to concretize, such as organizing themselves in order to attain the collective good and thus improve aspects such as the sanitary quality of the cheese and its production process, its quality control and product certification, as well as the development of better market options. It must be considered that a geographical indication (GI), or any other seal of territorial anchorage, has no value in itself, but is based on the collective action of producers and other related actors, who influence the development of traditional, genuine and social identity cheeses(25). It is worth noting that consumers do not always value the intangible factors (recognition, culture) that influence their consumption. Therefore, the cultural richness of artisanal cheeses is an important aspect that should be reclaimed in order to generate greater appreciation by the consumer(26). The revaluation of local products has become a strategy that is closely related to what many authors call local development, presenting a conception of development as something generated from local capacities and resources(10).

The transmission of the know-how of the manufacture of criollo cheese in cocoyam leaf across generations

Based on various accounts of the descendants of Mr. Delfino Melo Quijano, a pattern was generated to locate the origin of the cocoyam leaf cheese, as well as the way in which the know-how was transmitted from one generation to another. Thus, it was possible to interconnect the transfer of knowledge with the elaboration of the product. According to the oral narration, "Since Don Delfino and his wife, Rafaela Pedraza, had a large number of cattle heads, they decided to produce cheese with the remainder that was left over after the sale of the raw milk". Thus, "while Delfino and some employees took care of the cows and the milking, Rafaela made cheese at home, supported by some neighbors, since, as is tradition, along with her domestic activities and with caring for her five children ―Gonzalo, Casimiro, Pablo, Baldomero, and Sofía―, Rafaela was also responsible for the production of cheese; through this activity she also sought to make a little more money".

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An undeniable fact is that "over time, not only the women of the family engaged in cheese production but also the men". The know-how was passed on to everyone. However, only a few of the sons continued to engage in the activity. Andrea Castillo, wife of Casimiro Melo Pedraza, learned the cheese-making technique from her mother-in-law; with the passage of time, she became an important collaborator in the cheese making process. Six children were born to the Melo Castillo couple: two men and four women, whose names were Ángelo Crescenciano, Crisanto, Justina, Teresa, Prisca, and Honorina. It was Ángelo Crecenciano and his wife, Angelina Díaz Hernández, who rescued the cheese-making know-how; their two daughters, Griselda and Susana, who also learned the cheese-making process in their childhood, inherited this. Honorina, the youngest daughter of Casimiro Melo Pedraza and Andrea Castillo, married Rodolfo García Díaz, a small local farmer who not only continues to provide the milk ―the basis for the production of cheese―, but has also encouraged Honorina to keep make it to the present day. This knowledge has been passed on to their children, Alejandro and María Concepción, who, although still young, have learned the technique and will surely be the ones to continue the family cheese-making tradition over time. It should be noted that, in this region, most of the current cheese makers continue to preserve the traditional way in which the original family produced this type of cheese. Such is the case of Paula and Graciela Hernández, Cipriana López, Irma Reyes, Cecilia Apolonio, Marina Bustos, Alicia and Hilaria Montiel, and the Campoy family, who in their testimony mention that their parents or grandparents worked closely with Rafaela Pedraza in its manufacture. Thus, it may be said that the knowledge and technique for manufacturing criollo cheese in cocoyam leaf has gone beyond the family circle that gave rise to it and has become a community asset. Figure 2 depicts the symbols used in the genealogical map that integrates the actors that have intervened ―starting with the Melo Pedraza family― in the preservation of the knowledge and technique for the production of criollo cheese in cocoyam leaf in this region, and Figure 3 shows the genealogy followed for the diffusion of the knowledge involved in the production of criollo cheese by those who learned it directly from that family.

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Figure 2: Symbols used in the genealogical map

Man Woman Person who recovers the cheese-making tradition Person who knowledge

possesses

cheese-making

Marital relationship Current producers of criollo cheese Actor level within the genealogical map

Figure 3: Genealogy of the diffusion of the knowledge of the manufacture of criollo cheese

There are other pathways, not directly related to the Melo Quijano family, through which the expertise of cheese making was passed on. This fact can be interpreted as an indication that this culinary heritage has very precise internal origins, as well as external ramifications that render it a part of a broader geographic system(27,28). Such is the case of Mrs. María del Carmen Bustos, who accumulates more than 40 yr of experience in the activity, taught to 514


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her by her mother, Lucía Pelcastre, who in turn learned it from her grandmother, Rufina Apolonio, and they both engaged in it together until the death of the latter. A similar case is that of Mrs. María Abraham Ávalos, who has been making this cheese for 37 ys, having acquired this knowledge from her mother-in-law, Teresa Mendoza. Similarly, Raúl Valentín has been making this cheese for five years with a technique taught to him by his grandmother Agustina Serna. In addition, Abundia Juárez acquired the knowledge from her mother, and both have been making cheese for thirty years. Figure 4 shows the genealogical map of these cheesemakers. Figure 4: Genealogy of the families where the transfer of knowledge of criollo cheese production could not be established

As can be seen from the testimonies provided, the participation of women in the transmission of know-how for the manufacture of this product and in the permanence of the cheese-making practice in this region has been predominant. However, at the same time, it is part of a family reproduction strategy, since the whole family is involved in its manufacture. Thus, there is a division of activities: the father is in charge of milk production and cow maintenance; the mother makes and sells the cheese and spreads the know-how; the sons and daughters collaborate in its production and distribution; in other words, the cocoyam leaf criollo cheese not only has a territorial flavor, but also forms part of a family culture that transcends the domestic sphere and is a geographical factor of community identification. In this manner, the fact that the family income is complemented by integrating the mother's activities with the cheese production, all with the active support of the family members, is a factor that has helped to sustain cheese production. Previous research indicates that the domestic structure behind cheese production in small family units is the result of adjustments to the family division of labor, which is modified as women have a greater economic participation in raising an income, also resulting in a substantial increase of her production(29). In this case, cheese making is a paradigmatic example of the transition process from a traditional rural society to the new rurality(30), an adaptation to new 515


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scenarios that is not uniform and that, for the less favored regions or activities, represents a challenge, with more limitations than resources to overcome it. Likewise, a previous study of a case of artisanal cheese production in Herzegovina concluded that women play a very important role in the appraisal of typical products, which guarantees not only their recognition, protection and economic well-being, but also generates a more integrated model in the development of the region of origin, showing evident advantages of improvement and tangible benefits (employment growth, higher income, etc.)(31). In other regions of Mexico, family milk production and the tradition of cheese making have sustained the local development of a delimited territory. In these areas, the articulation of the family milk system becomes a specific productive resource, linked to the domestic, local and regional manufacture of cheese, where know-how becomes a window of opportunity, with regional fame and reputation(32). This articulation is important because it gives viability to rural households, incorporating the various members of the family into the cheese-making activity, some of them part-time, and allowing pluriactivity, which can be essential for its operation. In particular, the preservation of the artisanal character of a product consists in a production process and characteristics that are defined according to local knowledge, and even the culinary practices inherited by each family, and it represent an advantage throughout the chain to final consumption(33): Trust relationships are thereby established between the producer (or marketer) and the consumer that can last for a long time, and the products are valued, recommended and promoted by word of mouth by their buyers, extolling their qualities. In the particular case of the Chiapas cream cheese, its artisanal production is valued; it is based on the origin, the manufacture process, the production equipment, the livestock used (for a dual purpose) and their diet, the know-how of cheese (passed down through generations), etc.. All these elements ultimately contribute to impart the unique characteristics of the cheese, such as its genuineness and typicality. Cheesemakers value the process because it allows them to reproduce their know-how, passed down through history; it also enables them to be part of a group or guild, where knowledge is shared and improved(34). In this sense, the know-how of artisanal products is associated with empirical knowledge that is disseminated in the form of non-formal education processes, which are scarcely valued by public institutions. This situation is associated with the production of originrelated quality products, upon which natural climatic conditions confer distinctive characteristics that render them recognizable and valued by the consumers(10). In this manner, the increasing potential of this type of genuine products is closely linked to aspects such as geographical and cultural diversity and allows the creation of a great variety of foods and ways of preparing them in local and regional gastronomy(35).

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Technological trajectory in the process of making criollo cheese in cocoyam leaf

The study of typical food products of Italy as a strategy to strengthen gastronomic tourism considers that the degree of craftsmanship in the making of a local product is directly linked to the relationship between a territory and its original productions and that this relationship contributes to enhancing the quality of the product, due to the care taken by the producers in the selection of the ingredients(36). This also allows the genuine product to retain its place as part of a cultural heritage, whereby a strong connection between the genuine product and the development of an appreciative community awareness is established. Criollo cheese in cocoyam leaf emerged, like others, as a strategy to avoid wasting seasonal milk surpluses. Its manufacturing process today is still very similar to the original, only some slight changes have been incorporated into it (Table 2). Most of the genuine Mexican cheeses were first made at ranches as a means to avoid wasting and preserve surplus milk during the rainy season. Table 2: Technological trajectory of the production system of criollo cheese in cocoyam leaf Year

Manufacture technology

1916

Date established as the date of origin of this cheese.

1917

During this year, the designation of the procedure for the production of this cheese was completed. It included the following aspects: 

Fluid cow's milk was used in the production process

The milk was curdled in clay chápales, which had a capacity of 20 liters; the chamolito, a stick instrument similar to a spoon, was used for this procedure.

The temperature was determined based on observation and touch.

The curd grinding process was carried out on a metate, where coarse salt was added to the curd.

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Year

Manufacture technology 

The draining procedure consisted of placing the ground cheese on a cocoyam leaf and letting it sit there for the time necessary for it to acquire consistency and flavor.

Once this was accomplished, the cheese was wrapped in the cocoyam leaf, which allowed its subsequent transportation and sale.

The cheese making process did not include the use of palm leaf baskets or metal containers

1994

Plastic demijohns and aluminum buckets were first introduced into the production of cheese, replacing the use of the chápal.

1997

Pieces of cloth or cloth sacks were first used to facilitate the draining of the whey.

1998

The chamolito was replaced by the aluminum spoon, although some cheesemakers (e.g. Angelina Díaz and Hilaria Apolonio) still use it today.

1999

The use of wood and PVC molds was introduced.

2012

The use of natural rennet was substituted by commercial rennet (only by two producers).

2013

Cheese maker Raúl Valentín replaced the cocoyam leaf with plastic bags, a situation that did not prosper among the other producers.

2017

The use of fluid cow's milk and the method of curdling, salting and grinding are still used in the traditional production process of this cheese. So is the packaging of the final product in the cocoyam leaf.

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Year

Manufacture technology

Image

Milk pasteurization has not been a method adopted by cheesemakers, since this procedure adds costs to the product, in addition to modifying the consistency and flavor of the cheese.

Conclusions and implications

The territorial anchorage (understood as the link that food products have with the place where they are produced) is essential to understand and sustain an artisanal system such as the one presented herein, since this connection is transformed over time into a culinary tradition of which the people feel very proud. The importance of criollo cheese in cocoyam leaf lies precisely in that it is a food with a history ―the result of an expertise that has been passed down through generations of family and acquaintances. One way to contribute to its diffusion and appraisal as a local gastronomic heritage would be to mention to the consumer that this cheese has preserved a highly artisanal character over time and that the peculiarities it has acquired from the physical and cultural environment are expressed in its characteristic flavor, higher fat content, and different color and consistency, in addition to its being wrapped in cocoyam leaf ―all of which confer different organoleptic characteristics upon it, compared to the so-called commercial cheeses. Literature cited: 1.

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Martín GMB, López AXA. Productos agroalimentarios de calidad y turismo en España: Estrategias para el desarrollo local. Geographicalia 2005;(47):87–110.

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Nunes DC. Somos lo que comemos Identidad cultural, hábitos alimenticios y turismo. Estud y Perspect en Tur 2007;16(2):234–242.

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Unigarro SC. Patrimonio cultural alimentario. Primera ed. Ecuador: Auxiliadora Balladares UM, editor; 2010.

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Leyva TDA, Pérez VA. Pérdida de las raíces culinarias por la transformación en la cultura alimentaria. Rev Mex Cienc Agríc 2015;6(4):867–881.

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Fournier T. Are traditional foods and eating patterns really good for health? In: Sébastia B, editor. Comer comida tradicional Política, identidad y prácticas. 1rst ed. Francia: Routledge; 2016:180–200.

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20. Krone E, Thomé CF, Menasche R. Del lomo de las mulas a la clandestinidad: Dilemas entre las exigencias legales y el sistema tradicional de producción del queso serrano de los campos de Cima da Serra (Brasil). International EAAE-SYAL Seminar-Spatial Dynamic in Agri-food Systems. Brasil; 2010. 21. Romano P, Ricciardi A, Salzano G, Suzzi G. Yeasts from Water Buffalo Mozzarella, a traditional cheese of the Mediterranean area. Int J Food Microbiol 2001;69(1–2):45– 51. 22. Thomé CF, Menasche R. Tradition and diversity jeopardised by food safety regulations? The Serrano Cheese case, Campos de Cima da Serra region, Brazil. Food Policy. 2014;45:116–124. 23. Villegas A, Santos A, Cervantes F. Los quesos mexicanos tradicionales. México: Universidad Autónoma Chapingo-CIESTAAM; 2016. 24. Pomeón T. El queso Cotija, México. Un producto con marca colectiva queso “Cotija Región de origen”, en proceso de adquisición de una Denominación de Origen. México: FAO-IICA; 2007. 25. Poméon T. De la retórica a la práctica del patrimonio: procesos de calificación de los quesos tradicionales mexicanos [tesis doctorado]. Texcoco, México; Universidad Autónoma Chapingo; 2011. 26. Espejel GA, Rodríguez PDM, Barrera RAI, Ramírez GAG. Factores estratégicos de la innovación y mercado en queserías artesanales de México. Rev Venez Gerenc 2018;23(82):424–441. 27. Enríquez-Sánchez J, Muñoz-Rodríguez M, Altamirano-Cárdenas JR, Villegas-De Gante A. Activation process analysis of the localized agri-food system using social networks. Agric Econ 2017;63(3):121–135. 28. Guzmán M. La valorización de los alimentos en Europa y en América Latina. In: Aspects juridiques de la valorisation des denrées alimentaires Colloque Lascaux. San José, Costa Rica; 2012:1–15. 29. Grass RJF, Sánchez GJ, Altamirano CJR. Análisis de redes en la producción de tres quesos mexicanos genuinos. Estud Sociales 2015;23(45):185–212. 30. Aguilar CE, Amaya CS, López MI. Alimentos con calidad. Nuevas estrategias rurales para nuevos consumidores. Arx d’Etnografia Catalunya 2016;(16):137-152. 31. Samardzic S, El Bilali H, Bajramovic S, Kanlic V, Ostojic A, Berjan S, et al. Cheese in a suck: exploring history, production area and production process of a typical herzegovinian product. Int J Environ Rural Dev 2014;5(2):74–79. 521


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32. Castañeda MT, Boucher F, Sánchez VE, Espinoza OA. La concentración de agroindustrias rurales de producción de quesos en el noroeste del Estado de México: un estudio de caracterización. Estud Soc 2009;17(34):73–109. 33. Andablo RAC, Hernández MMC, Catalán DCG. Gobernanza e integración de familias rurales a cadenas pecuarias: el caso del ejido Cobachi, Sonora. Econ Teoría y Práctica. 2015;(42):105–135. 34. Lozano MO, Villegas GA. Valorización simbólica del Queso Crema de Chiapas, un queso mexicano tradicional con calidad de origen. PASOS Rev Tur y Patrim Cult 2016;14(2):459–473. 35. Goméz MMB, Armesto LXA. Productos agroalimentarios de calidad y turismo en España: Estrategias para el desarrollo local. Geographicalia 2005;(47):87–110. 36. Olivieri FM, Giraldi A. Food and wine tourism: an analysis of Italian typical products. Alma Tour 2015;(11):11–35.

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https://doi.org/10.22319/rmcp.v12i2.5642 Review

Feed efficiency indexes in hair sheep: meat quality and associated genes. Review

Carlos Arce-Recinos a Alfonso Juventino Chay-Canul b* Baldomero Alarcón-Zúñiga c Jesús Alberto Ramos-Juárez a Luis Manuel Vargas-Villamil a Emilio Manuel Aranda-Ibáñez a Nathaly del Carmen Sánchez-Villegas a Ricardo Lopes Dias da Costa d

a

Colegio de Postgraduados. Campus Tabasco. Periférico Carlos A. Molina, Km 3.5. Carretera Cárdenas-Huimanguillo. 86500 H. Cárdenas, Tabasco, México. b

Universidad Juárez Autónoma de Tabasco. División Académica de Ciencias Agropecuarias, Tabasco, México. c

Universidad Autónoma Chapingo. Departamento de Zootecnia, Estado de México, México.

d

Instituto de Zootecnia. São Paulo, Brasil.

*Corresponding author: alfonso.chay@ujat.mx; alfonsochay2@gmail.com

Abstract: Hair sheep are essential for meat production in tropical regions, where feed efficiency has been little evaluated. Feed consumption represents more than 70 % of the costs. Therefore, animals with high feed efficiency could increase the profitability of the production system.

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There exist tools that help select individuals with increased feed efficiency without compromising the quality of the product. This review aims to identify these geneticmolecular and statistical tools, such as residual feed intake (RFI) and residual intake and gain (RIG). Previous studies report differences ranging from 9 to 30 % in the dry matter intake (DMI) of efficient and inefficient animals, maintaining a similar daily weight gain (DWG) using the RFI index. Moreover, the DMI is similar using the RIG index. Although, the DWG of efficient animals is higher by up to 50 g d-1, reducing feed conversion by one kg. This difference is attributed to a group of genes associated with feed efficiency (Adra2a, Gfra1, Gh, Glis1, Il1rapl1, Lep, Lepr, Mc4r, Oxsm, Pde8b, Rarb, Ryr2, Sox5, Sox6, and Trdn). These genes could be used to select hair sheep with high feed efficiency, considering the genes associated with meat quality (Capns1, Cast, Dgat1, Fabp4, Igf-i, Lep, Mstn, and Scd). Key words: Feed efficiency, Meat quality, Genes, Hair sheep.

Received: 16/03/2020 Accepted: 11/09/2020

Introduction The global sheep population in 2017 consisted of 1,202 million heads. Approximately 74 % of this population is distributed between Asia and Africa (42.25 and 31.7 %, respectively). The remaining 26 % is located in the rest of the continents. Although America has the smallest sheep population (6.76 %), its average carcass weight is higher (18.6 kg) than that of the other continents, only surpassed by Oceania (21.6 kg)(1). In Mexico, sheep production is one of the livestock activities with more presence regarding territorial distribution. According to the preliminary figures of 2018, the sheep population reached 8'683,835 heads(2); approximately 11 % of this population in the American continent, distributed in around 53,000 production units. About 53 % is located in the center of the country, 24 % in the south-southeast, and 23 % in the north(3). Pelibuey is one of the most numerous breeds; it is used as breeding stock due to its maternal ability, high prolificacy, rusticity, resistance to parasites, and great adaptation to the various climatic conditions in the country(4). Moreover, feed intake is one of the most important factors in intensive meat production systems, representing more than 70 % of total production costs(5). Therefore, the selection of 524


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animals with high feed efficiency, those that require a lower feed intake to maintain their performance or increase their production with a similar intake, could increase the unit’s profitability(6). Reducing feed costs would help keep profitable prices within a fluctuating agricultural supply market and competitiveness in the global market. Traditionally, the meat production livestock industry has used feed conversion (FC) to assess feed efficiency(7). Nonetheless, this measure is questionable because the DMI is highly correlated with body size and production level(8); this tends to select animals with high DWG. However, animals with high DMI are also selected, which increases production costs(7). Taking a different approach, other authors have defined feed efficiency as the animal capacity to reach a specific weight with a lower DMI(9). Ruminants' efficiency is low compared to other species. However, they can transform nonfood resources for humans (forages and nonprotein nitrogen) into high-quality food (animal protein)(7). Consequently, several tools have been sought to help explain, predict, and select individuals with greater efficiency in feed utilization and energy intake. Residual feed intake (RFI) being among the most used ones(9,10). RFI is defined as the difference between the real and the expected feed intake for a specific weight and production level during an established period(8,11). This tool identifies the animals with the greatest efficiency of feed utilization, improving the herd's genetics and reducing the production costs of each increased kilogram of live weight(8). Koch et al(9) proposed the Residual Gain (RG) index; this tool estimates the expected gain for a specific production level and identifies the animals with the highest weight gain rates. A new indicator of feed efficiency was recently proposed, the Residual Intake and Gain (RIG) index. This indicator retains the selection characteristic of RFI and RG, which are independent of body weight. RIG selects the animals with the greatest DWG and the lowest DMI since it correlates negatively with the DMI and positively with the DWG(12). The meat industry is not only interested in the efficiency of feed utilization but also the quality of the final product. Meat quality includes various traits, such as physicochemical attributes (tenderness, color, fat content, intramuscular, and water holding capacity), palatability factors (flavor, juiciness, and smell), and food safety characteristics(13). These quality traits influence the decision-making of the consumer and the meat processing industry(14). On this matter, several studies have used RFI to determine the effect of feed efficiency on meat quality. They have reported that selecting efficient Angus bovines (low RFI) does not hurt meat quality(15,16). However, recent studies in Nelore cattle have reported conflicting results. Some authors observed that efficiency does not affect meat quality and the calpain system(17,18), yet other studies report the opposite. Therefore, animals with low

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RFI tend to have tougher meat(19). This undesirable characteristic is regulated by protein turnover and specific enzymes (especially those in the calpain system), which carry out the muscle postmortem proteolysis(20). Furthermore, previous reports mention that proteolysis is related to the maintenance energy requirement (MER); a high protein degradation rate is associated with a higher MER(21). Additionally, the most efficient animals have a lower maintenance metabolizable energy requirement(17,21). Thus, in Nelore cattle, the most efficient animals have a low protein degradation rate(22), which is associated with a higher shear force at different maturation times (0 d= 4.50 vs 4.00, 7 d= 4.22 vs 3.61, 21 d= 3.27 v. 2.69 kg/cm2), low myofibril fragmentation index (37.0 vs 42 %), and high content of soluble collagen (17.7 vs 14.9 %), resulting in lower meat quality(19). Moreover, the development of molecular genetics, sequencing, and selective gene amplification techniques has increased the detection of genes that have a marked effect on traits of interest, i.e., feed efficiency and meat quality. This allows the detection of the genomic sequences associated with these genes and the establishment of selection programs based on molecular markers(23). A genetic marker is a specific DNA sequence with a known location in a chromosome; this sequence either has a specific function or is associated with the phenotypic expression level of a trait(24). The use of genetic markers helps with problems faced during traditional selection by selecting genetically superior individuals(25). Furthermore, the markers can predict improvement values for the individuals selected at birth more precisely than the classic pedigree index, reducing the generation interval(23). Therefore, this study aimed to review the feed efficiency indexes and their relationship with meat quality and the genes associated with these traits in hair sheep.

Feed efficiency indexes The RFI and RG indicators were proposed by Koch et al(9) after observing that feeding affects the maintenance of live weight and daily weight gain. They suggested that feed intake can be adjusted to body weight and weight gain, dividing it into two components: 1) The feed intake expected for a specific performance or production level and 2) A residual portion. The residual portion of feed intake could be used to identify animals that deviate below their expected level of feed intake (negative RFI); this allows comparing animals with different production levels during the measurement period.

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The RFI has been used as a selection criterion in beef cattle breeding programs. Heifers with low RFI are more efficient regarding feed utilization than those with a high RFI(26); additionally, their progeny tend to behave more efficiently(27). The estimated heritability of this characteristic is moderate (0.27-0.58) and independent from growth and production level(9,28,29,30), and it has no adverse effect on other economically important characteristics, such as meat quality(15). Furthermore, RFI reduces livestock's environmental impact because animals with low RFI tend to produce lower amounts of methane (CH4) per unit of consumed dry matter due to their lower DMI and best energy use efficiency(31,32,33). Therefore, RFI is one of the carbon dioxide (CO2) and CH4 mitigation strategies of livestock. The main advantages of using RFI as a selection criterion are improved feed efficiency(8,34) and increased productivity in the breeding sector, reducing the area used per animal unit(35). The novel RIG index improves feed efficiency and identifies animals with greater growth rates and lower fat proportion without affecting meat and carcass quality, reducing confinement and slaughter times of animals because they reach their commercial weight at early ages(36). The studies that involve the RFI and RIG indexes have been mainly carried out in cattle, pigs, and poultry. These indexes have also been evaluated in temperate climate sheep. Although some studies have included Brazilian hair sheep crosses, the Santa Inés and Pantaneira breeds stand out(5,36,37,38); there is also a study in Dorper sheep(39) (Table 1 and 2). In Mexico, this tool is just starting to be implemented, so there are few studies; there is only one previous study in the Rambouillet breed(40). Therefore, the behavior of hair sheep is still unknown (Table 1).

Estimating the RFI and RIG indexes

The RFI determines the expected DMI and is estimated through a multiple linear regression equation as a function of mean metabolic weight (MMW) and DWG. The model used by Koch et al(9): Yi = β0 + β1 GDPi + β2 PMMi + εi Where: 𝐘𝐢 = Dry matter intake of the i-th animal. 𝛃𝟎 = Regression intercept.

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𝛃𝟏 𝐆𝐃𝐏𝐢 = partial regression coefficient of dry matter intake in the i-th DWG of the animal. 𝛃𝟐 𝐏𝐌𝐌𝐢 = partial regression coefficient of dry matter intake in the i-th mean metabolic weight of the animal. 𝛆𝐢 = residual error in the dry matter intake of the i-th animal. Moreover, RG helps estimate the expected DWG through a multiple linear regression as a function of DMI and MMW. 𝑌𝑖 = 𝛽0 + 𝛽1൫𝐶𝑀𝑆𝑖 ൯ + 𝛽2൫𝑃𝑀𝑀𝑖 ൯ + Ԑ𝑖 Where: Yi= Weight gain of the i-th animal. 𝛃𝟎 = Regression intercept. 𝛃𝟏 𝐂𝐌𝐒𝐢 = partial regression coefficient of the DWG of the i-th DMI of the animal. 𝛃𝟐 𝐏𝐌𝐌𝐢 = partial regression coefficient of the DWG of the i-th MMW of the animal. 𝛆𝐢 = residual error in the DWG of the i-th animal. RIG is calculated with the two previously described models using the following equation: 𝐺𝐼𝑅(𝐶𝐴𝑅 ∗ −1) + 𝐺𝑅. The index requires prior standardization (Mean = 0 and Standard Deviation = 1) of the RFI and RG. After determining the RFI, animals are classified into high (>0.5 SD above the mean, higher feed consumption than expected for maintenance and production; thus, lower efficiency), medium (±0.5 SD from the mean), and low RFI (<0.5 SD below the mean, lower feed consumption; thus, higher efficiency)(41). The same categorization procedure is used to determine the RIG groups. However, high RIG indicates greater efficiency, and low RIG means lower efficiency.

Intervening physiologic factors

There are numerous and interrelated physiologic mechanisms associated with higher feed utilization efficiency. However, they have not been completely elucidated. Richardson and Herd(42) synthesized the results of a series of experiments in Angus cattle selected divergently for RFI. They estimated the proportion of the variation in RFI that explains the following processes: protein turnover, tissue metabolism and stress (37 %), digestibility (10 %), increase of heat and fermentation (9 %), physical activity (9 %), body composition (5 %), and feeding patterns (2 %). The mechanisms responsible for more than 25 % of the variation in RFI are not yet known. The physiologic processes associated with the variation in feed utilization efficiency have been grouped into five categories: 1) Feed intake capacity, 2) Feed

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digestion, 3) Metabolism (anabolism and catabolism), 4) Heat production related to digestion and physical activity, and 5) Thermoregulation(30). Knowing the biological processes involved and the degree to which they contribute to the feed efficiency of hair sheep is crucial since information is scarce in these breeds. Therefore, it is necessary to carry out studies that help understand how these mechanisms favor this behavior, which would allow the selection of more efficient and productive animals.

Feed intake and productive performance

Voluntary feed intake is regulated by a complex interaction between neuroendocrine control mechanisms and the physicochemical properties of feed; this interaction changes according to the physiologic state of the animal(43). Moreover, feed intake directly correlates with the energy used for digestion; at higher the intake, the higher the energy expenditure. This results from an increase in digestive organ size and the energy used in the tissues of these organs(30). This energy expenditure is known as heat increase during fermentation; in ruminants, it represents approximately 9 % of the metabolizable energy intake(44). Most studies (Table 1) indicate that sheep with low RFI show the same DWG as animals with high RFI(5,6,38-40,45-55); animals with low RFI have a better energy use efficiency(33). However, Rocha et al(37) reported significant differences in DWG, making energy use efficiency more noticeable. In all the studies, DMI was lower on the most efficient animals, with a difference ranging from 9 to 30 % compared with those less efficient. Therefore, it is expected that the more efficient animals show a better FC (Table 1). Previous studies in sheep, using the RIG index(5,36,38), have shown that sheep classified with high RIG have a lower DMI, higher DWG, lower FC, and higher feed efficiency (FE) (Table 2). Although the difference in DMI is not as high as that observed with RFI, the DWG differs by up to 50 g d-1. Moreover, FC differs in more than one kg, so the FE is greater in animals with high RIG. Considering that feed is the most significant production cost in animal production systems, lower feed consumption and greater weight gains represent an important reduction in operation costs and increase the profitability of the production units and the efficient use of the supplied energy.

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Methane production

The rumen microbial ecosystem is extremely diverse. It includes Eukarya, Archaea, and Bacteria phylotypes that interact between them, the feed, and the host, with densities of 1010 bacteria mL-1, 106 protozoa mL-1, and 103 fungi ml-1 of ruminal fluid(56). The diversity and concentration of the organisms that live in the rumen are influence by several factors, such as diet, breed, age, health status, environment, and geographic location(57). However, diet is considered the primary determinant of ruminal microbial diversity and the fermentation parameter in cattle and sheep(58). Thus, animals fed forage have a more diverse microbial ecosystem, with more frequent methanogenic groups, compared to those provided concentrate-based diets(59). This implies greater use of free H2 (produced by a more acetic fermentation) to reduce CO2 into CH4(60). The results reported by Henderson et al(61) indicate that regardless of the type of diet and geographic location, there is a central microbiome in the rumen comprised of seven groups. These groups represent 67.1% of the bacterial sequences in the global analyzed samples. This major group includes Prevotella, Butyrivibrio, Ruminicoccus, Lachnospiraceae, Ruminococcaceae, Bacteroidales, and Clostridiales. However, some genera are more abundant with specific diets. For example, Bacteroidales, Clostridiales, Fibrobacter, and Ruminococcaceae are more abundant in animals fed with forage; Prevotella and Succinivibrionaceae are more abundant with concentrate-based diets. Moreover, in the same study, they reported that the archaea population is constituted mainly by Methanobrevibacter gottschalkii and Methanobrevibacter ruminantium, representing 74 % of all the archaea inside the rumen. Other found species were Methanosphaera sp. and two groups belonging to Methanomassiliicoccaceae. These five species constituted 89 % of the total archaea; Methanobacterias being one of the main species that utilize free H2 to reduce CO2 to CH4(62). These species are associated with fibrous diets, where fermentation is more acetic and H2 release is higher Recent studies indicate that feed efficiency is related to CH4 production(31,62,63). It has been reported that the methanogenic communities in animals with high RFI are more diverse compared to efficient animals, with a high prevalence of M. stadtmaniae and Methanobrevibacter sp. Thus, animals with high RFI emit more CO2 and CH4 due to their higher fiber intake, which increases ruminal CH4 production. Animals with low RFI tend to modify their bacteria consortia. Therefore, they can use the fibrous components of the ration more efficiently, reducing the passage rate and increasing digestibility. Thus, completely fermenting rations at a ruminal level(62).

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Using statistical prediction models, female sheep have shown significant differences in CH4 emissions. Emissions are lower in animals with low and medium RFI, compared to those with high RFI (0.025a, 0.028a, and 0.032b CH4 kg-1 d-1, respectively). However, no differences were observed in male sheep due to the lack of significant difference in the DMI of efficient and inefficient animals(40). Furthermore, greater efficiency could be related to bacteria that modify the fermentation pattern towards a more propionic fermentation, which favors meat production(33). Propionate is the main substrate contributing to the gluconeogenesis process; glucose is required as an energy source in protein synthesis(43). Previous studies have reported greater propionate concentrations in highly efficient sheep (low RFI) fed concentrate-based diets, compared to those less efficient (41.2 vs 30.2 % Molar)(6). Therefore, animal selection based on feed efficiency indexes could reduce the greenhouse gases (GHG) produced by sheep.

Candidate genes associated with feed Various studies have reported many single nucleotide polymorphisms (SNP) associated with feed efficiency in bovine species(64-67). Few studies have focused on sheep. Knowing the genes implicated in the biological processes related to desirable, productive characteristics (feed efficiency and meat quality) of farm animals(20,55,68-86) helps understand the relationship between these parameters and then use these genes as molecular markers for the selection of animals with desired traits (Table 3). Cockrum et al(87) identified markers through genome-wide association studies (GWAS) with a nominal threshold of P<3.02-4 in sheep genes associated with RFI. The candidate genes were: Glis Family Zinc Finger 1 (Glis1), SRY-related box -5 and -6 transcription factor (Sox5, Sox6), and Interleukin 1 Receptor Accessory Protein Like 1 (Il1rapl1). Another gene associated with this index is the Leptin receptor (Lepr). The association of a SNP in exon 2 of Lepr has also been reported in lactating ewes (P<0.05); the homozygous CC genotype had the highest RFI (2.579a), compared to the TC (1.218b) and TT (1.005b) genotypes(88). Recent studies have reported the association of DWG and specific SNPs; these associations can be considered in selecting animals with better productive performance. For example, in sheep, three genes have been associated with DWG. The triadin gene (Trdn) is in chromosome 8, and the 3-oxoacyl-ACP synthase (Oxsm) and Retinoic acid receptor beta (Rarb) genes are located in chromosome 26(89). Furthermore, the Leptin gene (Lep) has been associated with DWG, with significant differences (P<0.05) in the DWG (six-month weaning) of heterozygous BC, AB, and AC genotypes than in the homozygous AA and CC

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(116, 103, 99, 94, and 94 g d-1, respectively)(90). In the Salsk breed, significant differences (P<0.001) were observed in the growth hormone (Gh) genotypes; AB was superior to AA (128.64 vs 81.51 g d-1)(91). The Melanocortin-4 receptor gene (Mc4r) has also been associated with DWG. A SNP located in the 3' untranslated region of the gene (NM_001126370.2) causes a G>A nucleotide variation in the 1016 position. The heterozygous GA genotype was superior to the homozygous GG at 120 (210.23 vs 192.01 g/d) and 180 d (166.35 v. 155.66 g/d) of fattening. Furthermore, SNP 292 G> A was detected with a variation in amino acid 98 Gly> Arg, which affected the eye area of the Longissmus muscle(92). The association of FC with some genes has been reported. In exon 3 of the Lep gene in lactating ewes, significant differences (P<0.001) were found in the genotypes of a SNP with amino acid variation (c.314 G>A, Arg>Gln). The GC genotype showed lower FC (2.019 kg) compared to the AG genotype (3.886 kg) in milk production(88). Additionally, the g.1429 C>A and g.1117 A>C synonym mutations in the Alpha-2A adrenergic receptor (Adra2a) and Ryanodine receptor 2 (Ryr2) genes had a positive effect with this efficiency indicator. In Adra2a, three genotypes were identified (CC, CA, and AA); the homozygous CC genotype had the lowest FC (4.67b, 5.18a, and 5.14a kg, respectively). As for Ryr2, similar genotypes were identified. However, the homozygous had the lowest FC, but it was statistically similar to the CC genotype (5.14b, 5.08b, and 5.46a kg, respectively)(55). Recently, in Santa Inés sheep, the GDNF family receptor alpha 1 (Gfra1) and Phosphodiesterase (Pde8b) genes have been associated with FE(93). The genes implicated in feed efficiency can help identify superior individuals using molecular techniques. These techniques have been scarcely used in hair sheep. Their use will help identify and select, at an early age, those individuals with higher feed efficiency, reducing the generation interval.

Meat quality and associated candidate genes

Previous studies in sheep(5,37,39,46-49,51) suggest that carcass characteristics (Longissimus area, subcutaneous fat thickness , and Longissimus muscle depth) are not negatively affected when using the RFI index. However, regarding carcass yield, there tends to be a significant difference (P<0.1) between efficient and inefficient animals(37,54). Moreover, genes have been associated with the physicochemical parameters that determine meat quality, such as pH, tenderness, water holding capacity, and color.

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pH

In small ruminants, a normal pH ranges from 5.5 to 5.8(94) and is related to desirable characteristics in meat quality, such as color, shear force, and water holding capacity(95). Some studies have demonstrated the relationship between the pH and the polymorphism of some genes. A previous study reported the association of the Lep gene (intron 2, g.103 A>G) in the Suffolk breed and identified the AA and AG genotypes. The homozygous genotype had a lower pH value (5.53) when compared to the heterozygous (P<0.05)(96). Moreover, genotypes of the Fatty acid-binding protein gene (Fabp4) were identified in Chinese sheep with an effect on pH (P<0.1). The AG heterozygous genotype had a lower pH (6.3); AA and GG had a pH of 6.5(97). Although the final pH was higher than that reported as desirable in the literature(94).

Tenderness

As rigor mortis begins, sarcomeres shorten, and myofibrils undergo transverse contraction, increasing shear force. Within myofibrils, protein density increases in specific areas when the space between myofilaments decreases. Therefore, it is likely that this space reduction reduces the protease activity in the myofibril proteins, affecting meat tenderness (98). The decrease in temperature and pH in the carcass, along with the increase in cytoplasmic calcium, activates proteolytic enzymes, such as caspases and calpains(95), improving meat tenderness. Calpains are responsible for up to 90% of the proteolytic tenderizing of meat(99). Other proteolytic systems in the muscle, such as the lysosomal proteases and the multicatalytic proteasome complex, participate in cytoskeleton proteolysis and meat tenderizing, although to a lesser extent(100). In sheep, some genes have been associated with shear force. Calpastatin (Cast) being the main gene associated with the texture. In Iranian breeds, significant differences have been reported between Cast genotypes (B, C, D, I)(101). Genotype I required a shear force of 8.39 kg; genotype C required 12.69 kg. Sheep with genotype I are more desirable for this parameter. Additionally, a previous study reported a nucleotide variation (197A>T) in exon 6 of Cast, changing amino acid 66 from glutamine (Gln) to leucine (Leu). The heterozygous AT genotype had a lower shear force than the homozygous AA (6.68 vs 8.71 kg). For this same gene, two genotypes were detected on the Awassi breed. These genotypes showed significantly different (P<0.05) shear forces. The MN genotype had a higher force than the MM genotype (4.36 and 3.98 kg, respectively)(102). In Chinese breeds, previous studies have reported the association between Diacylglycerol O-acyltransferase 1 (Dgat1) genotypes and

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tenderness. The TT genotype required a lower force than TC and CC (2.30, 2.69, and 2.73 kg)(103). Also, in Chinese breeds, the association of Fabp4 genotypes and tenderness has been previously reported. The AA genotype was more tender than the AG and GG genotypes (2.24, 2.78, and 2.88 kg, respectively, P<0.05)(97). Lep is another gene associated with this parameter. For example, previous studies have reported the polymorphism of this gene in the Suffolk breed (intron 2, g.103 A>G). The shear force of the AA genotype is lower than that of the AG genotype (3.6 and 4.7 kg, respectively)(96).

Water holding capacity (WHC)

WHC is defined as the ability of meat to retain its total or partial water content (104); it is closely related to the pH and isoelectric point of muscle proteins (pH 5.1-5, net charge 0). Thus, under these conditions, WHC is minimized(98). This parameter is evaluated by drip loss and cooking loss tests. The first test measures the water lost because of gravity(105), i.e., the extracellular water. In contrast, the second test measures the water loss derived from cooking the meat(104). In Awassi sheep, the Cast gene is related to cooking loss, with differences (P<0.05) between the MM and MN genotypes. The homozygous genotype had the highest percentage of water loss (48.45 and 45.69 %, respectively)(102). Moreover, genes associated with the drip loss parameter have been previously identified. For example, three genotypes of the Dgat1gene were identified; the water loss in the TT genotype was lower than that of TC and CC, which showed similar losses (67.1, 92.6, and 92.4 g kg-1)(103). Furthermore, the Fabp4 gene is also associated with this parameter. Of the AA, AG, and GG genotypes, AA had the lowest loss percentage (8.86, 9.48, and 9.39 %, respectively), although there were no significant differences (P<0.1)(97). Polymorphisms of the Calpain small subunit 1 (Capns1) gene have also been associated with WHC. Five genotypes with different water loss percentages (P<0.01) have been identified. The genotype B1B1 had a 4.11 % water loss, while A1A1, A1B1, A1C1, and B1C1 ranged from 2.23 to 3.30 %(14). Additionally, two genotypes of the Insulin-like growth factor 1 (Igf-1) with significant effects on drip water loss have been reported. The homozygous AA genotype lost 2.47 %, while the heterozygous AB lost 3.33 %(106). Furthermore, the polymorphism of the Myostatin (Mstn) gene has also been associated with this parameter. Two genotypes with significant differences (P<0.05) in their water loss percentages have been identified. The AA genotype had a water loss of 2.5 %, while AE lost 3.5 % of water(107).

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Color

Meat color is largely the main attractive factor for the consumer, who perceives this parameter as a sign of freshness and quality; thus, red color in sheep meat is preferable. The color of meat changes as the myoglobin pigments in the meat surface interacts with oxygen, changing from deoxymyoglobin (purple) to oxymyoglobin (red) to metmyoglobin (brown)(108). The CIE-L* (black-white), a* (red-green), and b* (blue-yellow) values have been used to determine meat color. A light reflectance ratio of 630/580 nm is used to detect the chemical changes that result from the oxygenation or oxidation of myoglobin(109). In Merino sheep, significant differences (P<0.05) in the L* reflectance coordinates between Capns1 genotypes (A1A1, B1B1, A1B1, A1C1, and B1C1) have been reported. Genotypes B1B1 and A1C1 showed the lowest and highest luminosity (38.05 and 41.13, respectively)(14). Like calpains, the antagonist of Cast is associated with color. Significant differences (P<0.05) in L* have been observed between the MM and MN genotypes in Awassi sheep; the luminosity of the homozygous genotype was higher than that of the heterozygous (37.60 and 32.47, respectively)(102). In Iranian sheep, two genotypes (A and B) were identified for the Stearoyl-CoA Desaturase (Scd) gene. These genotypes showed significant differences in L* and a*; the B genotype had a higher L* (40.96 and 43.16, respectively) than A, while A had a higher a* value than B (16.0 and 15.08, respectively)(110). In hair sheep, no previous study has evaluated the genes associated with carcass characteristics and meat quality. Therefore, using molecular techniques that evaluate these genes is critical to accelerating the genetic improvement of hair breeds.

Conclusions RFI and RIG are indexes that allow identifying and selecting animals with high feed utilization efficiency. In sheep, a negative effect on the carcass characteristics has not been detected. The heritability of feed utilization efficiency is moderate and is associated with multiple genes. These genes can be used as molecular markers for genetic improvement. Therefore, the study of these indexes and the use of molecular techniques in the selection and breeding of hair sheep could help predict animal behavior. Furthermore, some of the genes related to carcass characteristics and meat quality can be included in the breeding programs of these breeds. This would promote the development of sheep farming since more efficient animals have lower feed requirements without affecting growth rate (RFI), or greater weight gains with similar feed intake (RIG), reducing production costs and increasing the

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profitability of the production units. In addition to producing the quality food demanded by the global market and contributing to reducing the ecological footprint of livestock.

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109. Hunt MC, Acton JC, Benedict RC, Calkins CR, Cornforth DP, Jeremiah LE, et al. Guidelines for meat color evaluation. Kansas State University, Manhattan, KS: American Meat Science Association; 1991:1-17. 110. Aali M, Moradi-Shahrbabak H, Moradi-Shahrbabak M, Sadeghi M, Kohram H. Polymorphism in the SCD gene is associated with meat quality and fatty acid composition in Iranian fat and thin tailed sheep breeds. Livest Sci 2016;(188):81-90.

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Breeds ½D½SI RHS ¾T¼P ½D½SI Dorper Rambouillet Targhee Ghezel Ile de France Targhee Targhee RHS Kurdi Hu Ghezel Hu Hu

Table 1: Production parameters in sheep classified by residual feed intake (RFI) Residual feed intake Low Medium High Low Medium High Low Medium High Daily weight gain Dry matter intake Feed conversion b a 0.280 0.270 1.24 1.41 4.43b 5.15a 0.260 0.240 2.23b 3.22a a b ab b b b a b 0.321 0.277 0.306 1.34 1.35 1.52 4.18 4.90 5.00b 0.284 0.301 0.286 1.25** 1.37** 1.44** b a b 0.266 0.253 2.63 3.00 5.94 6.91a 0.180 0.170 0.180 1.39c 1.48b 1.67a b b a b a 0.350 0.330 0.360 1.92 2.02 2.32 6.58 7.71 7.83a b a b 0.210 0.200 1.01 1.12 4.95 5.53a 0.329 0.335 1.42b 1.63a 4.35 4.93 b b a 0.297 0.302 0.286 2.15 2.31 2.52 b a 0.294 0.293 2.21 2.43 2.10b 2.89a b a 0.260 0.260 1.82 2.11 b a 0.280 0.250 1.50 1.72 b a 0.280 0.290 1.52 1.72 5.47 5.93 c b a c b 0.250 0.260 0.260 1.09 1.25 1.33 4.51 4.84 5.39a 0.260 0.270 1.05b 1.48a 3.92b 5.62a

DDMI % 12.06 30.74 11.84 13.19 12.33 16.77 17.24 9.82 12.88 14.68 9.05 27.34 13.74 12.80 11.63 18.04 29.05

Author 5 6 37 38 39 40 45 46 47 48 49 50 51 52 53 54 55

DDMI= Difference in dry matter intake (%), ½D½SI= ½Dorper ½Santa Inés, RHS= Rambouillet, Hampshire, and Suffolk, ¾T¼P= ¾Texel ¼Pantaneira. **, abc= Significant differences.

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Breed ½D½SI ¾T¼P ½D½SI

Table 2: Production parameters in sheep classified by residual intake and gain (RIG) Residual intake and gain Low Medium High Low Medium High Low Medium High Low Medium Dry matter intake Daily weight gain Feed conversion Feed efficiency a b b a a b 1.39 1.31 0.26 0.30 5.32 4.28 0.19b 1.28 1.27 1.22 0.26b 0.29a 0.31a 4.99a 4.28b 3.91c 0.20c 0.24b 1.41 1.37 1.31 0.26** 0.29** 0.30** 5.36* 4.61* 4.27* 0.18* 0.21* ½D½SI= ½Dorper ½Santa Inés, ¾T¼P= ¾Texel ¼Pantaneira, *= Calculated data, **, abc= Significant differences.

548

High 0.23a 0.26a 0.23*

Author 5 36 38


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Table 3: Genes associated with sheep feed efficiency and meat quality Symbol

Glis1

Sox5 and Sox6

Gene

Glis Family Zinc Finger 1

Chrom

1

SRY-related box -5 and -6 transcription factor

15

Interleukin 1 Il1rapl1 Receptor Accessory Protein Like 1

X

Lepr

Leptin receptor

1

Trdn

Triadin

8

Biological process Significantly promotes human and mouse fibroblast reprogramming into induced pluripotent stem cells during embryonic development. It is highly expressed in the fertilized ovum, moderately expressed in metaphase II oocytes, and weakly expressed in two-cell embryos. Additionally, this gene is associated with the regulation (including the transcription factor Foxa2, several genes of the Wnt and Esrrb families) of genes involved in the mesenchymal-epithelial transition, a crucial process in somatic cell reprogramming. Its expression is related to an efficient process of chondrogenesis, although the Sox9 gene is required to activate and maintain chondrocyte-specific genes. The Sox5 and Sox6 genes significantly increase the transcriptional activity of Sox9, ensuring its binding to DNA. Related to intellectual disability and autism spectrum disorders promoted by the absence of the Il1rapl1 protein. Mutations in Il1rapl1 result in the absence of the protein or the production of a dysfunctional protein in humans. It produces a protein of the same name that, when combined with Leptin, triggers a series of chemical signals (JAK/STAT signaling pathway) that activate the receptor and transphosphorylate the JAK molecules associated with it. This pathway participates in energy homeostasis. It regulates the release of Ca2+ through the Ryr2 and Casq2 calcium release channels in the sarcoplasmic reticulum; this is a crucial step

549

Param

Author

RFI

68-70, 87

RFI

71, 88

DWG

72-74, 89


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Oxsm

Mitochondrial 3oxoacyl-ACP synthase

26

Rarb

Retinoic acid receptor beta

26

Lep

Leptin

4

Gh

Growth hormone

11

Mc4r

Melanocortin-4 receptor

23

Adra2a

Alpha-2A adrenergic receptor

22

for the contraction of the skeletal and cardiac muscles. In humans, the lack of triadin results in cardiac arrhythmia with sudden cardiac death. An enzyme related to the synthetic α-lipoic acid pathway. Its activity is essential for the elongation of the fatty acid chains in the production of α-lipoic acid. α-lipoic acid deficiency represents a risk factor for diabetes. Overall, retinoic acid receptors are essential for retinoic acid signaling during embryonic development and organogenesis. Mice lacking two isotypes of Rara, Rarb, Rarg show some characteristics of vitamin A deficiency syndromes in fetal and postnatal stages, as well as some congenital malformations. Hormone synthesized in the adipose tissue with an important role in the regulation of appetite and energy metabolism. Additionally, leptin has been linked to fat deposition in mammals. Activates anabolic processes that regulate the increase in body size and skeletal growth. It controls and coordinates the flow of metabolic processes, such as stored fat mobilization and fatty acid and glucose catabolism in tissues. This receptor is predominantly expressed in the hypothalamic appetite regulator nucleus; it regulates food intake and energy homeostasis. Catecholamine regulator; associated with energy metabolism. This receptor also participates in the adrenaline pathway and can regulate energy metabolism through the secretion of adrenaline, which affects FC.

550

DWG

DWG

DWG FC pH Tenderness

75, 90 75, 88 75, 96

DWG

76, 91

DWG

77, 92

FC

51, 55, 72, 78


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Ryr2

Ryanodine receptor 2

25

Pde8b

Phosphodiesterase 8B

7

Gfra1

GDNF family receptor alpha 1

22

Fabp4

Adipocyte fatty acid-binding protein

9

Capns1

Calpain small subunit 1

14

Cast

Calpastatin

5

Dgat1

Diacylglycerol Oacyltransferase 1

9

Main channel of Ca2+ release from the sarcoplasmic reticulum in ventricular myocytes. This receptor is related to heart disease. This receptor also participates in the adrenaline pathway and can FC regulate energy metabolism through the secretion of adrenaline, which affects FC. This gene encodes a cyclic adenosine monophosphate-specific phosphodiesterase that regulates thyroid-stimulating hormone levels. The thyroid synthesizes thyroxine, which binds to the FE receptors to control biological processes, such as gene expression, 79-81, growth, development, and metabolism. 93 Associated with the tyrosine kinase receptor, which regulates cell proliferation, growth factors, and neuronal development and FE differentiation. Known as intracellular lipid chaperons, they bind and transport pH long chain fatty acids in mammals. In cattle, these proteins are Tenderness 82, 97 associated with growth, fat deposition, and carcass traits. WHC Mainly associated with the postmortem degradation of myofibrillar WHC proteins and the production of free amino acids, resulting in meat 20, 14 Color tenderization. This enzyme inhibits calpain activity and is related to the 20, Tenderness regulation of muscle protein degradation. The inhibition of muscle 101,102 protein degradation by the calpastatin system increases production WHC 20, 102 efficiency but affects meat tenderness. Color This enzyme modulates the synthesis of triglycerides and regulates Tenderness their circulation. Additionally, it is directly related to glucose 83, 103 WHC metabolism, obesity, insulin resistance, and hepatic steatosis.

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Igf-1

Insulin-like growth factor 1

3

Mstn

Myostatin

2

Scd

Stearoyl-CoA Desaturase

22

This protein participates in the control of skeletal growth and cell differentiation by activating the cell cycle. Myostatin is a potent negative regulator of muscle mass in mammals. The natural mutations in Mstn inactivate or suppress the protein, which increases musculature. The skeletal muscles affected by these mutations increase their myofibrils (hyperplasia) and, to a lesser extent, the cross-sectional area of the myofibers (hypertrophy). These mutations have a greater impact on homozygous individuals compared to heterozygous individuals. It regulates lipid synthesis and oxidation.

WHC

84, 106

WHC

85, 107

Color

86, 110

Chrom= Chromosome, Param= Parameter, RFI= residual feed intake, DWG= daily weight gain, FC= feed conversion, FE= feed efficiency, WHC= water holding capacity.

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https://doi.org/10.22319/rmcp.v12i2.5821 Review

Bioelectrical impedance analysis (BIA) in animal production: Review

Larissa Luísa Schumacher a* Julio Viégas a Gilmar dos Santos Cardoso a Anderson Bertoluzzi Moro a Tiago João Tonin a Stela Naetzold Pereira a Leonardo Tombesi da Rocha a Ana Luiza Van Caeneghen a Janaína Vargas Teixeira a

a

Federal University of Santa Maria. Department of Animal Science. Santa Maria, Brazil.

*Corresponding author: larissaluisaschumacher@gmail.com

Abstract: Bioelectrical impedance analysis (BIA) is a method based on the different levels of opposition to the flow of an ionic current through the different body tissues. Results are expressed by primary measures of resistance (Rs) and reactance (Xs). From such measures, equations are applied to determine the phase angle (PA) and impedance (Z). Bioimpedance analysis has been indicated as a reliable and precise method to determine the body composition and nutritional status in humans. BIA has recently been adapted to be applied on animal production. Therefore, the aim of this review is to provide an analysis on the potential use of bioelectrical impedance on zootechnical production. Through BIA, correlations among bioelectrical measures and tissue composition of swine, bovine, ovine, bubaline and fish carcasses can be established. In this regard, a growing number of demands were led by more precise and cost-effective methods to evaluate the body composition in the zootechnical sector, in which the analysis of

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bioelectrical impedance proved to be a promising and minimally invasive technology to replace traditional methods. Key words: Body composition, Impedance, Technology, Zootechnical production.

Received:02/10/2020 Accepted:10/03/2021

Introduction The pursuit of excellence in quality within the zootechnical chain in Brazil and in the world has been constant. To maintain the status quo, the emphasis should be placed on the use of technologies to guarantee the biosecurity of food on animal production adaptable to consumer requirements. Different methods to evaluate the quality and composition of the most diverse meat and milk products are available in the literature. However, many of these methods, such as carcass dissection and physical and chemical composition require skilled and qualified labor, state-of-the-art equipment and considerable financial funds. Hence, research and exploration of technologies and methodologies are fundamental to help evaluate efficiently the quality of zootechnical products. In view of that, bioelectrical impedance (BIA) is characterized for being a technology of quick measurement, minimally invasive, relatively cost-effective and less subjective. BIA shows great potential to predict tissue chemical composition of farm animal carcasses(1) as well as to evaluate the quality of raw cow milk(2). BIA analysis is based on the principle that body tissues have different impedances, it means an opposition to the flow of an ionic current. Such impedance is determined by primary measures of resistance (Rs) and capacitive reactance (Xc). The flux of the electric current opposes to the vector Rs, when it goes through intra and extra cellular environments(3). Similarly, Xc also shows opposition to the current flux caused by the capacitance produced by the cell membranes(4). Hence, the search for alternative methods becomes necessary to determine and uphold the quality of zootechnical products if we are to consider the current juncture. In this regard, this article review aims to relate and unveil the principle of BIA and its use in animal production.

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Electric bioimpedance Body tissues have different levels of conductivity and opposition to the flow of an ionic current due to their chemical-physical composition(4). From this principle, the analysis of electrical bioimpedance is carried out as a method of evaluating body composition, nutritional condition, total amount of body water, physiological properties, and an indicator of several clinical and pathological situations, such as prognostic of cancer, malnutrition and cardiac insufficiency(5). This method is relatively cost-effective, minimally invasive and of easy handling and applicability. It also offers quick measurement since it takes approximately 5 sec to gather the data(6). Besides, differently from traditional methods, BIA does not require the sacrifice of animals to evaluate tissue composition and energetic level unless dissection is performed when applicable(7). The principles of BIA have been applied and adapted for animal production to determine the tissue composition of swine(8), bovines(9), ovine(10,11), bubalus(12) carcasses as well as to evaluate the composition of raw cow milk(2). To use BIA, an ionic current should pass along the animal body. The current is usually alternate of low amplitude (500 to 800 μA) and high frequency, which cannot be felt by the body. It usually takes four electrodes (a tetrapolar system) to apply the current: one pair of electrodes produces the current excitation while the other pair measures the difference in the potential reached(13). In biological systems, humans or animals, the displacement of the current occurs through the dissolved ions in the body fluids, especially ions of sodium and potassium. The literature shows that when the current is applied to the bioimpedometer, the different animal tissues present different opposition to the flow of the ionic current, which is called impedance (Z). The value of the impedance is frequency dependent(4) and is the resultant composition of two vectors named resistance (Rs) and reactance (Xc). When the current is applied, it disperses through the ions in the body fluids and is inversely proportional to its motility and directly proportional to the area that it traverses. From the primary values of Rs and Xc obtained by the bioimpedometer, the mathematical model proposed by Lukaski et al(14) is used, showing dependence on the length of the conductor, on the frequency used and on the area of transversal section, in other words, the body volume: Z = (Rs² + Xc²)0.5. The magnitude of the impedance is calculated by the square root of the sum of the squares of resistance and reactance combined to the circuit(14); all measures are expressed in ohms (Ω). The resistance occurs because of the opposition to the electric current when flowing across intra and extracellular environments(3). The opposite can be obtained by the

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conductance (C). According to Eickemberg et al(4), this is inversely related to resistance (C=1/Rs), that is, the larger the amount of liquid, the weaker the current flow opposition. Therefore, the resistance shows opposite behavior to the amount of water in the body and the level of hydration in these environments. Intracellular fluids are composed by nucleus and cytoplasm mostly formed by salts, proteins and water, considered good electrical conductors. Likewise, conductive materials, such as K and PO-4 ions(15), also form the extracellular fluids. The same applies to lean tissues formed by muscles and viscera, which are good conductors of ionic current due to their large amount of water and electrolytes. Adipose and bone tissues, on the other hand, conduct ionic current with less intensity, when compared to the muscles and viscera, being highly resistant(16). If the tissues were homogeneous, the opposition would be only resistive. However, the tissues are heterogeneous and show another type of opposition, the reactance, which originates from tissues that show composition and characteristics of electric capacitors (condensers) in their structure produced by the cell membranes. Cell capacitance is known as an energy storage property (to concentrate electrons) in tissue interfaces and cell membranes for a short period, having the characteristic of delaying the electric current(17). Cytoplasmic membranes involve two layers of protein material with hydrophilic properties, proving to be good electric conductors, and a lipid-insulating layer (the dielectric layer). Those membranes act as if they were a capacitor (Xc)(4). This assessment is an indicator of body lean mass quantity, which can be related to the structure and function of cell membranes since each tissue component responds differently to the flow of an alternate applied current(18,19). The BIA method considers that a singular cylindrical conductor with homogenous length and transversal area represents the animal body. Nevertheless, such statement is objectionable once the composition and transversal section areas are considered heterogeneous(20). Hence, it is necessary to relate BIA with proven methods in the literature to determine chemical and physical compositions so that it is possible to validate the method and its respective prediction equations, identify and narrow down errors and make technology more reliable and precise(21). Since BIA analysis can also provide information on body composition, factors such as body and environment temperature, and length of body segment must be taken into consideration. According to Hartmann et al(22) temperature and length affect significantly the measurements of resistance and reactance, which is explained by the temperature increase that boosts the vibration of the atoms.

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Considering the nature of the biological fluids, the temperature exhibits a negative coefficient for resistance, that is, when the temperature decreases the resistance increases. Consequently, the conductance decreases proportionally(6). Other variables can also interfere on the serum concentration of electrolytes, electrode placement spots, types of electrodes used, training of users on the bioimpedometer application, use of nonconductive materials, calibration of the device as well as breed, age and weight (3,10). In this regard, impedance values are associated to the total amount of water and the composition of body tissues in animals(6). Besides, the impedance can also be used as an indirect method to assess the bacteriological quality in raw milk.

Phase Angle

Whenever an electric current is applied to biological tissues, a detour is formed as soon as the current traverses the cell membranes. Part of the membranes has the ability to store energy, which means that there should be an observable delay in the electric current flow due to capacitance, generating a decrease in the current tension(23). This characteristic originates a phase change since there is no synchrony in the capacitor between the variations of current and tension, generating a geometric transformation of the angle of the capacitance under the designation of phase angle (PA)(4). According to Cintra et al (3), the phase angle determined by BIA is a method to measure the relation existing between the resistance and the reactance in series or parallel circuits. Eickemberg et al(4) explained that there might be variation from 0º to 90°, in which 0º involves a resistive circuit without any cell membrane or degradation, and 90º corresponds to a capacitive circuit in which all cellular membranes have extra cellular fluid. PA depends on the capacitance and is negatively associated to resistance(24). It is related to quality, size and cellular integrity, given that its variation indicates alterations in the body composition, in the functioning of the membrane or in human health conditions(4). Therefore, PA can be quantified geometrically by the formula PA = (Xc/R), calculated by the relation between the arc tangent of Xc and Rs, where the result obtained is expressed in radians, being multiplied by (180°/π ≅ 57,296) to convert in degrees(25). The equation, according to Baumgartner et al(24), is the following: AF = [tan-1(Xc/R) x 180°/π]. Eickemberg et al(4) set as a value of normality for healthy individuals a variation between 4 and 15 degrees. According to Selberg and Selberg(26), when the values of PA are higher, the reactance values show the same tendency. These, in turn, are related to good health conditions and intact cell membranes. Contrarily, when PA rates are low, there is a relation with reactance, associating them to cell death, reduction of cell membrane selective permeability and even to the existence or worsening of some disease(27). When the assessment was performed in fish, Cox and 557


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Heintz(28) described that the angle exceeding 15º indicated that the animals were in good health conditions whereas the angle inferior to 15º indicated that health conditions were compromised. In this context, PA has been widely used as an indicator of the nutritional condition in human beings as well as in animal carcasses, of quality assessment and raw cow milk adulteration(1,2,9).

BIA for body composition and carcasses evaluation of farm animals The evaluation of the body composition is frequently used to improve management and zootechnical control on farm animal sector, enabling the responsible technician and raiser to select animals with higher performances, adapting them for the consuming market(16). The most commonly used methods to predict the composition and the carcass of living or slaughtered animals are often time-consuming, expensive and invasive(10). Consequently, researching about new methodologies and precise technologies is fundamental to meet such estimation. In this regard, BIA is a method minimally invasive, relatively inexpensive and one that has been used in the zootechnical sector to estimate the body composition of farm animals. In humans(4) BIA is used to assess the body mass index (BMI) since it considers the association between weight and the patient's squared height (BMI = weight/height²). Lukaski et al(29) , based on the principles of Ohm's law, related the cross-sectional area with the body volume, describing that the volume of a conductive mass can be the quotient between squared height and resistance (V= height² / LOL). Aiming to reproduce the equations of volume used in humans for animals, Jenkins et al(30) replaced the height by the length of the carcass. Others(31), replaced the height by the length of the conductor, represented by the distance between the electrodes that detect the current. Zollinger et al(9) associated in their studies the body compositions of animals and the resistive (RDs) and reactive (XDc) densities and described the relation between the weight, the resistive and capacitive volume, expressed in Kg²/cm² ohms. By assessing the potential use of BIA to determine the composition of the soft portion of carcasses of hot and cold lambs, Moro et al(32) verified that BIA measurements obtained from cold carcasses anticipate its components with higher precision than measurements obtained from hot carcasses. Such fact is explained by the decrease in conductance in response to loss of fluids during the cooling, and changes in the distribution of electrolytes between intracellular and extracellular environments in tissues.

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Acupuncture or hypodermic needles can be used as electrodes to perform the measures. They should be inserted in the animal under constant penetration depth, enabling the transmission without interruption of signal throughout the tissues(11). Besides, there should be extra care when animals are laid on non-conductive surfaces.

To make the relation of the variables of BIA with the body composition of animals possible, one should determine the levels of moisture, protein, mineral matter and lipids in the laboratory, among others. The position of the electrodes supposed to obtain the primary BIA measures performed in the back of the animals showed more accurate results than the ventral readings due to the differentiated tissues that each compartment shows(21).

Significant changes are neither found in the variables of BIA nor in the membranes or extracellular compartments right after the slaughter, considering that the temperature shows little variation. Nevertheless, when the carcass starts to cool, biochemical changes in the cell membranes occur due to the rigor mortis effect as the carcass loses its ionic gradients with the raise of the temperature and time lapse of maturation(33).

According to Bertotti(33), this process is consistent with the enzymatic mechanisms since the phospholipid layers of the membranes suffer oxidation and give the membrane a porous aspect. Such mechanism described by Damez et al(34) causes an increase in permeability, facilitating the flow and mixture of the intra and extracellular fluids. Swentek et al(35) reported that the values for Rs and Xc in cold swine carcasses were approximately from 6 to 11 times higher than the ones in living swine, in addition to observing that Rs decreased proportionally to the temperature.

Altmann et al(10) obtained very weak correlation between the reactance and the composition of the carcass, what can also be found in studies with lamb(31). Others(8), found a positive correlation among the resistance, live weight and amount of fat in swine. Consequently, there was an increase in the resistance due to the decrease of total amount of water in the body, resulting the raise of weight and fat in swine.

Gibbs et al(36) found changes on the fat-free mass and on the fat-free soft tissue caused by stress when they used BIA to determine body alterations in newborn lambs exposed to intrauterine heat stress. Likewise, it was observed that BIA showed potential to estimate marbling in bovines in Japan(37). Berg and Marchello(31) used the following variables in their models: weight of cold and warm carcasses, length of the carcass and temperature associated with Rs and Xc. Some 559


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researchers(9) reported that they obtained weak relationship amongst most of the components of the carcasses. Moro et al(1) added phase angle, bioelectric volume, resistive and reactive density to their equations to associate with the components of the carcass since the resistive density can be related to these components and the reactive density might indicate the association with the concentration of lean mass.

In addition, Silva et al(38), when using BIA analysis as a technique for the prediction of the carcass and muscle of light goats, observed that Rs was the only independent variable that determined subcutaneous fat with prescription. However, by including the carcass length combined with Rs in the model, they obtained an even higher level of determination, 0.943 (P<0.01). To predict the amount of muscle, the insertion in the cold carcass weight equation combined with Rs, reported an accuracy of 0.998.

In a recent work(39), the authors showed the potential the parameters evaluated by BIA have to measure meat characteristics: the combination of Rs and Xc to predict intramuscular fat demonstrated adjustment of 79.3 % while for the physical-chemical characteristics the best adjustments were in the length of the sarcomere with 64.4 % and shearing force of 60.5 %.

The accuracy of prediction models improved with the inclusion of more information. Some models are shown in Table 1 along with their respective variables, which best adjusted to increase the capability to determine equations.

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Table 1: Prediction equations from in vivo evaluations, of bioimpedance, in the carcasses of bovine, bubalus, lamb and swine Authors

Dependent Variable

Equations

Bovine Velazco et al., 1999 Bubalus

Fat-free Mass

Y= 0,130 BW − 0,039 L + 0,0002 L2 − 0,007 Z − 0,98 9,320 Vol2 + 9,507 Vol3 + 35,555 BMI − 34,249

Sarubbi et al., 2008

Fat-free Mass

Y= 28,10 + 0,972LW + 12,21

0,94

Y= 0,555 LWt - 0,247 Rs + 0,390 Xc + 16,260

0,77

Y= 0,555 LWt - 0,247 RS + 0,390 XC + 16,260

0,78

Y = - 0,70 + 0,05RsD + 0,03V + 0,07PA Y = - 2,11 + 0,10RsD + 0,04V

0,91 0,87

Y = - 1,90 + 0,11V + 0,18RsD + 0,31PA

0,89

Y= 18,8+0,023 LW−10,5 L²/R

0,85

Y=1,43+0,001 LW−0,81 C

0,65

Lamb in vivo Berg and Marchelho, 1994

Moro et al., 2019

Avril et al., 2013

Fat-free Mass Fat-free Adipose tissue Protein (kg) Fat (kg) Lean mass (kg) Fat-free Mass (kg) Fat Mass (kg)

Lamb Carcass Fat-free Mass Berg and Marchelho, 1994

Fat-free Adipose tissue

Y= 0,439 HCWt + 0,167 L - 0,134 RS + 0,191 XC - 0,258 T + 19.914 Y= 0,583 CWt + 0,150 L - 0,027 RS + 0,013 XC 0,287 T + 1,836 Y= 0,433 HCWt + 0,124 L - 0,114 RS + 0,175 XC - 0,211 T + 17,811 Y= 0,555 CWt + 0,096 L - 0,022 RS + 0,008 XC 0,278 T + 3,868

0,77 0,77 0,79 0,77

Swine Swantek et al., 1992

Fat-free Mass Fat-free Mass (Cold)

Y= 0,486 LWt - 0,881 RS + 0,480 L + 0,880 XC + 0,81 7.950 y= 0,267 CWt - 0,158 RS + 0,519 L + 0,103 Xc + 0,83 20,04

Independent variables: BMI= BW 2/L2; BMI= Body mass index; BW= Body Weight; C= Conductance; CWt= Cold carcass Weight; HCWt= Hot carcass Weight; L= Length; LW= Live weight; PA= Phase Angle; Rs= Resistance; RsD= Resistive density; T= Temperature; V= Bioelectric volume; Vol2= L2/ (Rs 2 + Xc 2).5; Vol3= Geometric volume; Xc= Reactance; Z= Impedance.

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It is possible to evaluate BIA in the whole extension of the carcasses. However, some restrictions present during the measure of bioimpedance brought forth the need to assess the analysis of BIA by segments, in other words, by small sections in the carcasses. To provide precise information and meet the demands of the consumer market, Moro et al(32) reported recently that the analysis of bioimpedance proved to be a promising technology when compared to traditional methods, for it provides an easy and quick way to determine the composition of fat, protein and composition of water in commercial cuts. However, to produce more accurate information and meet the demands of the consumer market, such as the composition of fat, protein and water composition in commercial cuts, Moro et al(32) described that bioimpedance analysis proved to be a promising technology to replace traditional methods.

BIA assessment in fish

Electric bioimpedance can be a useful tool not only for scientific studies on fish, but also for the pisciculture industry, considering that the body composition of a great quantity of living fish could be quickly evaluated(40). Besides, its use could result in 20 to 41 times reduction in the total cost of the assessment procedures when compared to the traditional methods of chemical analyses. Wuenschel et al(41) reported that by means of this technology, since it is not lethal, it is possible to monitor the changes in the body composition of fish as they grow and make changes in the diet, according to BIA evaluation of the responses to biological interactions. Another important finding(42) is that BIA can be useful to analyze the biotic and abiotic variations that can affect the body's constituents of animals, which in turn cannot be sacrificed, as endangered species. According to some authors(43), the body geometry of fish favors the use of impedance as estimation of body composition, where an only measure can precisely represent the whole body (R²= 0.96). Aiming to use BIA analyses to determine the body composition of fish, Zaniboni-Filho et al(44) treated the fish with a diet composed by different rates of lipids (8.90% vs 18.68 %) to produce individuals with different body compositions. The results showed stronger correlations for the dorsal analyses of moisture and resistance in series (0.87); protein and resistance in series (0.87); ash and reactance in parallel (0.82). Weak correlations were observed among BIA data by ventral reading with the lipidic contents (0.44). These authors emphasized that BIA proved to be a proper method to determine the body composition of fish in accordance to the authors previously mentioned.

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Arantes(7) tested the use of Bioimpedance technique in Piava fish (Leporinus obtusidens) and found high level of the coefficient of determination obtained in the lateral region. The coefficients were respectively 0.92, 0.85 and 0.87 among BIA method and the parameters of body composition obtained by the chemical method, such as moisture, protein and ethereal extract. These results showed that BIA proved to be valid to estimate body composition and qualify the levels of energy of Piava fish. The effectiveness of BIA to evaluate fish composition is beneficial for fishing management and ecological investigations. It enables the evaluation of the energetic flow among and within populations, besides assessing the answers regarding environmental changes. Traditional measurement methods, although highly accurate, are time-consuming, expensive and lethal. On the other hand, BIA method represents a quick and non-lethal technique, which, explaines 80 % of the variability in the percentage of lipids in fish, demonstrating high accuracy in estimating and monitoring the body conditions of fish that live in rivers in inland Alaska territory(45). In addition, the technique can be beneficial for determining bioenergetic changes related to variations in the environment. Fitzhugh et al(46) used BIA to establish a relation with the energy available for the reproduction of sea fish. The authors observed that the phase angle remained less than 15º after the peak spawning season. Hartmann et al(40) reported that BIA showed potential to measure the reproductive status, maturity and gonad development, for under these conditions fish present alterations in their body fat percentage. According to some authors(28), phase angles measuring more than 15º indicated that the fish were healthy, while values of less than 15º showed fish with compromised health due to changes in the aquaculture environment. Differently from the models used for other animals, the phase angle showed high productivity among fish. Changes on the phase angle are also found when the fish face a long period of fasting. The fast forces the organism to use the nutrients stored to meet their energetic needs(47). The use of stored nutrients causes changes in the intra and extracellular fluids, loss of body protein, progressive cellular dehydration and decrease of phase angles. Furthermore, Zavadlav et al(48) suggested estimating the storage length and sensory properties of the squid samples with FA measurements, since they showed close correlation. On the other hand, it was observed(49) weak and non-significant correlations among PA, Rs and Xc and the components of body composition, reporting that the reason for the weak correlation is that the methodology of BIA was not able to detect alterations in body composition of fish. This fact corroborates the results of other authors(50), in which the morphological measures estimated by BIA in fish that face threat of extinction in inhabiting deserted regions were redundant, demanding caution in the field evaluation, as it presents great sensitivity. 563


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According to Cox et al(21), fish can be kept in ice for up to 9 h after being slaughtered with no alteration in Rs or Xc. Delays in freezing affect first Xc, then Rs and PA. This order is due to Xc representing the integrity of the cell membrane, which after 12 hours starts to swell in the face of rigor mortis. Thus, the cell membrane bursts releasing intracellular liquid in extra cellular spaces. To meet the demand of the consumer market, Fan et al(51) found that it is possible to define the quality, freshness and muscle softening of rainbow trout by means of impedance and during storage on ice. The same authors described that the procedure enabled the detection of the rigor mortis index via impedance, condition in which a strong and negative correlation between rigor mortis and (K) potassium (r = −0.938, P<0.01) was evidenced and a strong positive correlation was found with r= 0.981 (P<0.01) regarding hardness. Some similarity was described by Yuan et al(52), who demonstrated that the bioimpedance analysis showed a good correlation with the value of K after 24 h of storage in ice, suggesting that BIA effectively reflects the change in the biochemical compounds related to the freshness of fish meat. To narrow down errors during the research, Hartmann et al(40) recommend that the minimum sample should be of 60 fish and a minimum layer of fat of 29 % among fish to obtain correlations ≥ 0.80. Therefore, the results might show higher reliability to estimate the body composition of fish. However, the assessment of potential sources of errors and variations during BIA measurements is an important step in the protocol development to ensure the application of data obtained by this method. Champion et al(42) evaluated some challenges that the technique presents. For the technique to be effective, the authors suggest some criteria to be followed: the anatomical location of the electrode insertion; the fish size and variation among species; the environment/body temperatures; the time length between capture and death of the fish; the degradation of post-mortem biological tissue; the standardization of the catching method to reduce physiological stress. According to Cox et al(21), a change in the electrodes on the dorsal to the ventral side of a fish changes not only the distances between the electrodes, but also the types of tissues that are examined. Hafs and Hartmann(53) identified better correlations among BIA and tissue components when the electrodes were placed along the dorsal line. The fact that the fish have large and thick scales and might impair the contact between the skin and the electrode, some scales might have to be extracted. In short, the use of BIA in fish has shown promising results to estimate the body composition. However, further studies are needed to develop protocols and prediction equations to enhance the accuracy and applicability of this technique to a level that allows its use on field and in the industry.

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Assessment of BIA in bovine milk

Current analyses to verify the quality, composition or even the adulteration of milk are performed mostly by analytical methods in certified laboratories. Within the environment of a laboratory, however, it is hard to carry out tests and offer real-time prediction for the technicians. Therefore, it is important to develop new methodologies to monitor the composition and quality of milk to fulfill the expectations of the consumer market. It is useful and promising to use the electrical properties of milk. Hence, Felice et al(54) suggested a method of quantification of bacteria in raw cow milk based on the variation of electric capacitance. Mabrook et al(55) observed that the electric conductance decreases as the percentage of fat in the milk raises. It was reported(56) that when the temperature of the milk was raised, the mobility and the number of ions in the solution also raised, causing a decrease in Z. This validates the results found by others(2), who reported the same similar results. The fat from the milk can be considered an obstacle for the flow of the electric current, since large globules covered by a thin and non-conductive membrane form fat. Milk with high percentage of fat showed high resistance and consequently low conductivity(57). The strong correlation between the conductivity (C) and the milk somatic cell count (SCC) should also be noted. The raise in milk’s C is directly proportional to the increase of the udder inflammation and SCC. This inflammation causes alteration in the tissues permeability, resulting in a raise on the flow of Na+ and Cl- ions from the blood to the interior of the alveolar lumen of the mammary gland(58). It was observed strong correlations among the variables Rs, Xs, C, Z and PA and the total solid-not-fat components in raw cow milk, also coinciding with the coefficient of determination of the prediction equations(2). In the same study, when the temperature of milk was at 5 ºC, the average of Z was 147 ohms and 1.21 % of fat. Veiga et al(59) found different average values for Z in whole milk (219.56 ohms), semi-skimmed (203.57 ohms) and skimmed (170.08 ohms) when they analyzed the electric bioimpedance of cow milk fat. Other authors(60) reported average values of 89 ohms for Z. It was developed an impedance spectroscope sensor to detect adulteration of milk based on the measures of PA(61). In this study, the PA decreased when water from the tap was added. As the values for pH changed towards a basic solution, the PA and the conductivity also decreased. When urea and whey were added, the PA and the conductivity showed a raise. This is because the variables have the same nature. In other words, the nature of the change in PA is the same of the conductivity. Durante et al (56) observed that the adulteration of the composition of raw cow milk and UHT milk (ultra-high temperature) differed chiefly in the variable resistance. Raw milk 565


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showed little variation in face of adulteration by hydrogen peroxide. However, the adulteration was present in the samples of UHT milk. Such fact was possibly related to the fat rate and a lack of homogeneity of the raw milk. Sodium hydroxide samples showed tendency to decrease the resistance due to a larger presence of Sodium ions, demonstrating that the spectroscopy system showed consistent results concerning adulteration of cow milk. Methodologies to identify the composition, adulteration and conductivity of milk(56) using spectroscopy of impedance(62) and conductivimeters are different from BIA. It is important to emphasize that the technique of spectroscopy of impedance can provide data on the structure and composition of milk properties by means of different electric frequencies. BIA, on the other hand, uses an alternate current of low amplitude (500 to 800 μA) and high frequency (50 kH). Aspects such as breed, stage of lactation, genetics, and nutrition milking frequencies, age of the animal as well as the recipients and types of electrodes should be considered when bioimpedance of cow milk is analyzed. In this sense, the use of spectroscopy or simply bioimpedance in single frequency are promising techniques, which might provide quick and cost-effective results concerning composition, quality and potential adulteration of cow milk.

Conclusions The growing increase in the demands of the consumer market toward food safety, wellbeing and composition of products of animal origin highlights the need to investigate precise and cost-effective methods that assure quality. Bioimpedance analysis, thus, proved to be a promising, fast, relatively inexpensive and minimally invasive technology to characterize and predict the body composition of domestic animals and the quality of raw bovine milk, showing great capacity for replacing traditional methods. Nevertheless, in order to expand the use of BIA, it is important to highlight the need for controlling, as much as possible, the potential sources of errors and variations, regardless of the species used to define protocols and standardize the analysis. Moreover, further research is needed to assess the interaction of BIA with the variation of the most diverse environments and nutritional status. To ensure information and models that are more accurate, it is recommended to associate BIA data with modeling methods and statistical packages. Hopefully, in the near future, BIA can be used both in the field and industrial plants.

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Acknowledgements

To Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) for the scholarship granted to the first author.

Conflict of interest declaration

The authors declare they have no conflicts of interest with the work presented in this review article.

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https://doi.org/10.22319/rmcp.v12i2.5623 Technical note

Chemical and biological additives in high moisture triticale silages: Nutritional value and ingestive behavior in sheep

Valter H. Bumbieris-Junior a Egon H. Horst a* Murilo D. Paranzini a Odimári P. P. Calixto a Edson L. A. Ribeiro a Leandro D. F. Silva a Ivone Y. Mizubuti a Clóves C. Jobim b Mikael Neumann c

State University of Londrina, Center of Animal Science – Rod. Celso Garcia Cid, PR445, 86057-970, Londrina, Paraná, Brazil. a

b

State University of Maringá, Center of Animal Science, Maringá, Paraná, Brazil.

c

Midwestern Parana State University, Departament of Veterinary, Guarapuava, Parná, Brazil.

*

Corresponding author: egonhh@yahoo.com.br

Abstract: Triticale high moisture grain triticale silage is an excellent option for ruminant diets, but loss control during its fermentation process should be further investigated. Thus, the objective of this study was to evaluate the effects of chemical and biological additives on high moisture triticale silages under chemical-bromatological composition, aerobic stability, and in vivo digestibility and ingestive behavior in sheep. The treatments were: high moisture triticale silage without additive (HMTC); high moisture triticale silage with

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enzyme-bacterial inoculant (HMTEB); high moisture triticale silage with 0.5 % urea in natural matter (HMTU); and high moisture triticale silage with 1.5 % sodium benzoate in natural matter (HMTSB). Four sheep were housed in appropriate metabolic cages according to the ethical principles of animal experimentation. The addition of urea as additive to high moisture triticale silage provided an increase in crude protein and ammoniacal silage (189.7 and 106.2 g kg MS-1, respectively) but did not affect digestibility (699.6 g kg MS-1 for HMTU, with a general average of treatments of 687.5 g kg MS-1) and ingestive behavior of sheep. Fiber consumption by sheep increased with the addition of the enzyme-bacterial additive in the silage (431.87 versus 388.06 g d-1 of FDN for HMTEB and HMTC, respectively). All additives helped to preserve crude protein contents after silo opening, but none interfered in aerobic stability time of silage. Key words: Sodium benzoate, Nutritional quality, Aerobic stability, Enzyme-bacterial inoculant, Urea.

Received: 20/02/20 Accepted:04/08/2020

High moisture triticale silage shows potential for substitution or supplementation in ruminant diets, mainly because it has higher solubility of the starch(1) and higher levels of lysine(2) when compared to maize. However, the high epiphytic concentration of yeast present in the triticale grain(3) favors nutrient losses and decrease the aerobic stability of silage after silo opening. Linked to this, the use of chemical additives, such as sodium benzoate and urea, have been tested for control of these deteriorating microorganisms and consequent maintenance of food quality. Sodium benzoate has been tested for quality control of silages in low doses, due to concerns about possible sterilization of the food, which would impair its fermentation process(4). However, these claims are contradicted by other authors(5). Under the same view, Jobim et al(6) reported that addition of urea to silage of high moisture corn silages reduced dry matter losses and increased aerobic stability, but information on high moisture triticale silages is still scarce. In order to alleviate losses and increase the aerobic stability of silages, the use of bacterial inoculants, with or without enzymes, has become the objective of several studies(7,8), however, according to Bernardes et al(4) results that existing are inconclusive. In this context, the objective of this study was to evaluate the effects of different chemical and one biological additives containing fibrolytic enzymes in the high moisture triticale silages under chemical-bromatological composition, aerobic stability, nutrient digestibility and ingestive behavior in sheep.

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The harvest of triticale grains (X. Triticosecale Wittmack cv. IPR 111) for silage production occurred when they reached approximately 30 % humidity. Soon after harvest the grains were crushed in 8 mm sieves, adding the additives according to the defined treatments. The treatments were: high moisture triticale silage without additive (HMTC); high moisture triticale silage with enzyme-bacterial inoculant (HMTEB); high moisture triticale silage with 0.5 % urea in natural matter (HMTU); and high moisture triticale silage with 1.5 % sodium benzoate in natural matter (HMTSB). Twenty-four (24) polyethylene pails with a capacity of 4.5 L were used as experimental silos. The mean compaction density was 1,067 kg of MV m-3. The silos were stored for 11 mo until opening. The enzyme-bacterial inoculant used was Silotrato®, composed of Lactobacillus curvatus, L. acidophilus, L. plantarum, L. buchneri, Pediococcus acidilactici, Enterococcus faecium, Lactobacillus lactis at concentrations of 109 CFU g-1 and 4% of complex enzymatically based on cellulase. The application was made with the additive diluted in non-chlorinated water at a concentration of 4.3 g L-1, according to the manufacturer's recommendation. The chemical additives, urea and sodium benzoate, were homogenized to the triticale grains manually after processing. In order to exclude the effect of the addition of water in the silage with enzyme-bacterial inoculant, in the others also it was included pure water in the same volume. For the chemical-bromatological evaluation of the silages, a completely randomized design with four replicates was used, and the buffer capacity (BM), ammoniacal nitrogen (N-NH3), hydrogenation potential (pH), dry matter organic matter (OM), crude protein (CP), ethereal extract (EE), neutral detergent fiber (NDF) and acid detergent fiber (FDA). The determination of ammoniacal nitrogen and buffer capacity was performed using the technique described by Playne and McDonald(9). The pH values were determined according to Cherney and Cherney(10). The contents of dry matter, organic matter and ethereal extract according to AOAC(11). Neutral and acid detergent fiber according to Van Soest(12) methodology. Aerobic stability was evaluated 340 d after silo sealing. Samples of 1.0 kg of each replicate were placed in polypropylene containers coated with plastic bag and conditioned in an environment with uncontrolled temperature. Silage temperatures were measured twice a day at 0900 and 1500 h for 7 d, with a thermometer inserted at 10 cm in the center of the mass. Loss of aerobic stability was defined as the time required for the silage to rise 2 °C relative to room temperature(13). From another container set, representing each replicate, daily samples were taken for pH, DM and CP determination. The design was a completely randomized design with three replications, in a scheme of subdivided plots, where the factors attributed to the plots were the silages and to the subplot the exposure time to the air. The silages used to feed the sheep followed the same manufacturing procedures described above, and were stored in 16 concrete silos with a capacity of 250 L. In the evaluation of the ingestive behavior and apparent digestibility of nutrients, the method of total fecal 575


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collection was used, for which four castrated male sheep with an average weight of 25 kg were housed in appropriate metabolic cages equipped with a drinking fountain and individual feeders and mineral mixers. Procedures were adopted in accordance with the ethical principles of animal experimentation, approved by the Committee of Ethics in Animal Experimentation of the State University of Londrina, according to document number 26014.2012.79. The evaluations with sheep were conducted in a 4x4 Latin square design, with four treatments and four periods. Each collection period lasted 5 d and preceded 10 d of adaptation. The diets maintained a roughage-concentrate ratio of 50:50, formulated solely with the foods described in Table 1, according to requirements of the NRC(14) for weaned sheep category with daily average gain of 300 g. As a bulky source out used Coast-cross hay (Cynodon dactylon (L.) pers) chopped and supplied as mixed feed. Table 1: Chemical-bromatological composition of Coast-cross hay and diets containing high moisture triticale silages with different additives and hay in the 50:50 ratio Diet Hay HMTC HMTEB HMTU HMTSB DM, g kg FM-1 780.3 793.9 787.8 789.3 823.2 -1 CP, g kg DM 158.5 154.8 177.1 154.2 129.7 -1 EE, g kg DM 19.1 20.3 19.3 18.5 11.7 NDF, g kg DM 677.1 433.5 441.8 436.1 441.1 1 ADF, g kg DM1

228.8

233.8

231.1

230.9

MM, g kg DM-1 OM, g kg DM-1

49.5 950.6

49.9 950.1

49.2 950.9

51.7 948.4

337.7 83.8 -

HMTC= control; HMTEB= enzyme-bacterial inoculant; HMTU= urea; HMTSB= sodium benzoate; DM= Dry matter; CP= Crude protein; EE= Ethereal extract; NDF= Neutral detergent fiber; FDA= Acid detergent fiber; MM= Mineral matter; MO= Organic matter.

The animals were fed twice a day at 0800 and 1700 h with water and mineral salt ad libitum. At the beginning of each period the animals were weighed considering the average weight for the calculation of the metabolic size. The feces of each animal were collected twice a day, by means of collection bags, and weighed. A subsample of 20 % of the total was stored in a freezer at -20 °C, as well as subsamples of food supplied and leftovers. For the laboratory analyzes, the subsamples were pooled to form samples composed by animal, treatment and period. The digestibility coefficients of the different diets were obtained using the system of equations cited by Silva and Leão(15). Chemical and bromatological analyzes of high moisture triticale silages, total diet, leftovers and feces included dry matter, organic matter, crude protein, ethereal extract, neutral detergent fiber and acid.

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On the last day of each period the animals were observed for 24 h to investigate the ingestive behavior(16), where each observation consisted of five-minute intervals(17). The behaviors evaluated were ingestion of solids (IS), water intake (WI), mineral salt intake (MSI), standing rumination (SR), lying rumination (LR), standing leisure (SL), lying leisure (LL) and atypical behavior (AB). In addition to these parameters, the number of chewing chews (CHEWS), the duration of ruminal cycle (DUR) and the number of chewing chews per second (CHEWS / S) were also evaluated. Data relating to chemical and bromatological composition of silages and experimental rations, animal performance and ingestive behavior had their means compared by the Tukey test at 5% significance by were submitted to the Tukey test at 5% significance by the GLM procedure of the SAS program (2001 The results of the aerobic stability were submitted to the regression analysis by program R (2013). The addition of urea caused a significant increase in the ammoniacal nitrogen contents of high moisture triticale silage (Table 2). This increase is due to the solubilization of urea in the presence of urease, an enzyme that catalyzes the hydrolysis of urea to carbon dioxide and ammonia, and this increase provided a higher buffer capacity of the ensiled mass, but did not differ from the control silage (364.2 and 323.3 meq NaOH 100g MS-1, respectively). Crude protein content was also higher (P<0.05) in urea added silage (189.7 g kg MS-1), which is a source of non-protein nitrogen. Table 2: Chemical and bromatological composition, pH and buffer capacity of high moisture triticale silages with different additives (g kg DM-1) Silage HMTC HMTEB HMTU HMTSB Average CV P DM, g kg FM-1 CP EE NDF ADF MM OM pH N-NH3, % N total BC, meq NaOH 100g DM-1

686.9 172.6b 16.0 109.3 39.1 19.6b 980.4a 4.50c

714.1 165.2b 18.5 126.0 49.0 20.5ab 979.5ab 4.35c

702.0 189.7a 16.4 114.5 43.6 19.0b 981.0a 4.84b

704.9 164.0b 14.9 124.5 43.3 24.0a 976.0b 5.67a

701.9 172.9 16.5 118.6 43.7 20.8 919.2 4.84

2.93 3.21 13.72 10.70 15.85 8.20 0.17 1.30

0.2208 <0.0001 0.2286 0.3081 0.4390 0.0092 0.0092 <0.0001

58.7b

46.4b

106.2a

42.1b

63.4

17.07 <0.0001

323.3ab

294.1b

364.2a

216.7c

299.6

6.25

<0.0001

HMTC= control; HMTEB= enzyme-bacterial inoculant; HMTU= urea; HMTSB= sodium benzoate; DM= Dry matter; CP= Crude protein; EE= Ethereal extract; NDF= Neutral detergent fiber; FDA= Acid detergent fiber; MM= Mineral matter; MO= Organic matter; N-NH3: Ammoniac nitrogen; BC= Buffer capacity. ab Means followed by different letters, in the line, differ (P<0.05).

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The above mentioned fermentation alterations provided higher pH of the urea treated silage in relation to the control silage (4.84 and 4.50, respectively), but lower than that found in silage supplemented with sodium benzoate. The justification for the silage with sodium benzoate had high pH value and low buffer capacity, would be the pKa of lactic acid. Bernardes et al(4) affirm that when pH values are higher than pKa, the efficiency of the acid in the solution is reduced because the acid form decreases and the ionized form predominates. When compared than control silage, it was observed that the addition of enzyme-bacterial inoculant did not alter the chemical-bromatological composition (Table 2), and as described by Bernardes et al(4), the addition of inoculants with homo and heterofermentative bacteria does not seem to influence the aerobic stability of the same (Figure 1). Figure 1: Value of pH during the aerobic stability test

When evaluating high moisture silages of different winter grains, some researchers found higher content of acetic and propionic acid in the high moisture triticale(18). In agreement, Ni et al(3) cited by Leão et al(19) affirm that there is a predominance of heterofermentative bacteria in the epiphytic community of this species, which could, according to the same authors, justify the prolonged aerobic stability of silage. Figure 1 shows the average pH of the high moisture triticale silage during the aerobic stability evaluation period. Although there is no difference between the treatments, it is possible to observe a constant increase of pH due to the consumption of organic acids. None of treatments showed a temperature increase above 2 °C compared to the ambient temperature during the entire aerobic exposure period (Table 3), which is a good indicator of deterioration control(13). On the seventh day all silages reached their maximum

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temperature, being this a consequence of the microbiological development priority. This temperature oscillation observed in silages follows the behavior of ambient temperature, counteracting a possible gradual increase constant and independent of external environment.

Table 3: Ambient temperature and temperature averages (°C) of high moisture triticale silages with different additives during aerobic exposure Days of aerobic exposure Silage 1 2 3 4 5 6 7 HMTC 28.83 28.35 29.02 29.13 27.45 28.83 30.28 HMTEB 28.92 27.92 28.45 28.57 26.93 28.30 29.73 HMTU 28.92 28.17 28.72 28.93 27.27 28.30 30.02 HMTSB 28.58 27.97 28.57 28.70 27.08 28.23 30.03 Ambient 27.10 28.10 28.15 27.30 27.20 30.25 29.80 temperature HMTC= control; HMTEB= enzyme-bacterial inoculant; HMTU= urea; HMTSB= High sodium benzoate.

The high density of compaction reached in the silos may have been a determining factor for good apparent control of deterioration; this favors that the yeast population is reduced during the anaerobiosis phase of the silo, providing a more stable food when exposed to oxygen(20).

Figure 2 shows the behavior of dry matter and crude protein during days of aerobic exposure. In relation to dry matter there was interaction between silages and days of aerobic exposure. Note the quadratic behavior for control silage (a), linear for silage with enzyme-bacterial additive (b), and cubic for silages treated with urea (c) and sodium benzoate (d).

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Figure 2: Dry matter (dotted line) and crude protein (solid line) contents of high moisture triticale silages with different additives during aerobic exposure

HMTC= control (a); HMTEB= enzyme-bacterial inoculant (b)= HMTU: urea (c); HMTSB= sodium benzoate (d).

Both control (a) and sodium benzoate (d) silages showed a more abrupt fall from the fourth day of aerobic exposure, whereas silage with enzyme-bacterial inoculant (b) had a linear decrease (R2= 0.8421) in the dry matter contents from the opening of the silo. This decrease in dry matter contents in silages with bacterial additives has been shown to be common in the aerobic stability studies, suggesting that losses of the same. These losses are due to the reduction in the concentration of acetate(21), which is a potent antifungal, and the increase in lactate concentration, which is a growth substrate for yeasts. Wilkinson and Davies(22) still point out that for each molecule of acetic acid formed, an equivalent molecule of carbon dioxide is produced, increasing dry matter losses. The initial rapid decrease in dry matter contents of urea silage (c) may be due to the evaporation of ammonia formed in larger amounts (Table 2) during the fermentation process of this treatment.

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The increase in the dry matter content observed in the first days of silage treated with sodium benzoate (d) indicates a loss of humidity for the environment. Furthermore, this type of additive is characterized by hindering the development of yeasts, delaying the onset of deterioration(5). Similar behavior was described in sugarcane silage with this same additive(23). In relation to crude protein content, trend lines indicate increasing linear behavior for all silages that were added, which is a dilution reflex, where consumption of carbohydrates is mainly observed, increasing the concentration of other constituents in dry matter. However, control silage showed an opposite behavior, with decrease in crude protein content during the days of aerobic exposure, suggesting that there was degradation by molds, which act at higher pH and consume more complex components(24). Studies about dry matter losses of silages after silo opening are widely diffused in the scientific field(7), but it is not possible to say in relation to each specific constituent, and a larger number of researches on the subject to come to a more precise conclusion. The data in Table 4 show that nutrient intake present significant difference only for neutral detergent fiber and acid detergent fiber when expressed in grams per day, where the highest intakes were recorded for the animals fed with silage with enzyme-bacterial additive. The explanation for this result may not be directly related to the treatment, however, it is possible that bacteria present in inoculant altered ruminal environment, allowing greater consumption. The improvement in fiber intake with the use of an enzyme-bacterial inoculant is contradictory among the authors. In review, Oliveira et al(7) concluded that the divergences in results may be related, among other factors, to the different variations of the inoculant used, and also of the diet. Just like McCuistion et al(25), with the addition of cellulase containing inoculant, it was expected that the fiber would be better utilized, which was not observed since it is a food with low contents of this component. Table 4: Nutrient intake of diets containing high moisture triticale silages with different additives (g day-1) Diet Average CV, % P HMTC HMTEB HMTU HMTSB DMI 975.78 1056.15 954.12 957.75 985.95 7.33 0.2569 CPI 156.51 164.47 163.66 147.41 158.01 7.73 0.2688 EEI 19.49 22.23 19.73 18.36 19.95 14.95 0.3876 b a b b NDFI 388.06 431.87 383.64 381.76 396.33 5.33 0.0435 ab a b b ADFI 211.46 232.54 208.28 203.55 213.95 4.42 0.0197 OMI 927.66 1003.84 908.26 908.97 937.18 7.36 0.2599 HMTC= control; HMTEB= enzyme-bacterial inoculant; HMTU= urea; HMTSB= sodium benzoate; DMI= Dry matter intake; CPI= Crude protein intake; EEI= Ethereal extract; NDFI= Neutral detergent fiber intake; ADFI= Acid detergent fiber intake; OMI= Organic matter intake. ab Means followed by different letters, in the line, differ (P<0.05).

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In general, nutrient and dry matter digestibility of high moisture triticale silage were not affected (P>0.05; Table 5) by the addition of no additives, however, all diets showed dry matter digestibility compatible with high moisture corn and sorghum silage, which are the reference foods for this variable(26,27). However, both digestibility values of organic matter and crude protein were lower than those described for the same feed (891 and 907 g kg DM-1, respectively)(18). Table 5: Apparent digestibility of nutrients from diets containing high moisture triticale silages with different additives (g kg DM-1) Diet HMTE HMTC HMTU HMTSB Average CV P B DMD 679.6 687.4 699.6 683.4 687.5 2.01 0.2898 CPD 707.5 715.2 703.6 689.7 711.5 2.67 0.0823 EED 770.9 782.5 768.6 769.0 772.7 3.97 0.9035 NDFD 548.3 568.4 549.3 551.9 554.5 6.78 0.8583 ADFD 578.4 597.5 607.4 602.2 596.4 7.32 0.8012 OMD 706.8 710.4 721.0 710.6 712.2 1.95 0.5515 HMTC= control; HMTEB= enzyme-bacterial inoculant; HMTU= urea; HMTSB= sodium benzoate; DMD= Dry matter digestibility; CPD= Crude protein digestibility; EED= Ethereal extract digestibility; NDFD= Fiber in neutral detergent digestibility; ADFD= Fiber in acid detergent digestibility; OMD= Organic matter digestibility.

Ingestive behavior is a good parameter for the evaluation of any food(27), since often the acquired chemical or fermentative benefits are not reflected at the time of feeding. The data in Table 6 show that none of the variables related to ingestive behavior of sheep presented significance between the treatments. Longer water intake time was expected for animals fed silage with sodium benzoate, in view presence of sodium of the additive itself, which was not observed. It should be noted that in this study water consumption was not measured. Kozloski et al(28) observed that ingestion of sheep may be affected by dietary protein, but that there was no difference when protein source was urea, as in the present study.

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Table 6: Ingestive behavior of sheep fed with a diet containing high moisture triticale silage with different additives Diet HMTC HMTEB HMTU HMTSB Average P CHEWS 78.73 84.69 79.35 79.71 80.62 0.3716 -1 DUR, sec cycle 56.29 59.94 57.52 57.06 57.70 0.4289 -1 CHEWS S 1.40 1.41 1.38 1.40 1.40 0.6047 -1 WI, min d 2.19 4.06 2.19 3.75 3.05 0.7490 -1 IS, min d 57.50 55.00 53.75 52.50 54.69 0.8895 -1 MSI, min d 5.31 3.75 3.13 6.65 4.71 0.1597 -1 SR, min d 7.81 6.25 6.88 5.31 6.56 0.7381 -1 LR, min d 141.56 148.75 147.50 132.50 142.58 0.4305 -1 SL, min d 43.75 42.19 40.94 45.93 43.20 0.8783 -1 LL, min d 99.69 97.81 102.81 109.00 102.34 0.6623 -1 AB, min d 2.19 2.19 2.81 4.36 2.89 0.5053 HMTC= Control; HMTEB= Enzyme-bacterial inoculant; HMTU= Urea; HMTSB= Sodium benzoate; CHEWS= Number of chewing chews; DUR= Duration of the rumination cycle; CHEWS S -1= Number of chewing chews per second; WI= Water intake; IS= Ingestion of solids; MSI= mineral salt intake; SR= Standing rumination; LR= lying rumination; SL= Standing leisure; LL= Lying leisure; AB: atypical behavior.

The fibrolytic action of some enzymes present in certain additives leads to a reduction in the silage fiber content, which may increase the feed intake of the animals (27). However, this report did not show this difference in the constitution of fibers (Table 1) and consequently ingestion. Very expressive effects were not observed with the addition of the studied additives on the chemical-chemical composition, aerobic stability, digestibility of nutrients and ingestive behavior in sheep. Can be highlight the addition of urea as a high moisture triticale additive for promoting increased silage crude protein content. Literature cited: 1.

Moeinoddini HR, Alikhani M, Ahmadi F, Ghorbani GR. Rezamand P. Partial replacement of triticale for corn grain in starter diet and its effects on performance, structural growth and blood metabolites of Holstein calves. Animal 2017;11:61-67.

2.

Zhu F. Triticale: Nutritional composition and food uses. Food Chem 2018;241:468– 479.

3.

Ni K, Wang Y, Cai Y, Pang H. Natural lactic acid bacteria population and silage fermentation of whole-crop wheat. Asian-Australas J Anim Sci 2015;28:1123-1132.

4.

Bernardes TF, Reis RA, Siqueira GR, Amaral RC, Pires AJP. Estabilidade aeróbia da ração total e de silagens de capim-marandu tratadas com aditivos químicos e bacterianos. Rev Bras Zootec 2007;36:754-762.

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5.

Knicky M, Spörndly R. The ensiling capability of a mixture of sodium benzoate, potassium sorbate, and sodium nitrite. J Dairy Sci 2011;94:824-831.

6.

Jobim CC, Lombardi L, Macedo FAFD, Branco AF. Silagens de grãos de milho puro e com adição de grãos de soja, de girassol ou uréia. Pesqu Agropecu Bras 2008;43:649-656.

7.

Oliveira MR, Jobim CC, Neumann M, Bueno AVI, Leão GFM, Daniel JLD. Effects of inoculation with homolactic bacteria on the conservation of wheat silage stored in bunker-silos. Ital J Anim Sci 2018;17:81-86.

8.

Jondreville C, Genthon C, Bouguennec A, Carre B, Nys Y. Characterization of European varieties of triticale with special emphasis on the ability of plant phytase to improve phytate phosphorus availability to chickens. Br Poult Sci 2007;48:678689.

9.

Playne MJ, McDonald P. The buffering constituents of herbage and silage. J Sci Food Agric 1996;17:262-268.

10. Cherney JH, Cherney DJR. Assessing silage quality. In: Buxtou DR, Muck RE, Harisson JH. Silage science and technology. Madison. 2003;141-198. 11. Official Methods of Analysis. Official methods of analysis. 15th ed. Gaithersburg (MD): AOAC International. Official Methods 934. 01, 942.05. 1990. 12. Van Soest PJ. Nutritional ecology of the ruminant. 2. ed. Ithaca: Cornell University Press; 1994. 13. Taylor CC, Kung Junior L. The effect Lactobacillus buchneri 40788 on the fermentation and aerobic stability of high moisture corn in laboratory silos. J Dairy Sci 2002;85:1526-1532. 14. NRC. Nutrient requirements of sheep 6th ed. National Academy of SciencesNational Research Council, Washington, DC, 1985. 15. Silva CJF, Leão MI. Fundamentos de Nutrição de Ruminantes. Piracicaba: Ed. Livroceres; 1979. 16. Johnson TR, Combs DK. Effects of prepartum diet, inert rumen bulk, and dietary polythylene glicol on dry matter intake of lactating dairy cows. J Dairy Sci 1991;74:933-944. 17. Carvalho GGP, Pires AJV, Silva RR, Carvalho BMA, Silva HGO, Carvalho, LM. Aspectos metodológicos do comportamento ingestivo de ovinos alimentados com capim-elefante amonizado e subprodutos agroindustriais. Rev Bras Zootec 2007;36:1105-1112.

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18. Pieper R, Hackl W, Korn U, Zeyner A, Souffrant B, Pieper B. Effects of ensiling triticale, barley and wheat grains at different moisture content and addition of Lactobacillus plantarum (DSMZ 8866 and 8862) on fermentation characteristics and nutrient digestibility in pigs. Anim Feed Sci Technol 2011;164:96-105. 19. Leão GFM, Jobim CC, Neumann M, Horst EH, Santos SKD, Venancio BJ, et al. Nutritional composition and aerobic stability of winter cereal silage at different storage times. Acta Sci Anim Sci 2017;39:131-136. 20. Tabacco E, Piano S, Revello-Chion A, Borreani G. Effect of Lactobacillus buchneri LN4637 and Lactobacillus buchneri LN40177 on the aerobic stability, fermentation products, and microbial populations of corn silage under farm conditions. J Dairy Sci 2011;90:928-936. 21. Silva VP, Pereira OG, Leandro E, Silva T, Ribeiro K, Mantovani H, et al. Effects of lactic acid bacteria with bacteriocinogenic potential on the fermentation profile and chemical composition of alfalfa silage in tropical conditions. J Dairy Sci 2016;99:1895–1902. 22. Wilkinson JM, Davies DR. The aerobic stability of silage: key findings and recent developments. Grass Forage Sci 2012;68:1-19. 23. Pedroso ADF, Nussio LG, Loures DRS, Paziani SDF, Ribeiro JL, Mari LJ, et al. Fermentation, losses, and aerobic stability of sugarcane silages treated with chemical or bacterial additives. Sci Agric 2008;65:589-594. 24. Nout MR. Rich nutrition from the poorest–Cereal fermentations in Africa and Asia. Food Microbiol 2009;26:685-692. 25. McCuistion K, Foste JL, Schuster G, Wester D, Lopez Z, Umphres AM et al. Forage mass, nutritive value, and in situ degradation of sorghum silage treated with fibrolytic enzymes. Crop Forage Turfgrass Manag 2017;3:182-194. 26. Costa FMJ, Júnior GD, Zacaroni OF, Santos JF, Pereira RAN, Pereira MN. Silagem de grãos úmidos de milho de textura dura ou macia em dietas com polpa cítrica para vacas em lactação. Arq Bras Med Vet Zoot 2014;66:203-210. 27. Ribeiro ELA, Mizubuti IY, Silva LDF, Paiva FHP, Sousa CL, Castro, FAB. Desempenho, comportamento ingestivo e características de carcaça de cordeiros confinados submetidos a diferentes frequências de alimentação. Rev Bras Zootec 2011;40:892-898. 28. Kozloski GV, Cadorin Júnior RL, Harter CJ, Oliveira L, Alves TP, Mesquita FR et al. Effect of suplemental nitrogen source and feeding frequency on nutrient supply to lambs fed a kikuyu grass (Pennisetum clandestinum) hay-based diet. Small Ruminant Res 2009;81:112-118.

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https://doi.org/10.22319/rmcp.v12i2.5540 Technical note

Polyunsaturated fatty acid supplementation during breeding in nulliparous Katahdin ewes: reproductive efficiency and pre-weaning growth in lambs

Ricardo Vicente-Pérez a Ulises Macías-Cruz b* Leonel Avendaño-Reyes b Enrique O. García-Flores a Ricardo Martínez-Martínez a Oziel D. Montañez-Valdez c José A. Reyes-Gutiérrez c Alfonso J. Chay-Canul d María M. Crosby-Galván e

a

Universidad de Guadalajara. Departamento de Producción Agrícola-CUCSUR, Av. Independencia Nacional 151, C.P. 48900, Autlán, Jalisco, México. b

Universidad Autónoma de Baja California. Instituto de Ciencias Agrícolas, Baja California, México. c

Universidad de Guadalajara. Departamento de Ciencias de la Naturaleza-CUSUR, Jalisco, México. d

Universidad Juárez Autónoma de Tabasco. División Académica de Ciencias Agropecuarias, Villahermosa, Tabasco, México. e

Colegio de Posgraduados. Campus Montecillo, Programa de Ganadería. Estado de México, México.

*Corresponding author: ulisesmacias1988@hotmail.com 586


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Abstract: A total of 46 nulliparous Katahdin ewes were distributed under a completely randomized block design in two dietary treatments (n=23) around mating to evaluate the effects of adding of polyunsaturated fatty acid (PUFA) on the reproductive performance and pre-weaning growth in lambs. Treatments were two concentrates formulated isoenergetic and isoproteic that contained or did not contain (control) n-6 PUFA, and both were offered for 42 d (7 d before the breeding period and 35 d of breeding period; exposure to ram). Dietary addition of PUFA shortened (P<0.05) the estrus interval, without affecting (P>0.05) other reproductive variables. Lamb birth weight did not change (P>0.05) with addition of PUFA; however, the dietary addition of PUFA increased (P<0.05) pre-weaning growth rate and weaning weight in male lambs but not female lambs. Dietary addition of PUFA also improved (P<0.05) pre-weaning growth in twin birth lambs but not in single birth lambs. In conclusion, the inclusion of omega-6 PUFA in the diet of nulliparous Katahdin ewes during breeding is a promising dietary strategy since it shortens estrus interval without affecting other reproductive variables, and improves pre-weaning growth in male lambs and twin birth lambs. Key words: Hair sheep, Linoleic acid, Flushing effect, Fertility, Postpartum growth.

Received: 09/10/2019 Accepted: 16/07/2020

Because of their higher incidence of silent, shortest and less intense estrus, young ewes have lower reproductive efficiency than adult ewes(1). In addition, offspring born to young ewes also tend to exhibit low birth weight and slow pre-weaning growth(2). Omega 6 (n-6) polyunsaturated fatty acid (PUFA) are essential for ruminants. They favor the reproductive processes of folliculogenesis, ovulation and estrus activity by stimulating synthesis of 17β estradiol in ovaries, as well as prostaglandins F2α (PGF2α) in endometrium(3,4). Additionally, PUFA can regulate epigenetic processes and modify fetal programming during the early gestation, causing long-term postnatal effects in offspring(5). So, formulation of breeding diets to include n-6 PUFA is a potential nutritional strategy to improve reproductive efficiency in nulliparous ewes and growth in their offspring. In multiparous Pelibuey ewes, dietary supplementation with corn oil (rich in n-6 PUFA) improves follicular development, corpora lutea count and oocyte quality(6), as well as embryo development(7). This is attributed to increases in serum concentrations of cholesterol, insulin, 17β-estradiol, and progesterone(8). However, the effects of including n-6 PUFA in the diet of mating ewes on reproductive variables has been inconsistent across studies(9,10). In 587


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multiparous wool breed ewes, n-6 PUFA supplementation around conception effectively reduced pre-weaning mortality and increased offspring capacity for post-natal thermoregulation(11). Note that these beneficial effects of n-6 PUFA have not been demonstrated in primiparous hair sheep. Therefore, the objective of this study was to evaluate the effect of adding n-6 PUFA in the breeding diet on the reproductive efficiency of nulliparous Katahdin ewes during the natural reproductive season, as well as on pre-weaning growth of their offspring. The study was carried out during the sheep reproductive season (October-November) at the “El Tilzapote” ranch, located in the town of Ayutita, Autlán de Navarro municipality, Jalisco, Mexico (19°48’ N, 104°24’ W; 1,013 m asl). Experimental animals were 46 nulliparous Katahdin ewes with 9-mo of age, 43.9 ± 2.5 kg of live weight (LW) and 3.1 ± 0.6 units of body condition score (BCS) on a 1-to-5 scale(12). Selection criteria for ewes were BCS from 2.5 to 3.5 units, and presence of signs of estrus one month prior to beginning of study, to ensure ovarian cyclicity. Ewes were assigned to one of two dietary treatments (n = 23) following a completely randomized block design (CRBD; blocking factor= LW). Treatments consisted of feeding the ewes with corn silage (without grains) ad libitum and 400 g/d/ewe of a concentrate formulated with (PUFA group) or without (control group) a n-6 PUFA-rich source (Table 1). Table 1: Chemical composition of concentrates and corn silage offered to ewes during the breeding period Chemical Concentrates Concentrates Silage components Fatty acids, % Control PUFA Control PUFA Crude protein, % 38.4 39.0 7.2 C14:0 0.5 0.1 Ash, % 6.0 5.0 25.7 C16:0 20.4 12.1 Crude fiber, % 10.2 10.1 11.6 C16:1 n-7 0.4 0.2 ADF, % 16.4 15.5 23.9 C18:0 3.3 3.6 NDF, % 53.0 43.5 59.1 C18:1 n-9 39.5 24.4 TDN, % 84.0 85.0 47.4 C18:2 n-6 28.0 50.3 DE, Mcal/kg DM 3.7 3.7 2.1 C20:0 0.4 0.3 ME, Mcal/kg DM 3.0 3.1 1.7 C18:3 n-6 0.3 0.2 C20:1 n-9 0.4 0.1 C18:3 n-3 2.8 2.4 C22:0 0.1 0.2 Polyunsaturated 31.4 53.2 Monounsaturated 40.3 24.7 Saturated 24.3 16.0 ADF= acid detergent fiber; NDF= neutral detergent fiber; TDN= total digestible nutrients; DE= digestible energy; ME= metabolizable energy.

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Both concentrates were isoenergetic and isoproteic, although the PUFA concentrate contained 3% of a commercial vegetable oil rich in n-6. The control concentrate contained 3% frying oil, rich in oxidized fatty acids, to ensure that concentrate consumption was unaffected by differences in texture or consistency. Overall, ewes were fed the treatment diets during 42 d, 7 days before breeding and the 35 d of breeding period. The concentrates were offered once daily at 0700 h, before the silage was provided. Once the breeding period ended, the ewes in both groups (PUFA and control) were fed corn silage for up to 4 wk before the lambing. During the last 4 wk of gestation and lactation period, both groups were also fed a concentrate at 500 g/d/ewe (metabolizable energy [ME]= 3.0 Mcal/kg dry matter [DM], and crude protein [CP]= 380 g/kg DM). This concentrate contained 50% soybean meal, 23% ground canola, 19% ground corn, 4% minerals, 1% urea and 3% oil. On d 8 and 90 (weaning) postpartum, the offspring had free access to creep feeding (CP= 210 g/kg DM, and ME= 3.5 Mcal/kg DM), which was formulated with 30% soybean paste, 63% corn, 2% gluten, 2% oil, 2% minerals and 1% milk substitute. During the experiment, the ewes were penned separately by treatment (PUFA and control). The trough space within each pen was sufficient to ensure that all females could consume concentrate and silage simultaneously, without competition. Feed samples were collected once a week from each group and processed for determination of bromatological analysis (DM, CP, ash and crude fiber)(13), as well as neutral and acid detergent fiber fractions(14). Total digestible nutrients (TDN)(15), digestible energy (DE) and ME(16) were calculated using formulas. Fatty acid profiles of concentrates were determined with a gas chromatographer (HP 6890, USA) equipped with an automatic injector (HP 7683, USA), tray with autosampler and a 100 m x 0.25 mm x 0.2 µm (film) capillary column at 29 psi (Supelco SP® 2560, USA). Evaluation of corporal status: Ewe LW and BCS were recorded at d 7 before breeding, at the end of breeding and at parturition. Total weight gain (TWG) and daily weight gain (DWG) were calculated during the 42-d test period. Evaluation of reproductive performance: Ewes did not receive a hormonal treatment prior to or during the breeding period, so the evaluation of the estrus activity was in accordance with the natural estrous cycle. Ewe estrus activity was recorded daily (0800 and 1800 h) during the 35-d breeding period (October 8 to November 11) using three Dorper breed rams with proven fertility. The rams were placed individually in the pens, but rotated between treatments. An ewe was considered to be in estrus when receptive to the ram, accepting natural mounting behavior without a movement reflex. The date and hour of the day of estrus detection was recorded for each ewe. Those in estrus were marked on the back with crayon and kept in the same pen. The number of mounts per ewe was not controlled, but a ratio of 589


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15 females per male was considered sufficient to ensure pregnancy(17). One month after ended the breeding period, a pregnancy diagnosis was done abdominally using a portable ultrasound (Model DP-10 Vet, Mindray, Shenzhen, China) equipped with a micro-convex transducer. Nonpregnant diagnosed ewes were removed from the pen. At parturition, ewes were kept in the same pen, recording only lambing date and type (single or twin). The collected data were used to calculate the reproductive variables. Percentage of ewes in estrus was calculated by expressing the number of ewes in estrus as a percentage of the total number of treated ewes. Estrus interval was calculated as the number of days elapsed between the first day of breeding and the day with signs of estrus. Pregnancy rate was the percentage of ewes diagnosed as pregnant from the total number of mated ewes. Lambing rate was the percentage of ewes lambed from the total number of pregnant ewes. Fertility rate was the percentage of ewes lambed from the total number of treated ewes, and fecundity was the percentage of lambs born per mated ewe. Prolificity was calculated as the number of lambs born per ewe lambed. Finally, the percentage of ewes with single or twin lambing was calculated from the total number of ewes lambed. Evaluation of pre-weaning growth: All lambs were identified at birth with metal ear tags, and their sex and birth weight were recorded. Lambs were weighed again at weaning (90 d) to calculate TWG and DWG. Statistical analysis: All data were analyzed using the SAS statistical package(18). Body status variables, estrus interval and prolificacy were evaluated with an analysis of variance under a CRBD. Variables expressed in percentage were analyzed with a Chi-squared test. Birth weight and lamb pre-weaning growth variables were also processed with an analysis of variance. However, a 23 factorial arrangement in a completely randomized design was applied, where the model considered the fixed effects of dietary treatment (control and PUFA), sex (female and male), lambing type (single and twin) and all possible interactions. For pre-weaning growth variables, birth weight was added to the model as a covariate. Means were compared with a Tukey test at = 0.05. The treatment × sex × lambing type interaction was not significant (P>0.05), so it was not included in results. Ewe body status variables (LW, BCC, TWG and DWG) were unaffected (P≥0.31) by the dietary inclusion of PUFA at all measurement times (Table 2). Additionally, PUFA supplementation reduced (P= 0.05) the estrus interval by 7 d, but did not affect (P≥0.28) other reproductive variables (Table 3). The estrus distribution results (Figure 1) showed that most of the ewes in the PUFA treatment (P<0.05) exhibited estrus in the first week of breeding (17.4 vs 47.8 %), while most of the control ewes (P<0.05) exhibited estrus in the second week (43.5 vs 17.4 %). On weeks 3, 4 and 5, the proportion of ewes in estrus decreased in both groups, although the control ewes had higher (P<0.05) percentage of estrus than those PUFA ewes on the wk 4. 590


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Table 2: Live weight, weight gain and body condition in nulliparous Katahdin ewes fed either a concentrate containing n-6 polyunsaturated fatty acids (PUFA) or one without (Control) Groups SE P Variables Control PUFA Live weight, kg Initial (7 days pre-mating) 44.0 43.8 0.1 0.42 End of mating 49.5 48.6 0.6 0.31 Parturition 49.5 48.7 3.7 0.84 TWG, kg 5.6 4.8 0.6 0.37 DWG, g/day 132 114 14 0.37 Body condition Initial (7 days pre-mating) 3.1 3.2 0.1 0.52 End of mating 3.5 3.6 0.1 0.42 Parturition 3.3 3.2 0.2 0.50 SE= standard error; TWG= total weight gain; DWG daily weight gain.

Table 3: Reproductive performance in nulliparous Katahdin ewes fed either a concentrate containing n-6 polyunsaturated fatty acids (PUFA) or one without (Control) Group Variables Control PUFA P Ewes, n 23 23 Ewes in estrus, % 23/23 (100.0) 22/23 (95.6) 0.31 Estrus interval, days 17.0 ± 2.3 10.3 ± 2.3 0.05 Gestation rate, % 18/23 (78.3) 17/22 (77.3) 0.66 Birth rate, % 16/18 (88.9) 16/17 (94.1) 0.57 Fertility, % 16/23 (69.6) 16/23 (69.6) 1.00 Fecundity, % 24/23 (104.3) 21/23 (91.3) 0.35 Single births, % 8/16 (50.0) 11/16 (68.7) 0.28 Twin births, % 8/16 (50.0) 5/16 (31.2) 0.28 Prolificity, n 1.5 ± 0.1 1.3 ± 0.1 0.67

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Figure 1: Estrus distribution per week (a) and cumulative weekly estruses (b) during mating period in nulliparous Katahdin ewes fed either a concentrate containing n-6 polyunsaturated fatty acids (PUFA) or one without (Control)

a,b

Different letters in the same week indicate differences between groups (P<0.05).

Pre-weaning growth results are shown in Table 4. The treatment × sex interaction did not affect (P>0.11) birth weight, but did affect (P<0.05) DWG, TWG and weaning weight. Dietary inclusion of PUFA increased (P<0.05) TWG, DWG and weaning weight in male lambs, but not in female lambs. The treatment × lambing type interaction affected (P<0.05)

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birth weight and pre-weaning growth variables. Lambs born from single lambing had higher (P<0.05) birth weight than those born from twin lambing in both the dietary groups. In contrast, the PUFA treatment increased (P<0.05) DWG, TWG and weaning weight in lambs born from twin lambing, but not (P>0.05) in single birth lambs. Finally, the lambing type × sex interaction affected (P<0.05) birth weight, but not TWG, DWG and weaning weight. Overall, birth weight was higher (P<0.05) in single birth lambs than in twin birth lambs in both sexes. Table 4: Pre-weaning growth in lambs of Katahdin ewes fed either a concentrate containing n-6 polyunsaturated fatty acids (PUFA) or one without (Control) Study Factors Growth Variables n DWG Factor A Factor B LWB (kg) LWW (kg) TWG (kg) (g/day) Treatment × sex interaction Female 14 3.8 ± 0.2ª 28.0 ± 1.2ª 24.2 ± 1.2a 269 ± 14ª Control a Male 10 3.9 ± 0.3ª 28.2 ± 1.7ª 24.5 ± 1.7 276 ± 19ª a Female 15 3.9 ± 0.2ª 28.5 ± 1.2ª 24.7 ± 1.2 278 ± 13ª PUFA b b Male 6 3.7 ± 0.3ª 34.3 ± 2.9 30.5 ± 2.9 341 ± 33b Treatment × lambing type interaction Single 8 4.5 ± 0.3ª 29.6 ± 2.0ab 25.9 ± 2.0ab 306 ± 20ª Control b Twin 16 3.2 ± 0.2 26.6 ± 1.4ª 22.8 ± 1.4ª 239 ± 12b Single 11 4.1 ± 0.2ª 31.6 ± 2.4b 27.9 ± 2.4b 324 ± 25ª PUFA b b b Twin 10 3.5 ± 0.2 31.1 ± 2.3 27.4 ± 2.3 295 ± 26ª Lambing type × sex interaction Female 14 4.5 ± 0.2ª 29.8 ± 1.5ª 25.2 ± 1.5ª 281 ± 13ª Single Male 5 4.2 ± 0.3ª 32.0 ± 2.7ª 27.9 ± 2.7ª 310 ± 29ª Female 15 3.2 ± 0.2b 27.7 ± 1.5ª 24.5 ± 1.5ª 272 ± 16ª Twin b Male 11 3.4 ± 0.2 28.8 ± 2.3ª 25.4 ± 2.3ª 282 ± 25ª n= number of lambs; LWB= live weight at birth; LWW= live weight at weaning; TWG= total weight gain; DWG= daily weight gain. ab Different letter superscripts in the same column and same double interaction indicate differences (P<0.05).

Addition of n-6 PUFA in the breeding diet had no effect on body status in the Katahdin ewes, which was expected as both the PUFA and control concentrates were isoenergetic and isoproteic, with a relatively low (3%) oil inclusion level in both diets. Sheep diets should not be formulated with more than 6% of any vegetable oil because excessive oil intake can reduce ruminal microbial activity and, consequently, feed intake and body status(3). Ewe LW and BCS results coincide with previous reports(10). Inclusion of n-6 PUFA in the breeding diet shortened the natural estrus interval by seven days in the Katahdin ewes. This may be due to two possible mechanisms, depending on which

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estrus cycle stage a sheep is in when it begins the intake of a PUFA-rich diet. First, PUFA intake may have caused early lysis of the corpus luteum by stimulating PGF2α synthesis, since these are precursors of arachidonic acid(4). Second, the presence of PUFA could have increased growth and steroidogenic capacity in the pre-ovulatory follicles(8). The shortened estrus interval observed in the present results coincides with a study of Merino ewes, which exhibited a shorter estrus interval when fed oleaginous seeds rich in n-6 PUFA during the breeding period(19). Feeding with n-6 PUFA during the breeding period helped to naturally synchronize estrus activity in the evaluated ewes. About 50 % of the ewes in the PUFA treatment presented estrus and were mated naturally within the first week of the breeding period. This has great practical relevance since feeding to ewes with PUFA can be applied to reduce production times associated with breeding, lambing, lamb pre-weaning care and general herd management. Although the estrus interval was shorter by including n-6 PUFA in the breeding diet, it did not change reproductive performance in Katahdin ewes. This contradicts the expected results, based on previous studies. For example, previous studies in Pelibuey ewes indicate that n-6 PUFA supplementation during breeding favors follicular(6) and embryonic(7) development, as well as the ovulatory rate(7) and corpus luteum functionality(8). Hence, higher pregnancy rate, fertility, prolificacy and multiple lambing in nulliparous Katahdin ewes was expected. In contrast, in another study, the fertility and lambing rates, and the proportion of twin births, improved in multiparous Afshari ewes fed n-6 PUFA protected with calcium salt(9,20). Supplementation with soybean oil as a n-6 PUFA source in Pelibuey, Blackbelly and Pelibuey x Blackbelly ewes, is reported to increase prolificacy but not the conception and fertility rates(17). The lack of improved reproductive performance in PUFA ewes may have been caused by the short (7-d) pre-breeding feeding time; it is required to offer the concentrate at least 20 d before exposing the ewes to the ram, and to continue during the breeding period (9,17,20). Another possible cause is low post-intake PUFA bioavailability. Only 15 % of PUFA reach the intestine intact and ready for absorption, the remaining percentage will be saturated during ruminal biohydrogenation(3). For example, ewes fed sunflower oil protected in calcium salt exhibited greater follicular growth, serum concentrations of steroidal hormones, fertility, prolificacy and lambing rates than those fed unprotected sunflower oil(20). The effect of PUFA intake in ewes during breeding on offspring birth weight is inconclusive in the literature. Some studies report no effects(19), while others indicate improvements(9,20). In the present study, birth weight was unaffected by PUFA maternal intake and offspring sex, although lambing type did caused variation in this variable. Birth weight was higher in single

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birth lambs than in twin birth lambs, regardless of sex and mother’s origin; this is well documented in the literature(21). The PUFA treatment ewes exhibited better pre-weaning growth in lambs, particularly in male lambs and twin birth lambs. Fetal programming is known to begin post-conception, and varies by sex and lambing type(2). Male fetuses are programmed to have better postnatal muscle development than female fetuses(22). Multiple gestation fetuses, unlike single gestation fetuses, are programmed to naturally have intrauterine growth restriction, which can negatively affect its postnatal development(23). The PUFA are associated with fetal programming of lipid and muscle metabolism, as well as neonate behavior and vigor(5). The current findings therefore suggest that addition of n-6 PUFA exerts long-term beneficial effects on pre-weaning growth in lambs by modifying fetal programming in early gestation. Indeed, this nutritional strategy appears to partially reverse fetal growth programming in twin-pregnancy fetuses. This would explain the improved pre-weaning growth in twin birth lambs from PUFA treatment ewes. Future research is needed to confirm the possible effects of PUFA in fetal programming of hair sheep. Overall, dietary addition of n-6 PUFA during the breeding period shortened the time of estrus onset in nulliparous Katahdin ewes, but did not improve overall reproductive performance during the natural reproductive season. It also had long-term beneficial effects on preweaning growth in male lambs and those born in twin births. Acknowledgements The authors thank D.V.M Ramón Andrade Mancilla for providing access to “El Tilzapote” Ranch and technical support during the experiment. Literature cited: 1. Corner RA, Mulvaney FJ, Morris ST, West DM, Morel PCH, Kenyon PR. A comparison of the reproductive performance of ewe lambs and mature ewes. Small Ruminant Res 2013;114:126-133. 2. Kenyon PR, Blair HT. Foetal programming in sheep – Effects on production. Small Ruminant Res 2014;118:16-30. 3. Hess BW, Moss GE, Rule DC. A decade of developments in the area of fat supplementation research with beef and sheep. J Anim Sci 2008;86(14 Suppl):E188204. 4. Whates DC, Abayasekara DRE, Aitken RJ. Polyunsaturated fatty acids in males and female reproduction. Biol Reprod 2007;77:190-201.

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5. Kabaran S, Besler HT. Do fatty acids affect fetal programing? J Health Popul Nutr 2015;33(14):1-9. 6. Meza-Villalvazo V, Magaña H, Sandoval C, Morales M, Chay A, Trejo A. Efecto de los ácidos grasos poliinsaturados sobre población folicular y calidad ovocitaria en ovejas Pelibuey. Universidad y Ciencia 2013;29:255-261. 7. Herrera-Camacho J, Aké-López JR, Ku-Vera JC, Williams GL, Quintal-Franco JA. Respuesta ovulatoria, estado de desarrollo y calidad de embriones de ovejas Pelibuey superovuladas suplementadas con ácidos grasos poliinsaturados. Téc Pecu Méx 2008;46:107-117. 8. Meza-Villalvazo VM, Magaña-Sevilla H, Rojas-Marquez CA, Sandoval-Castro C, TrejoCordova A. El aceite de maíz incrementa los niveles séricos de progesterona y estradiol en ovejas de pelo. Ecosist Recur Agropec 2018;5:583-589. 9. Daghigh Kia H, Asgari Safdar AH. Effects of calcium salts of fatty acids (CSFA) with different profiles (w-3 and w-6) during the flushing period on reproductive performance on Afshari ewes. Small Ruminant Res 2015;126:1-8. 10. Mirzaei-Alamouti H, Mohammadi Z, Shahir MH, Vazirigohar M, Mansouryar M. Effects of short-term feeding of different sources of fatty acids in pre-mating diets on reproductive performance and blood metabolites of fat-tailed Iranian Afshari ewes. Theriogenology 2018;113:85-91. 11. Clayton EH, Wilkins JF, Friend MA. Intergenerational effects of omega-6 fatty acids. 2. Preliminary evidences for the influences of diet fed to dam at conception on sex ratio of lambs born to their daugthers. Anim Reprod Sci 2017;57:51-59. 12. Russel AJF, Doney JM, Gunn RJ. Subjective assessment of body fat in live sheep. J Agr Sci 1969;72(3):451-454. 13. AOAC, 2003. Official methods of analysis. 17th Edition current through 2nd Revition.ED. Association of Official Analytical Chemists, Washington DC, USA. 14. Van Soest PJ, Robertson JB, Lewis BA. Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. J Dairy Sci 1991;74(10):223-232. 15. Alves AR, Beelen PMG, de Medeiros AN, Neto SG, Beelen RN. Consumo e digestibilidad do feno de sabia por caprinos e ovinos suplementados com polietilenoglicol. Rev Caatinga 2011;24:152-157. 16. NRC. Nutrient requirements of sheep. National Academy Press, Washington, DC. 1985.

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17. Cansino-Arroyo G, Herrera-Camacho, Aké-López. Tasas de concepción, fertilidad y prolificidad en ovejas de pelo alimentadas con dietas enriquecidas con ácidos grasos poliinsaturados. Universidad y Ciencia 2009;25:181-185. 18. SAS Institute, SAS/STAT. User´s guide statistical released 9.1. 2nd Ed. SAS Intitute, Inc. Cary, NC, USA; 2004. 19. Clayton EH, Friend MA, Wilkins JF. Increasing the proportion of female lambs by feeding Merino ewes a diet high in omega-6 fatty acids around mating. Anim Prod Sci 2016;56(7):1174-1184. 20. Asgari Safdar AH, Sadeghi AA, Chamani M. Effects of different fat sources (saturated and unsaturated) on reproductive performance and biological indices of ewes during flushing period. Trop Anim Health Prod 2017;49:1447-1453. 21. Macías-Cruz U, Álvarez-Valenzuela FD, Olguín-Arredondo HA, Molina-Ramírez L, Avendaño-Reyes L. Ovejas Pelibuey sincronizadas con progestágenos y apareadas con machos de raza Dorper y Katahdin bajo condiciones estabuladas: producción de la oveja y crecimiento de los corderos durante el período pre-destete. Arch Med Vet 2012;44:2937. 22. Sinclair KD, Allegrucci C, Singh R, Gardner DS, Sebastian S, Bispham J, et al. DNA methylation, insulin resistance, and blood pressure in offspring determined by maternal periconceptional B vitamin and methionine status. Proc Natl Acad Sci U S A 2007;104:19351-19356. 23. Van der Linden DS, Sciascia Q, Sales F, McCoard SA. Placental nutrient transport is affected by pregnancy rank in sheep. J Anim Sci 2013;91:644-653.

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https://doi.org/10.22319/rmcp.v12i2.4856 Technical note

Presence of aflatoxin B1 in goat feed in goat milk production units of the Mexican Highlands

José Jesús Pérez González a Salvador Vega y León a Rey Gutiérrez Tolentino a* Beatriz Sofia Schettino Bermúdez a Fátima Itzel Martínez Solis a Arturo Camilo Escobar Medina ab

a

Universidad Autónoma Metropolitana. Departamento de Producción Agrícola y Animal. Calzada del Hueso 1100, Col. Villa Quietud, Delegación Coyoacán, 04960, Ciudad de México, México. b

Centro Nacional de Sanidad Agropecuaria (CENSA). San José de las Lajas, Mayabeque, Cuba.

*Corresponding author: reygut@correo.xoc.uam.mx

Abstract: The presence of aflatoxins in silage and grains intended for feeding lactating ruminants entails a problem for animal health and milk safety. The objective of this study was to determine the aflatoxin B1 content in feed consumed by goats from four goat milk production units in the Mexican highlands (MHL). Samples (n= 47) of concentrates and 29 samples of silage from four goat milk production units in the Mexican Highlands (MHL) were analyzed by High Performance Liquid Chromatography (HPLC), using a reversed-phase column and fluorescence detection after the derivatization of aflatoxins. The results showed that 38.29 % and 31.02 % of the concentrate and silage samples, respectively, had AfB1 levels above the maximum permissible limit established by the European Union (EU) (0.05 µg/kg); while 29.78 % and 10.34 % for concentrates and silage, respectively, presented values higher than the 20 µg/kg proposed by the official Mexican standard. The results obtained corroborate the current problem of the presence 598


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of aflatoxins in the diet of lactating goats, as this toxin can be metabolized into aflatoxin M1 and affect the safety of milk and milk derivatives. Key words: Aflatoxin B1, Concentrate, Silage, HPLC, Lactating goats.

Received: 13/04/2018 Accepted: 08/01/2020 Today, food safety and quality assurance is an important factor for many countries(1). The health and productivity of an animal, along with the quality and safety of the milk it produces, depend on the quality and management of the feed it consumes. No feed intended for the nutrition of dairy animals should present any risk of physical, chemical or microbiological contamination. Both commercial feed and feed produced on the farm should be considered as a potential health risk; for this reason, before it is provided to dairy cattle such as goats, it should be carefully examined in order to ensure the absence of contaminants (soil, foreign bodies, wire, fungi, among others)(2). Food contamination by fungi is a very frequent phenomenon, due to the fact that their spores are widely distributed in the environment (air, water, soil) so that agricultural production (mainly grains and seeds) is affected by more than 25 % by the presence of some type of mycotoxins(3). Fungi can develop at any point in the food chain under conditions (pH, relative humidity, grain moisture, viability, storage time, and the presence of microflora) that favor their development(4); it is worth mentioning that some species of fungi are able to colonize and produce aflatoxins in different media, such as food and animal feed. Aflatoxins are toxic substances produced in the secondary metabolism of the fungi Aspergillus flavus, Aspergillus parasiticus, and Penicillium puberulum(5). Eighteen (18) types of aflatoxins have been identified, of which six are significant food contaminants: B1, B2, G1, G2, M1, and M2; AfB1 is the most carcinogenic and toxic of these(4). Aflatoxins, when found in fodder, silage and concentrates, can be present in their original form, or metabolized in animal tissues when consumed by animals. Its metabolites include aflatoxin M1 (AfM1), which is excreted in milk(6,7). The first studies on the determination of AfM1 in Mexico were carried out in the state of Sonora by Esqueda et al(8) in samples of ultra-pasteurized cow's milk marketed in that state, and the presence of AfB1 in feed for dairy goats in Mexican herds has not been reported either. Some of the countries in which research has been conducted on goat food, milk and dairy products are Egypt(9,10), Cuba(11), Portugal(12), Spain(13), Italy(14-17), Brazil(18), Turkey(19,20) Kenya(21,22), and South Africa(23). Most of the researches determined the transfer of AfB1 from food to AfM1 in milk and cheese. They also evaluated the AfM1 content in milk and cheese, finding up to 69 % of positive samples 599


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with levels above the maximum permissible limit established by the European Union (EU), of 0.05 µg/kg for milk, and up to 19 % of positive samples with levels above the maximum permissible limit established by the EU for cheese. In Mexico, the current status of the presence of AfB1 in goat feed is unknown, and so is the permanent application of methods and techniques to assess this mycotoxin considered as pathogenic. The objective of this study was to determine the AfB1 content in feed for goats from four goat milk production units of the Mexican Highlands (MHL). The methodology was developed as follows: 47 samples of concentrates (composed mainly of corn, sorghum and soybean) and 29 samples of corn silage were obtained from four goat milk production units (Unit 1, Unit 2, Unit 3 and Unit 4) of the MHL. Samples were taken simultaneously each month during the period from June 2008 to August 2009, according to the methodology proposed by the Norm NOM-188-SSA1-2002(24). The minimum amount for each sample was one kilogram, taken from different points of the lot. Samples were transported to the laboratory in clean, labeled containers, protected against contamination and deterioration during transport. Samples were analyzed for AfB1 content by HPLC with fluorescence detector according to AOAC Methods 968.22 (extraction and chromatographic column), 971.22 (preparation of solutions and determination of aflatoxin concentration), and 990.33 (derivatization)(25), as well as to the ISO 14718 method (high performance liquid chromatography)(26). For sample processing, 500 g of sample were ground in a mill and passed through a sieve with an aperture of 1 mm. Subsequently, the sample was divided by the quarting procedure, taking the sample diagonally, mixed and stored in a nylon bag or tightly closed flask. For the extraction, 50 g of previously ground and sieved sample was weighed to the nearest 0.1 g and placed in an Erlenmeyer flask with a lid, and 25 g of Celite 545, 25 ml of water and 250 ml of chloroform were added to it. The cap was secured and mechanically agitated for 30 min. Subsequently, the solution was decanted by passing it through a fluted filter paper. The first 50 ml of the filtrate were collected and stored in an amber bottle at 4 ºC until analysis. For purification, the bottom of a chromatographic column was filled with glass wool, 5 g of anhydrous sodium sulfate (J.T. Baker) and a sufficient amount of chloroform was added up to the middle of the column. Next, a solution of 10 g of silica gel (J.T. Baker) in chloroform was added by sliding it over the walls of the column. The column walls were washed with 20 ml of chloroform and allowed to drain. When 5 to 7 cm of chloroform remained above the silica, 15 g of anhydrous sodium sulfate were added leaving 1 to 2 cm of chloroform above the top of the sulfate. The chloroform was then drained to the top of the sulfate. The sample was added and drained until it reached the top of the column, which was washed with 150 ml of hexane and 150 ml of diethyl ether. Both washes were discarded and the aflatoxins were eluted with 150 ml of a mixture of chloroform and methanol (97:3 v/v). The chloroform:methanol eluate was rotoevaporated to near dryness under reduced pressure at a temperature of 30 ºC. The 600


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residue obtained was transferred to a vial and recovered with 500 to 1000 μl of chloroform and evaporated to dryness under nitrogen. 200 μl of hexane were added to the dry residue and stirred with the vortex (ZX4 Advanced IR Vortex Mixer- VELP Scientifica) for 1 min. Subsequently, 50 μl of trifluoroacetic acid were added, capped and vortexed for 1 min and placed in a double boiler at 40 ºC for 30 min. After this time, they were evaporated under nitrogen. The residue was resuspended in 500 μl of the mobile phase (200 ml methanol, 200 ml acetonitrile, and 600 ml water, filtered and degassed) before being subjected to a chromatography. In order to derivatize the standard, 50 μl of the known concentration of the standard was taken, brought to dryness under nitrogen and proceeded in the same way as described above. A MerckHitachi high-performance liquid chromatograph with a LaCrhom-7480 fluorescence detector (excitation and emission length of 350 nm and 450 nm, respectively) and a C 18 Lichrocart 100 reverse phase column (5µm 250 x 0.4 cm) were used. The flow rate was 1 ml/min. First, a mobile phase followed by the standard was applied to check the retention times. Subsequently, 50 μl of the eluate from the samples were applied. Chromatograms were recorded using a Perkin Elmer NCI 900 interface and processed with TOTALCHROM version 6.2 software. Method validation was performed under the guidelines of the National Metrology Center (Centro Nacional de Metrología)(27). A standard curve with known concentrations of 0.1, 0.25, 0.5, and 1 µg/ml was prepared from the working solution in order to establish the linearity, limit of detection, limit of quantification, and accuracy of the method. The results were as follows: Figure 1 shows the chromatographic profile of AfB1 when the standard is derivatized with trifluoroacetic acid. The retention time was 5.21 ± 0.10 min. The calibration curve (y=312869.71x+218056.30) showed significant linearity (P<0.05) over a range of 0.10 to 1 µg/ml with a regression coefficient of 0.99. The limits of detection and quantification were 0.241 and 0.43 µg/kg, respectively. Recovery was 87 %. The results obtained were satisfactory according to the criteria proposed in the Laboratory Guide for Method Validation(27), and they show that the method was efficient in assessing the presence of AfB1 at the levels required by the EU(28) and the Norm NOM-188-SSA1-2002(24) for 5 and 20 µg/kg, respectively.

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Figure 1: Chromatographic profile of the derivatized AfB1 standard (2.19 µg/ml)

Chromatogram 1 is of the reagent blank where the signal (A) corresponds precisely to the solvent peak.

Table 1 shows a summary of the number of concentrate and silage samples at different AfB1 content ranges, where it is observed that 38.29 and 31.0 % of the samples exhibited AfB1 levels above the maximum permissible limit established by the EU (5 µg/kg) for concentrates and silage, respectively(28). On the other hand, 29.78 and 10.3 % of the concentrate and silage samples, respectively, exceed the value established in the Mexican norm (NOM-188-SSA1-2002)(24). Table 1: Occurrence of aflatoxin B1 in concentrate and silage samples in four goat milk production units Frequency distribution in % Matrix Analyzed samples, No. Positive samples exceeding established by the EU, % Positive samples exceeding established by the NOM, %

Concentrate Silage the

MPL

the

MPL

nd-5 µg/kg 5-20 µg/kg >20 µg/kg

Total

47 38.3

29 31

76 69.3

29.8

10.3

41.1

29 (61.7%) 4 (8.5%) 14 (29.7%)

20 (68.9%) 6 (20.6%) 3 (10.3%)

49 (64.4%) 10 (13.1%) 17 (22.3%)

MPL = maximum permitted level; EU= European Union; NOM= Mexican Official Norm.

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Figure 2 shows the ranges of aflatoxin B1 concentrations per unit for concentrate and silage samples, where the concentration range ranged from 0.46-974 µg/kg and 0.44123.98 µg/kg, respectively. Unit 1 for concentrate showed the highest aflatoxin values with a median of 125 µg/kg, while unit 2 for silage showed a median of 8 µg/kg. 22.3% of all samples (concentrates and silage) showed values above 20 µg/kg, reaching levels up to 50 times the permissible value, an aspect of great concern due to the risk it may pose to the safety of dairy products(29). Figure 2: AfB1 concentrations in concentrates (A) and silage (B) from four goat milk production units in the Mexican highlands

In graph B in Unit 1, the aflatoxin value is not provided because this product is not offered.

The presence of aflatoxins in corn in high concentrations in the order of thousands of µg/kg has been reported by several authors in the African region(30), where there is a predominance of a subtropical and tropical climate characterized by high temperature and humidity, which, together with poor agricultural and production practices, favors the growth of these toxins(31). Reports in other regions such as Asia and Latin America(32), also report high aflatoxin levels in food, which corroborates the global problem of this toxin and has been alerted by the Food and Agriculture Organization of the United Nations (FAO) in different scenarios, where the risk of aflatoxin contamination is expected to increase in corn due to the effect of climate change(33). Another factor that conditions the level and synthesis of aflatoxins is the substrate. Thus, foods with high concentrations of carbohydrates favor the production of toxins(29). Carbohydrates are the most important part of cereals such as corn, oats, sorghum and soybeans, used for the production of concentrates that are fed to goats, and are therefore more susceptible to fungal contamination and the consequent synthesis of aflatoxins. The presence of aflatoxin B1 in silage has also been reported when aerobic spoilage occurs during processing, which favors the growth of pathogenic microorganisms and the production of endotoxins and mycotoxins(34,35). A study carried out in Brazil showed aflatoxin B1 values in corn silage in a range of 0-100 µg/g in pre- and post-fermented samples(36), which are higher than those found in this study. Other studies also reflect 603


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high counts of fungi, which could affect the palatability of feed and reduce nutrient absorption by animals(37). However, the greatest causes for concern are the consumption of these foods by lactating animals and the presence of metabolic products in dairy products, which will eventually affect human health, mainly that of infants. The presence of the aflatoxin M1 in milk is a result of the metabolic transformation of aflatoxin B1; thus, a contamination rate of 13.4 % in feed materials results in AfM1 levels estimated between 0.22 to 3.47 %(38). A study conducted on 17 goat farms in northeastern Italy showed a positive correlation (0.6) between the presence of aflatoxin B1 in the concentrate and aflatoxin M1 in milk, where concentrations of 5 µg/kg aflatoxin B1 in feed exhibited an aflatoxin M1 conversion rate of 0.5 % (25 ng/kg milk)(39). These results alert regulatory agencies in predicting the presence of aflatoxin M1 in milk in these units. Given that the median concentration of AfB1 in concentrate and silage was higher than 20 µg/kg in this study and considering a conversion rate of 0.5%, it is possible to find more than 100 ng of aflatoxin per kilo, which is above the MPL established by the FDA. On the other hand, greater control of the feed used in livestock farms is required in order to minimize the impact of mycotoxins on the dairy industry and public health. This aspect has been corroborated in several studies when there is a continuous improvement of feeding techniques in dairy farms(40). There was a high concentration of AfB1 in the four goat milk production units of the MHL, above the maximum permissible limits established. Therefore, it is necessary to pursue further research and to develop a permanent detection program in these units in order to avoid batches of food contaminated with AfB1, since it should be kept in mind that the absence of AfB1 is very important for the dairy industry, because when an animal ingests food contaminated with AfB1, between 1 and 3% of this aflatoxin is metabolized into the milk and dairy products in the form of AfM1, which affects the quality and safety of milk and dairy products. The presence of aflatoxin B1 in silage in Mexico was reported herein for the first time, an aspect that should be further researched to detect the presence of other mycotoxins that also affect public health, such as ochratoxin, zearalenone and fumonisins, which have been reported in tropical countries such as Brazil. On the other hand, given that goat milk production in Mexico has increased in the last decade and due to the lack of information on this subject, longitudinal studies should be strengthened in order to understand the presence of AfB1 and AfM1 in goat production, adding as well other areas with great potential for goat milk production.

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Literature cited: 1. FAO. Food and Agriculture Organization of the United Nations. Sistemas Nacionales de Inocuidad de Alimentos en las Américas y el Caribe: Análisis de la situación actual http://fao.org/docrep/fao/010/j6410s.pdf 20/05/08. Consultado 30 Ago, 2017. 2. Trujillo J. Lineamientos para el reconocimiento de las buenas prácticas en producción de leche caprina. (2002). Fuente: http://64.233.187.104/search?q=cache:ILqy5ULsQi8J:www.senasica.sagarpa.gob. mx/web/propuestas_web/221204/inocuidad_agroalimentaria/Lineamientos. Consultado 30 Ago, 2017. 3. Escobar A, Vega S, Gutiérrez R, Coronado M, Díaz G. Aflatoxina M1 en leche y derivados lácteos. Actualidad y Perspectivas en América Latina. Carnilac Ind 2005;20:21-27. 4. Vega S, León J. Residuos tóxicos en alimentos. Conceptos y métodos. 1.a ed. CDMX, México: UAM-X. 1998. 5. Bolet M, Socarrás M. Micotoxinas y cáncer. Rev Cubana Invest Bioméd 2005;24:5459. 6. Gimeno A, Martinez M. Residuos de Aflatoxina M1 y otras micotoxinas en leche y derivados, control y recomendaciones http://www.engormix.com 20/05/08. 2001. Consultado 14 Jul, 2017. 7. Noa M, Pérez N, Gutiérrez R, Escobar A. Los residuos químicos en la leche: importancia y problemática actual en México y en el mundo. 1.a ed. México, DF, UAM-X; 2001:192. 8. Esqueda M, Higuera I, Nieblas J. Aflatoxina M1 en leche comercializada en Hermosillo, Sonora, México. Rev Mex Mic 1995;11:179-183. 9. Helferich W. Aflatoxin in food producing animals: metabolism and transmission. Dissertation Abstr Internat 1984;44:3583-3605. 10. Mashaly R, El-Deeb S, El-Nouty F, Hassan G, Salem M. Effect of feeding aflatoxins to Egyptian Baladi goats on milk yield, composition and physical properties. Egypt J Dairy Sci 1984;12:135-144. 11. Acosta A, Escobar A, Margolles E, Mella C. Dinámica de excreción de aflatoxina M1 en leche de cabras. Rev Salud Anim 1989;11:208-211. 12. Bento H, Fernandes A, Barbosa M. Detection of aflatoxin M1 in goat milk [abstract]. XXIII International Dairy Congress. Montreal. Quebec. 1990:26. 13. Barrios M, Gualda M, Cabanas J, Medina LM, Jordano R. Occurrence of aflatoxin M1 in cheeses from the south of Spain. J Food Protect 1996;59:898-900. 605


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14. Finoli C, Vecchio A. Aflatoxin M1 in goat dairy products. Mic Aliment Nut 1997;15:47-52. 15. Minervini F, Visconti A, Bottalico A, Montagna M. On the occurrence of aflatoxin M1 in cheeses in some southern Italian areas. Ind Aliment-Italy 2001;40:513-516. 16. Battacone G, Nudda A, Palomba M, Pulina G. Carry over of aflatoxin from feed to ovine milk and curd. Scienza e Tecnica Lattiero-Casearia 2002;53:283-293. 17. Virdis S, Corgiolu G, Scarano C, Pilo A, De Santis E. Occurrence of aflatoxin M1 in tank bulk goat milk and ripened goat cheese. Food Control 2008;19:44-49. 18. Oliveira C, Ferraz J. Occurrence of aflatoxin M1 in pasteurised, UHT milk and milk powder from goat origin. Food Control 2007;18:375-378. 19. Bingol N, Tanritanir P, Dede S, Ceylan E. Influence of aflatoxin present in forages and concentrated feedingstuffs on milk and some serum biochemical parameters in goats. B Vet I Pulawy 2007;51:65-69. 20. Ozdemir M. Determination of aflatoxin M1 levels in goat milk consumed in Kills province. Ankara Univ. Vet. Fak. 2007;54:99-103. 21. Anyango G, Mutua F, Kagera I, Andang`O P, Grace D, Lindahl J. A survey of aflatoxin M1 contamination in raw milk produced in urban and peri-urban areas of Kisumu County, Kenya. Infect Ecol Epidemiol 2018;8:1-10. 22. Kilonzo R, Imungi J, Muiru W, Lamuka P, Kamau Njage P. Household dietary exposure to aflatoxins from maize and maize products in Kenya. Food Addit Contam 2014;31:2055-2062. 23. Bingol N, Tanritanir P, Dede S, Ceylan E. Influence of aflatoxin present in forages and concentrated feedingstuffs on milk and some serum biochemical parameters in goats. B Vet I Pulawy 2007;51:65-69. 24. NOM-188-SSA1-2002. Norma Oficial Mexicana. Productos y Servicios. Control de aflatoxinas en cereales para consumo humano y animal. Especificaciones sanitarias. Secretaría de Salud. Diario Oficial de la Federación. 14 de junio de 2000. 25. AOAC. Oficial methods of analysis. 15th ed. Arlington, VA, USA: Association of Official Analytical Chemists. 1995. 26. ISO. International Organization for Standardization. Animal feeding stuffsdetermination of aflatoxin B1 content of mixed feeding stuffs-method using highperformance liquid chromatography. ISO. 14718:1998. 27. CENAM. CNM-MRD-PT-030. Métodos analíticos adecuados a su propósito. Guía de Laboratorio para la Validación de Métodos y Temas Relacionados. Centro Nacional de Metrología. Publicación Técnica. Los Cués, Querétaro., México. 2005. 606


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28. UE. Commission Directive 2003/100/EC. Amending Annex I to Directive 2002/32/EC of the European Parliament and of the Council on undesirable substances in animal feed. European Union. Official Journal of the European Union. Brussels. 2003. 29. Moss M. Risk assessment for aflatoxins in foodstuffs. Int Biodeter Biodegr 2002;50:137-142. 30. Misihairabgwi JM, Ezekiel CN, Sulyok M, Shephard GS, Krska R. Mycotoxin contamination of foods in Southern Africa: A 10-year review (2007–2016). Critical Rev Food Sci Nutr 2017;1-16. 31. Matumba L, Van Poucke C, Njumbe Ediage E, De Saeger, S. Keeping mycotoxins away from the food: Does the existence of regulations have any impact in Africa. Crit Rev Food Sci Nutr 2014;57(8):1584-1592. 32. Bhat R, Rai V, Karim A. Mycotoxins in food and feed: present status and future concerns. Compr Rev Food Sci Food Saf 2009;9:57-81. 33. EFSA. Modelización, predicción y cartografía de la aparición de aflatoxinas en los cereales en la UE debido al cambio climático. Informe científico presentado por la Autoridad Europea de Seguridad Alimentaria. 2012. Fuente: https://efsa.onlinelibrary.wiley.com/doi/epdf/10.2903/sp.efsa.2012.EN-223. Consultado 20 ago, 2017. 34. Pahlow G, Muck R, Driehuis F, Oude Elferink S, Spoelstra S. Microbiology of ensiling. Silage science and technology (Agronomy Series No. 42). Buxton DR, et al editors. Am Soc Agron. Madison, WI. 2003. 35. Ferrero FS, Prencipe D, Spadaro ML, Gullino L, Cavallarin S, Piano E, Tabacco BG. Increase in aflatoxins due to Aspergillus section Flavi multiplication during the aerobic deterioration of corn silage treated with different bacteria inocula. J Dairy Sci 2019;102(2):1176-1193. 36. Keller M, Pereyra M, Keller K, Alonso V, Oliveira A, Almeida T, et al. Fungal and mycotoxins contamination in corn silage: Monitoring risk before and after fermentation. J Stored Prod Res 2013;52:42–47. 37. Alonso A, Pereyra C, Keller L, Dalcero A, Rosa C, Chiacchiera S. Cavaglier L. Fungi and mycotoxins in silage: an overview. J Appl Microbiol 2013;115(3):637643. 38. Dimitrieska-Stojković, E, Stojanovska-Dimzoska, B, Ilievska, G, Uzunov, R, Stojković G, Hajrulai-Musliu Z, et al. Assessment of aflatoxin contamination in raw milk and feed in Macedonia during 2013. Food Control 2016;59:201-206.

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39. Sacca E, Boscolo D, Vallati A, Ventura W, Bigarand F, Piasentiera E. Aflatoxin ocurrence in milk and supplied concentrates of goat farms of north-eastern Italy. J Sci Food Agric 2009;89(3):487-493. 40. Cammilleri G, Graci S, Collura R, Buscemi MD, Vella A, Macaluso A, et al. Aflatoxin M1 in cow, sheep, and donkey milk produced in Sicily, Southern Italy. Mycotoxin Res 2019;35(1):47-53.

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https://doi.org/10.22319/rmcp.v12i2.5466 Technical note

Prediction of the fermentative quality of sunflower silage by nearinfrared reflectance spectroscopy (NIRS) on oven-dried samples

Sonia Pereira-Crespo a Aurora Sainz-Ramírez b Dalia Andrea Plata-Reyes b Aida Gómez-Miranda b Felipe González-Alcántara b Adrián Botana a Laura González a Marcos Veiga a Cesar Resch a Roberto Lorenzana c Fernando Próspero-Bernal a* Carlos Manuel Arriaga-Jordán b Gonzalo Flores-Calvete a

a

Centro de Investigacións Agrarias de Mabegondo de la Axencia Galega da Calidade Alimentaria de la Consellería do Medio Rural. Xunta de Galicia, Mabegondo, Abegondo, A Coruña, Galicia, España. b

Universidad Autónoma del Estado de México, Instituto de Ciencias Agropecuarias y Rurales. Toluca, Estado de México, México. c

Laboratorio Interprofesional Galego de Análise do Leite, Mabegondo, Abegondo, A Coruña, Galicia, España.

*

Corresponding author: fer_104_7@hotmail.com 609


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Abstract: The objective of the present work was to evaluate the predictive ability of calibration equations developed by NIRS (near-infrared reflectance spectroscopy) on dry and ground samples for estimating the fermentative quality of sunflower silage. NIRS spectra of a total of 52 oven-dried and ground silage samples from different laboratory silo tests carried out at the Mabegondo Agricultural Research Center (Centro de Investigacións Agrarias de Mabegondo, CIAM) were registered. The fresh samples were analyzed using reference methods. The pH, lactic acid, acetic acid, ethanol, ammonia nitrogen and soluble nitrogen levels were determined. NIRS calibrations were developed by modified partial least squares regression, performing a regression between spectral and reference data. The predictive capacity of the equations obtained ranged from excellent to good, with cross-validation coefficients of determination (r2cv) equal to or above 0.88. The RPD index values for all the parameters studied were equal to or above 3.0; therefore, the calibration equations obtained on dry and ground samples can be used satisfactorily to predict the fermentative quality of sunflower silages in routine analyses. Key words: Forage crops, Fermentation parameters, Reflectance spectroscopy.

Received: 23/08/2019 Accepted:18/04/2020

The nutritional evaluation of forages is relevant due to the high variability of their nutritional value and to their high contribution to the total dry matter of cattle rations, compared to concentrate. In addition to the intrinsic characteristics of the forage at the time of cutting, the nutritional value of the silage is fundamentally conditioned by the quality of fermentation developed during storage in the silo(1), being highly variable depending on forage ensilability and post-harvest treatment(2), and particularly affecting the nitrogen value and the voluntary intake of silage(3). Therefore, for an efficient use of silage, its fermentative quality must be first characterized, for which it is essential to have fast, accurate and reliable methods. Instrumental analyses for determining the fermentative quality parameters of silage are complex, time-consuming and costly. NIRS (Near-Infrared Reflectance Spectroscopy) technology is widely recognized as a fast, inexpensive and highly accurate analytical technique for characterizing the keeping quality of silage as an alternative to wet analysis(4). Moreover, it is an environmentally clean technology that uses no reagents and generates no waste. NIRS analysis of silage in intact mode, in its fresh state, involves great difficulty, due to the high heterogeneity of the material(5). On the other hand, the presence of water in the intact sample interferes with the 610


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NIRS spectrum, since it absorbs part of the infrared radiation, generating two very significant absorption bands in the spectrum. However, it should be noted that NIRS analysis of dried samples has disadvantages compared to analysis with fresh samples, because the volatile constituents of silage, such as fermentation acids, alcohols and ammonium, are released and lost during the drying process of the sample. In one study, a series of samples before and after the drying process were determined by reference methods, and the prediction of the NIRS equations developed on dry samples were compared with those performed on wet material. As a result, it was observed that the prediction of pH, lactic acid and ammonia nitrogen was more robust on dry material, while the quality of the prediction for acetic acid was better when the NIRS measurement was performed on the wet sample(6). This is attributed to the fact that the quality of prediction obtained for the different parameters by the two methods is not related to the losses during the drying of the samples, since the reduction in the concentration of lactic acid, acetic acid, ethanol and ammonia nitrogen in the dry matter during drying was 3.5, 57, 53 , and 100 %, respectively, for grass silage, and 3.5, 83, 16, and 100 % for corn silage, in clear correspondence with their volatility (free version)(6). On the other hand, another study evaluated the effect of a corn silage sample preparation (fresh vs. dry and ground) on the estimation of fermentation parameters by NIRS. The results indicate that fresh samples provide a slightly higher predictive ability for acetic acid (r2cv = 0.85 vs 0.82) and lactic acid (r2cv = 0.78 vs 0.73), and a lower predictive ability for pH (r2cv = 0.54 vs. 0.63)(7). A study carried out at the Mabegondo Agricultural Research Center (Centro de Investigacións Agrarias de Mabegondo, CIAM) in Galicia indicates the convenience of using dry and ground samples instead of intact ones, by obtaining predictive models of the chemical composition and fermentative quality of grass silage with higher accuracy(8). In another work recently carried out at CIAM, the prediction of fermentation parameters of grass silage was evaluated by means of NIRS calibrations, developed on dry and ground material; the results obtained were satisfactory, with determination coefficients equal to or above 0.80(9). The knowledge of the fermentative quality of new types of forages in a fast and accurate way requires progress in the development of new NIRS calibrations. In this sense, the objective of the present work was to evaluate the predictive capacity of NIRS calibration equations in dry and ground samples to estimate fermentative quality parameters of sunflower silage. The work was carried out with a total of 52 sunflower silage samples from different laboratory silo trials conducted at CIAM in 2016 and 2017. The collection of samples covers a high variability in terms of maturity stage, including sunflower samples harvested at different phenological stages according to the Schneiter and Miller scale, from stage R4 (1 wk before flowering) to stage R7 (5 wk after the beginning of flowering)(10). The forage used for filling the laboratory silos came from the cultivation of two commercial hybrids: a forage variety (Rumbosol 91) and an oil variety (ES Shakira), grown on CIAM's experimental farms 611


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located in two locations in Galicia (Spain): Mabegondo (in the northwestern Atlantic coastal area of Galicia, at 100 masl) and Pobra de Brollón (an inland area of Galicia, at 400 m asl). In addition, the trials included silage without additives and with different additives: formic acid and two commercial inoculants (one based on homofermentative lactic acid bacteria, and the other, on homo- and heterofermentative lactic acid bacteria). The laboratory silos were opened 60 d after they were filled. The silage samples, after manual homogenization, were divided into two aliquots, one of which was dried in an oven at 80 ºC for 16 h(11), while the other was frozen at -18 ºC; both were vacuum-packed in hermetically sealed plastic containers until fermentative analysis was performed using reference methods. The spectral information of the dried and ground samples at 1 mm was obtained in a Foss NIRSystem 6500 monochromator spectrophotometer (Foss NIRSystem, Silver Spring, Washington, USA), located in a temperature-controlled room (24 ± 1 °C) and equipped with a spin module that performs reflectance (R) measurements in the spectral region between 400 and 2,500 nm, at 2 nm intervals. Absorbance data are expressed as Log (1/R, R= Reflectance). The spectra collection and chemometric analysis of the data was carried out using Win ISI II v.1.5 software (Infrasoft International, Port Matilda, PA, USA)(12). Using the CENTER algorithm(13), a Principal Component Analysis (PCA) was performed, followed by the calculation of distances between spectra in an n-dimensional space through the Mahalanobis distance, which allowed studying the structure and spectral variability of the population and detecting anomalous samples(13). The Global Mahalanobis distance (GH) is defined as the distance between a sample and the center of the population in the space defined by the PCA (Figure 1), considering as outlier samples those with GH values above 3 (spectral outlier)(13). Figure 1: Three-dimensional representation of spectral data of samples according to the global Mahalanobis distance

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SNV-Detrend pretreatment was applied to the spectral data(14) in order to correct for the scattered radiation phenomenon and the following eight mathematical treatments were evaluated: 1,5,5,1; 1,6,4,1; 1,10,5,1; 1,10,10,1; 2,5,5,1; 2,6,4,1; 2,10,5,1; 2,10,10,1. The first digit expresses the order of the derivative (1= first derivative, 2= second derivative); the second digit indicates the size of the segment on which the derivative is performed (interval expressed in nanometers); the third and fourth digits indicate the size of the intervals, expressed in nanometers, used for the signal smoothing calculation(15). The development of the calibration equations was performed by modified partial least squares regression (MPLS)(16) between spectral and reference data, including four crossvalidation groups to prevent overfitting, which were used sequentially to perform the validation of the generated equations. Fermentative analysis of intact silage samples was performed by reference methods, in duplicate(17). On an extract of 50 g of fresh silage sample, macerated at room temperature for 2 h in 150 ml of distilled water, pH, ammoniacal nitrogen (N-NH3) was determined with a selective electrode (Orion) and soluble nitrogen (sol-N) by macro Kjeldahl digestion. Fermentation acids (lactic, acetic, and propionic) and ethanol were determined by gas chromatography (Agilent Technologies, USA) with a BR-SwaxAcids high polarity capillary column (30 m x 0.53 mm x 1 µm; Bruker, USA). N-NH3 and sol-N parameters referred to total nitrogen, and fermentation acids and ethanol, to dry matter. The statistics used to select the best calibration equations were the standard errors of calibration (SEC) and standard errors of cross-validation (SECV) and the coefficients of determination (r2c and r2cv) obtained in the calibration and cross-validation process, respectively(18). In addition, other useful statistics were utilized to evaluate the predictive capacity of the calibration equations obtained, such as the RER index, or the ratio between the range of the reference data and the SECV, and the RPD index, or the ratio between the standard deviation of the reference data and the SECV(19). The descriptive characteristics (range, mean, and standard deviation) of the fermentation parameters of the calibration collective are shown in Table 1; they exhibit a wide range and a high standard deviation for each of the components analyzed using reference methods. This high variability confirms that this group is made up of very diverse silages, a key factor for obtaining robust calibration equations(20). The mean value (and range of variation) of the dry matter content of the silage population that made up the calibration set was 16.0 % (11.3 to 21.9 %).

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Table 1: Range, mean, and standard deviation of fermentative quality parameters of the calibration group (n=52) of sunflower silage Parameter

Range

Mean

SD

pH

3.55

4.29

3.91

0.21

Lactic acid, %DM

0.00

15.74

7.99

5.51

Acetic acid, %DM

0.52

4.04

2.39

1.10

Ethanol, %DM

0.90

12.50

3.78

3.43

N-NH3, %TN

2.21

10.37

6.09

2.59

Soluble N, %TN

26.96

52.95

41.41

7.68

DM= dry matter; N-NH3= ammonia nitrogen; TN= total nitrogen; SD= standard deviation.

Table 2 shows the statistics of the calibration equations obtained for the prediction of fermentation quality parameters. The coefficients of determination in the cross-validation process (r2cv) provide information on the quality of the calibration, based on which three levels of accuracy of the prediction models have been defined: r2cv values above 0.90 indicate excellent predictive ability; r2cv values between 0.89 and 0.70 indicate that the calibration is considered to have good quantitative predictive ability, and calibrations with r2cv values between 0.69 and 0.50 allow only adequate discrimination between high, medium and low values(21). Therefore, the r2cv values for pH (r2cv =0.98), N-NH3 (r2cv =0.96), acetic acid (r2cv =0.94), lactic acid (r2cv =0.90), and ethanol (r2cv =0.90) parameters indicate an excellent predictive ability, while the soluble N content (r2cv =0.88) exhibits a good accuracy ability(21). The accuracy of the prediction can be judged according to the values of the RER and RPD indexes(19); RPD values above 3 and RER values above 10 are taken as indicators of the usefulness of the predictions(19). The high standard deviation and the wide range of variation of the calibration collective account for the adequate RPD (3.0 - 6.5) and RER (9.0 - 22.8) values obtained.

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Table 2: Statistics of the calibration equation developed for the prediction of fermentative quality parameters of sunflower silage Parameter

MT

SEC

r2c

SECV

r2cv

RER

RPD

pH

(1,5,5,1)

0.02

0.99

0.03

0.98

22.8

6.5

Lactic acid, %DM

(2,10,10,1)

1.63

0.91

1.75

0.90

9.0

3.2

Acetic acid, %DM

(2,10,5,1)

0.17

0.97

0.25

0.94

13.9

4.3

Ethanol , %DM

(2,6,4,1)

0.97

0.92

1.07

0.90

10.9

3.2

N-NH3, %TN

(2,10,10,1)

0.44

0.97

0.54

0.96

15.1

4.8

Soluble N, %TN

(2,10,10,1)

2.18

0.92

2.58

0.88

10.1

3.0

DM= dry matter; MT= mathematical treatment; N-NH3= ammonia nitrogen; TN= total nitrogen; SEC= standard error of calibration; SECV= standard error of cross validation; r2c and r2cv: coefficient of determination in calibration and cross validation; RER= Range/SECV; RPD= standard deviation/SECV.

The prediction equations for pH, acetic acid, ethanol, N-NH3 and sol-N exhibit values of RPD>3 and RER >10, in compliance with those recommended in the literature(19). Thus, the pH value is the most accurately estimated one (RER=22.8; RDP=6.5), followed by the values for acetic acid (RER=19.5; RDP=4.3), N-NH3 (RER=19.5; RDP=4.3), ethanol (RER=10.9; RDP=3.2), and sol-N- (RER=10.1; RDP=3.0). In the case of the lactic acid prediction equation, the value of the RER index (9.0) did not reach the recommended value; however, the RPD value (3.2) exceeds the minimum value recommended in the literature(19). Therefore, the values of the RER and RPD statistics confirm the high accuracy and precision of the equations obtained, ensuring their validity from the point of view of their application in quantitative analysis(19). There is little information in the literature on the applicability of the NIRS technique for predicting the pH of forage sunflower silage(22). A work carried out with a group similar to the present work ―a collection of 50 dry and ground samples of experimental sunflower silage― exhibited a lower predictive capacity for pH estimation than the present work, with lower values of r2cv (0.86), RER (5.9), and RPD (2.5), and higher values of SECV (0.44)(22). Other studies, carried out on fresh samples, have obtained a lower predictive capacity for the pH value than the one determined in this work, with r2cv values of 0.85, 0.72, and 0.78 for grass silage(4), barley silage(23), and ryegrass silage(24), respectively. The lactic acid, acetic acid, and ethanol content in fresh grass silage samples were determined with a lower precision than that observed in this study, with r2cv and RPD values of 0.83 and 2.5, 0.73, and 2.0, and 0.77 and 2.8, respectively(25). Values of r2cv and RPD of 0.89 and 3.3 615


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for sol-N, and of 0.92 and 4.0 for N-NH3(25) ―similar to those obtained in this study― have been reported for grass silage. Once the prediction models have been developed, the fit of the data to the model must be evaluated, for which purpose a chart of the values predicted by NIRS versus the reference values is used. Figure 2 shows such a chart for the fermentation quality parameters studied. The results obtained exhibited a high correlation between the values predicted by NIRS and the reference values for all the parameters studied, with values for the coefficient of determination (R2) of the regression above 0.90, while the values of the slope of the regression ranged between 0.98 and 1.01, confirming the high precision of the equations developed, with values close to 1 in both cases(26). Figure 2: Reference vs predicted values by NIRS for all fermentation parameters

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The reference values of the studied parameters are distributed among all concentration ranges and in a very broad range of variation. In the case of lactic acid concentration, the analytical reference values show a very broad range of variation, but they are not distributed among all concentration ranges (Figure 2), with most of the samples in the range between 6 and 15.7 % DM, and only a small number of samples between 0 and 2 % DM. These low lactic acid contents are related to the application of formic acid to the silages(27). This work should be considered preliminary as it is based on a limited number of samples, and it is desirable to increase the database in future studies(18). It is advisable to incorporate new representative samples, with values distributed among the least represented sectors, mainly for the lactic acid content; increasing the number of samples of the calibration group will reinforce and increase the robustness of the developed models(18). The authors conclude that NIRS technology, applied to dry and ground samples, is a useful and appropriate tool for the prediction of fermentative quality parameters of sunflower silage, and, therefore, an alternative for determining these parameters in relation to conventional analytical methods. Acknowledgments and conflicts of interest This work was funded by projects ATT 2016/106, ATT 2017/180 and 2017/182 of the Ministry of Rural Affairs of the Xunta de Galicia (Consejería del Medio Rural de la Xunta de Galicia). The authors thank the National Council for Science and Technology of Mexico (Consejo Nacional de Ciencia y Tecnología) for awarding mixed grants to Sainz-Ramírez, Plata-Reyes, Gómez-Miranda, and González-Alcántara, and postdoctoral fellowships to Prospero-Bernal. The authors declare that they have no conflicts of interest. Literature cited: 1. Demarquilly C. Composition chimique, caractéristiques fermentaires, digestibilité et quantité ingérée des ensilages de fourrages: modifications par rapport au forage vert initial. Annales de Zootechnie 1973;(22):1-35. 2. McDonald P. Silage fermentation. In : Forage Conservation in the 80´s. E.G.F. Occasional Sympossium nº 11. British Grassland Society. Brighton, Reino Unido. C. Thomas 1979:6775. 3. Woolford MK. The silage fermentation. Nueva York, EEUU. Marcel Dekker, Inc. 1984:350.

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4. Park RS, Agnew RE, Gordon FJ, Barnes RJ. The development and transfer of undried grass silage calibrations between near infrared reflectance spectroscopy instruments. Anim Feed Sci Technol 1999;(78):325-340. 5. Givens DI, De Boever JL, Deaville ER. The principles, practices and some future applications of near infrared spectroscopy for predicting the nutritive value of foods for animals and humans. Nutr Res Rev 1997;(10):83-114. 6. Sorensen LK. Prediction of fermentation parameters in grass and corn silage by near infrared spectroscopy. J Dairy Sci 2004;(87):3826-3835. 7. Park R, Agnew E, Porter M. Recent developments in methods to characterize the chemical and biological parameters of grass silage. In Park R, Stronge M. editors. Silage production and utilization. Proc XIV Int Silage Conf, a satellite workshop of the XX Int Grassland Cong. Belfast, Northern Ireland: Wageningen Academic Publishers; 2005:109-119. 8. Castro P. Use of near infrared reflectance spectroscopy (NIRS) for forage analysis. Lowland and grasslands of Europe: Utilization and development. Corporate Document Repository. FAO- Food And Agriculture Organization Of The United Nations, Rome, Italy. 2002. http://www.fao.org/DOCREP/006/AD236E/ad236e14.htm. Accessed July 1, 2019. 9. Pereira-Crespo S, Fernández-Lorenzo B, Resch C, Valladares-Alonso J, González L, Dagnac T, et al. Predicción de la calidad fermentativa de ensilados de hierba mediante NIRS sobre muestras secas y molidas. Pastos y Forrajes en el siglo XXI. Palma de Mallorca, España, Sociedad Española para el Estudio de los Pastos. 2015:161-167. 10. Schneiter AA, Miller JF. Description of sunflower growth stages. Crop Sci 1981;(21):901-903. 11. Castro P. Efecto de tres temperaturas de secado sobre la composición química de forrajes y heces. En: Consejería de Agricultura, Ganadería y Desarrollo Rural Ed. Actas de XXXVI Reunión Científica de la SEEP. La Rioja, España: Sociedad Española para el Estudio de los Pastos. 1996:365-368. 12. WIN ISI 1.5. ISI WINDOWS. Near-Infrared Software, The Complete Software Solution for Routine Analysis, Robust Calibration and Networking, Port Matilda, PA, USA. ISI (Infrasoft International), LLC, 2000. 13. Shenk JS, Westerhaus MO. Population definition, sample selection, and calibration procedures for near infrared reflectance spectroscopy. Crop Sci 1991;(31):469-474. 14. Barnes RJ, Dhanoa MS, Lister SJ. Standard normal variate transformation and Detrending of near infrared diffuse reflectance spectra. Appl Spectroscopy 1989;(43):772-777.

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15. Shenk J, Westerhaus M. Routine operation, calibration, development and network system management manual. Silver Spring, MD, USA NIRS Systems Inc, 1995. 16. Martens H, Naes T. Multivariate calibration by data compression. In: Williams P, Norris K. editors. Near-infrared technology in the agricultural and food industries. St. Paul, Minnesota, USA. American Association of Cereal Chemists. 1987:57-88. 17. Stern M, Endres M. Laboratory manual: Research techniques in ruminant nutrition. Department of Animal Science. Minnesota, USA. University of Minnesota. 1991. 18. Shenk JS, Westerhaus MO. Analysis of agriculture and food products by Near Infrared Reflectance Spectroscopy. USA: Monograph, NIR Systems Inc. MD, USA. Silver Spring, 1995. 19. Williams PC, Sobering DC. How do we do it: a brief summary of the methods we use in developing near infrared calibrations. In: Davies AMC, Williams P. editors. Near Infrared Spectroscopy: The future waves. Chichester, England, United Kingdom: NIR Publications; 1996:185-188. 20. Shenk JS, Westerhaus MO. Population structuring of near infrared spectra and modified partial least squares regression. Crop Sci 1991;(31):1548-1555. 21. Shenk JS, Westerhaus MO, Calibration the ISI way. In: Davies AMC, Williams P. editors. Near Infrared Spectroscopy: The future waves. Chichester, England, United Kingdom, NIR Publications; 1996:198-202. 22. Fassio A, Gimenez A, Fernandez , Vaz Martins D, Cozzolino D. Prediction of chemical composition in sunflower whole plant and silage (Helianthus annus L.) by Near Infrared Reflectance Spectroscopy. J Near Infrared Spec 2007;15(3):201-207. 23. Park H, Hoon Lee S, Cheol Lim Y, Seo S, Choi K, Hea Kim J, et al. Prediction of the chemical composition of fresh whole crop barley silages by Near Infrared Spectroscopy. J Kor Grassl Forage Sci 2013;33(3):171-176. 24. Park H, Hoon Lee S, Choi K, Cheol Lim Y, Hea Kim J, Won Lee K, et al. Prediction of the chemical composition and fermentation parameters of winter rye silages by Near Infrared Spectroscopy. J Kor Grassl Forage Sci 2014;34(3):209-213. 25. Park RS, Agnew RE, Gordon FJ, Steen RWJ. The use of near infrared reflectance spectroscopy (NIRS) on undried samples of grass silage to predict chemical composition and digestibility parameters. Anim Feed Sci Technol 1998;72(1):155-167.

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26. Shenk JS, Westerhaus MO, Abrams SM 1989. Protocols for NIRS calibration: monitoring analysis results and recalibration. In Near Infared Reflectance Spectroscopy (NIRS): Analysis of forage quality. Marten GC, Shenk J, Barton FE editors. USDA. ARS. Agriculture Handbook Nº 643, Washington, USA. 1989:104-110. 27. Sainz-Ramírez A, Botana A, Pereira-Crespo S, González-González L, Veiga M, Resch C, et al. Efecto de la fecha de corte y del uso de aditivos en la composición química y calidad fermentativa de ensilado de girasol. Rev Mex Cienc Pecu 2020;11(3):620-637.

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https://doi.org/10.22319/rmcp.v12i2.4398 Technical note

Corbicular pollen spectrum (Apis mellifera) of samples from Huejotitan, Jalisco, Mexico

Roberto Quintero Domínguez a Lino de la Cruz Larios a Diego Raymundo González Eguiarte a José Arturo Solís Magallanes b José Francisco Santana Michel c† José Luis Reyes Carrillo d*

a

Universidad de Guadalajara. Centro Universitario de Ciencias Biológicas y Agropecuarias, Departamento de Producción Agrícola, Camino Ramón Padilla Sánchez 2100 Nextipac, 45200 Zapopan, Jalisco, México. b

Universidad de Guadalajara. Centro Universitario de la Costa Sur, Departamento de Ecología y Recursos Naturales, Autlán, Jalisco, México. c

Universidad de Guadalajara. Centro Universitario de la Costa Sur, Departamento de Ecología y Recursos Naturales, Laboratorio de Botánica, Autlán, Jalisco, México. d

Universidad Autónoma Agraria Antonio Narro. Unidad Laguna, Departamento de Biología, Torreón, Coahuila, México.

*Corresponding author: jlreyes54@gmail.com

Abstract: This study examines the different plants visited by the honeybee (Apis mellifera L.) during the honey harvest season (August to November) 2012. The work consisted in identifying the 621


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corbicular pollen pellets collected by the bees in one apiary in the village of Huejotitan, municipality of Jocotepec, state of Jalisco, Mexico. Three hives were selected and sampled monthly by means of Ontario modified pollen traps. The samples were tagged and frozen and later processed by acetolysis technique to remove the exine; permanent glycerine slides were made for the preservation and analysis. Identification and counting of pollen grains was performed using an Olympus BH-2® upright microscope equipped with a 100X ocular micrometer to measure each individual species pollen grain, using immersion oil. Wild plants in bloom were also collected monthly, tagged, pressed and taken to the herbarium for identification; the pollen was extracted, processed and identified for a reference collection that served as an ancillary means of identification and as a seasonal reference to the blooming species. In the corbicular pollen, 23 types of plants were identified: 13 at species level, five at genus level and five at family level belonging to 17 plant families. Myrtaceae resulted the most frequently represented family followed by Asteraceae, Fabaceae and Lamiaceae. Key words: Bee behavior, Bee foraging, Apipalynology, Apibotany.

Received: 08/03/2018 Accepted: 25/05/2020

Despite their role as key pollinators among insects(1), the biological fundamentals for pollen source selection by honey bees (Apis mellifera) in Mexico are still mostly unknown. Botanical studies with apicultural interests are not particularly abundant if is considered that Mexico is a large and mega diverse country, classified in the first places in apicultural production and exports in the world(2). Since bees depend entirely on the vegetation for their survival, it is crucial to understand their feeding preferences as well as the specifics about pollen availability throughout the year. Pollen contains the nutrient protein(3) needed for the brood and young workers survival and proper development. It also contains lipids, vitamins and minerals(4) as incidental components.

Foragers collect pollen in a trend and proportion that vary greatly according to the availability of the resources, distance to the source, nutritional value(5), needs of the hive, i.e. life cycle and physiology of workers, queen and drones and weather conditions(6). This is of particular interest to beekeepers and researchers because the gathering behaviour of the bees does not seem to have fixed patterns. Each season bees will collect pollen in regards to different variables and even in arbitrary ways, i.e. without regard to its nutritional value or from 622


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resources that are not as close or highly available as others(7). This type of information is fundamental to beekeeping and to assess the potential of any determined area, for the production of pollen and for all efforts related to the conservation of biodiversity(8), particularly where the populations of bees are declining.

Analysis of the pollen collected provides information about its botanical origin, the preferred plant species and aids in understanding the foraging behaviour of the bees. The objective of this study was to find what pollen types were collected by honey bees during the honey production season.

With this in mind, a sampling project was designed to collect and analyze corbicular pollen to determine the spectrum of the pollen used by A. mellifera. The pollen grains were primarily identified by means of a special pollen reference collection made from plants in bloom in the locality. These plants were identified by botanical specialists from the University of Guadalajara, and the voucher specimens remain at the Botanical Institute Herbarium of the Centro Universitario de Ciencias Biológicas y Agropecuarias (CUCBA). A site was selected within an area of importance for beekeeping, in one apiary in the village of Huejotitan, municipality of Jocotepec, state of Jalisco. The experimental site was located at 20°21’13.45’’N, 103°29’6.97’’W. The elevation at the site is 1,597 m asl. around the apiary, the land cover is dominated by seasonal cultivated crops, pastures and secondary vegetation interspersed with tropical deciduous forest.

Among 23 bee hives in the apiary, three were chosen for their strength to be sampled once a month for four months with modified Ontario pollen traps(9). From August to November 2012, traps were installed and kept in place for 24 to 48 h and then removed. This period corresponds to the honey preharvest and harvest season. The corbicular pellets were gathered from the trays, cleared of debris, put in plastic containers, tagged and frozen. At the laboratory, 1.5 g of pollen were taken from each of the three samples corresponding to one given month and mixed together to form one single larger sample of the pollen collected from the three hives together. In the end there were four samples from the original 12, one for each month.

Before processing, the pellets were carefully and softly mashed in a mortar. The pollen grains were processed by acetolysis technique to remove the exine; permanent glycerine jelly slides were made for the preservation and analysis; the pollen grains were identified by their size and shape, with an Olympus BH-2® upright microscope equipped with a 100X ocular micrometer to measure each individual species pollen grain, using immersion oil; volume of 623


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the individual pollen grain was calculated with the formula: V=4/3πa2b where "V" is volume, "a" is the major axe of the pollen grain and "b" the minor axe(10). Identification was made by comparison with the pollen reference collection of the Institute of Geology, Universidad Nacional Autónoma de México. In order to obtain the relative percentage, all the pollen grains were counted in each slide. A reference collection with the pollen grains of local plants in bloom was prepared as an ancillary means of identification.

Every month for 4 mo a circuit between 3 and 5 km long in the surroundings of the apiary was walked to sample all blooming plants. The pollen grains where obtained by extracting the anthers from the flowers and then processed for acetolysis according to the same technique(11)mentioned above. The information was used to determine whether a plant was a source of nectar, pollen or both, as well as their migratory status. Information was also taken from the available domestic bee flora publications(11-15). From the pellet samples, 23 different pollen types belonging to 17 plant families were recorded (Table 1) and from these 13 were identified at species level, 5 at genus level and 5 at family level. In August there was no dominant pollen type, however there were three secondary types, Aster sp., Eucalyptus citriodora and Ricinus communis, one important minor, Cyperaceae, and traces of other ones. Thus the four types were significant, with percentages above ten. In September E. citriodora was the dominant type with Poaceae and Psidium guajava as secondary types and traces of others. In this month three types were significant, with percentages above ten. In October no dominant type was obtained but there were again three secondary types, E. citriodora, Hyptis albida and L. leucocephala, all significant, with percentages above ten, and traces of others. In November E. citriodora was considerably dominant over the two secondary types, Asteraceae and Pseudosmodingium sp., but the three were significant, with percentages above ten, and traces of others. E. citriodora was significant in the four samples and Asteraceae and L. leucocephala were found in three. R. communis, Sicyos angulatus, Citrus sp., Pseudosmodingium sp. and Poaceae appeared in two samples each.

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Table 1: Pollen types from pollen pellet samples, represented by taxa in percentages in the Huejotitan, Jalisco region during August-November 2012 Taxa Acacia farnesiana Aster sp. Asteraceae Betula sp. Citrus sp. Cyperaceae Dodonaea viscosa Eucalyptus citriodora Fabaceae Fragaria vesca Fraxinus uhdei Heliocarpus terebinthinaceus Hyptis albida Leucaena leucocephala Poaceae Pseudosmodingium sp. Psidium guajava Psittacanthus calyculatus Ricinus communis Rubus idaeus Salix sp. Sapindaceae Sicyos angulatus Others

Family Fabaceae Asteraceae Asteraceae Betulaceae Rutaceae Cyperaceae Sapindaceae Myrtaceae Fabaceae Rosaceae Oleaceae Malvaceae Lamiaceae Fabaceae Poaceae Anacardiaceae Myrtaceae Loranthaceae Euphorbiaceae Rosaceae Salicaceae Sapindaceae Cucurbitaceae

Aug Sep Oct (%) (%) (%) 2.4 34.1 5.3 5.8 5.5 1.7 1.4 14.0 1.0 1.2 20.5 47.2 34.6 2.1 4.5

Nov Migratory (%) status native unknown 14.5 unknown unknown exotic unknown native 65.6 exotic unknown exotic 3.0 native 2.1 native 18.2 native 2.9 16.1 2.0 native 17.5 1.0 unknown 8.2 11.9 unknown 17.0 native 2.1 native 17.1 1.9 exotic 1.6 exotic 3.9 native unknown 5.8 1.3 native 1.7 1.6 1.7 unknown

Each month the represented families changed, however, there was a consistency in their overall presence and percentages of representation (Table 2).

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Table 2: Pollen types from pollen pellet samples, represented by families and percentages in the Huejotitan, Jalisco region during August-November 2012 August 2012 September 2012 October 2012 November 2012 Asteraceae Myrtaceae Euphorbiaceae Cyperaceae Rosaceae Salicaceae Fabaceae Loranthaceae Rutaceae

34.1 20.5 17.2 14.0 4.5 3.9 2.1 2.1 1.6

Myrtaceae Poaceae Betulaceae Asteraceae Fabaceae Euphorbiaceae Sapindaceae Others

64.2 17.5 5.5 5.3 2.9 1.9 1.0 1.7

Total

100

Total

100

Myrtaceae Fabaceae Lamiaceae Anacardiaceae Asteraceae Cucurbitaceae Malvaceae Rosaceae Rutaceae Sapindaceae Poaceae Others Total

34.6 18.5 18.2 8.2 5.8 5.8 2.1 1.6 1.4 1.2 1.0 1.6 100

Myrtaceae Asteraceae Anacardiaceae Oleaceae Fabaceae Cucurbitaceae Others

65.6 14.5 11.9 3.0 2.0 1.3 1.7

Total

100

Asteraceae was present in the four samples, Myrtaceae in three, Anacardiaceae, Fabaceae and Rosaceae in two, and Betulaceae, Cucurbitaceae, Cyperaceae, Euphorbiaceae, Lamiaceae and Oleaceae in one. 78 different species of plants in bloom, belonging to 30 families and 71 genres, were documented during the 11 mo (Table 3) in order to have as many as possible species of pollen grains documented for reference. The five best represented families were Asteraceae with 33.33 %, Fabaceae with 8.97 %, Solanaceae with 6.41 %, Lamiaceae with 5.12 % and Verbenaceae with 3.84 %. These five families represent 29.41 % of the total number of families and 57.67 % of the total number of species. 17 of all the species have been reported to be nectar producers, seven pollen producers, 17 nectar and pollen producers and 37 are not documented in terms of their importance for honey bees; 50 % were forbs, 30.77 % shrubs and 19.23 % trees. Considering all the species, 88.46 % were native and 11.54 % were exotic. Twenty-six (26) species were documented to be visited by honey bees.

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Table 3: Species of plants sampled for the reference collection Species

Family

Source

Form

Acacia farnesiana Adenophyllum cancellatum Argemone mexicana Asclepias glaucescens Bidens odorata Bidens pilosa Bocconia arborea Brassica rapa Buddleja sessiliflora Casimiroa edulis Castilleja tenuiflora Chromolaena collina Cissus verticillata Clematis rhodocarpa Conyza canadensis Cucurbita foetidissima Dicliptera peduncularis Diphysa puberulenta Dyssodia tagetiflora Ehretia latifolia Erythrina coralloides Eucalyptus citriodora Eupatorium odoratum Flaveria trinervia Fleischmannia sonorae Fraxinusuhdei Gronovia scandens Guazuma ulmifolia Heimia salicifolia Helianthus annuus L. Hyptis albida Ipomoea hederifolia Ipomoea murucoides Ipomoea purpurea Iresine diffusa Jacaranda mimosifolia Lantana camara

Fabaceae Asteraceae Papaveraceae Apocynaceae Asteraceae Asteraceae Papaveraceae Brassicaceae Scrophulariaceae Rutaceae Orobanchaceae Asteraceae Vitaceae Ranunculaceae Asteraceae Cucurbitaceae Acanthaceae Fabaceae Asteraceae Boraginaceae Fabaceae Myrtaceae Asteraceae Asteraceae Asteraceae Oleaceae Loasaceae Malvaceae Lythraceae Asteraceae Lamiaceae Convolvulaceae Convolvulaceae Convolvulaceae Amarantaceae Bignoniaceae Verbenaceae

N-P x P N N-P N-P x N N-P N x x N x x P x N-P x x x N-P N-P x x N-P x N-P x N-P N x N x x P P

shrub forb forb shrub forb forb tree forb shrub tree forb shrub forb forb forb forb forb shrub forb tree tree tree forb forb forb tree forb tree shrub forb shrub forb tree forb forb tree shrub

627

Migratory status native native native native native native native exotic native native native native native native native native native native native native native exotic native native native native native native native native native native native native native exotic native


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Leonotis nepetifolia Licopersicum esculentum var. cerasiforme Lippia umbellata Mandevilla foliosa Melampodium perfoliatum Melia azedarach Mimosa galeottii Montanoa karwinskii Nicotiana glauca Olivaea tricuspis Parthenium hysterophorus Perityle microglossa Phytolacca icosandra Pistacia mexicana Pithecellobium dulce Prosopis laevigata Pseudognaphalium chartaceum Psidium guajava Psilactis asteroides Psittacanthus calyculatus Ricinus communis Salvia misella Salvia tiliifolia Schinus molle Senecio salignus Senna occidentalis Serjania racemosa Solanum ferrugineum Solanum grayi Solanum grayi var. grandiflorum Tagetes erecta Thunbergia alata Tithonia tubiformis Tournefortia mutabilis Trixis hyposericea Verbena bipinnatifida Verbesina barrancae Verbesina crocata Vernonanthura cordata

Lamiaceae

N-P

shrub exotic

Solanaceae Verbenaceae Apocynaceae Asteraceae Meliaceae Fabaceae Asteraceae Solanaceae Asteraceae Asteraceae Asteraceae Phytolaccaceae Anacardiaceae Fabaceae Fabaceae Asteraceae Myrtaceae Asteraceae Loranthaceae Euphorbiaceae Lamiaceae Lamiaceae Anacardiaceae Asteraceae Fabaceae Sapindaceae Solanaceae Solanaceae Solanaceae Asteraceae Acanthaceae Asteraceae Boraginaceae Asteraceae Verbenaceae Asteraceae Asteraceae Asteraceae

N N x x N-P N N-P x x P x N x N-P N-P x N x N N x x N-P P x N-P x x x N x N x x x x x N

forb shrub shrub forb tree shrub shrub shrub forb forb forb forb tree tree tree forb tree forb forb shrub forb forb tree shrub forb forb shrub forb forb forb forb forb shrub shrub forb shrub shrub shrub

628

native native native native exotic native native exotic native native native native native native native native native native native exotic native native exotic native native native native native native native exotic native native native native native native native


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Vernonia bealliae Viguiera quinqueradiata

Asteraceae Asteraceae

P N

shrub native shrub native

The columns show species, family, food source: P= pollen, N= Nectar, x= not documented, form of life and migratory status in Mexico.

The months with more species in bloom were September and November with 16 species each, then October with 13 and finally August with 12. Bees represent the primary pollinators among insects and honey bees are becoming the only ones in areas where intensive crop monoculture is gradually wiping out the wild native insects. One of the reasons is that A. mellifera belongs to one of the few bee genera known to have polylectic habits(16). Yield increases are reported to be up to 96% in cultivated crops pollinated by them(17). In terms of the sources used by the honey bees as revealed in this study, Myrtaceae had the second highest percentage in August and by far the first in September, October and November. This family was prominently represented by E. citriodora, an introduced species. Originally evolved in the Austro-Malaysian region(18), has been introduced in many countries for its value as timber, fuel wood, wood fiber and ornament(19). The floral phenology of Eucalyptus tends to be synchronous among different individuals within one stand but at the same time shows great variation in flowering time and even intermittent flowering periods over the greater part of the year(20); honeybee has been documented to be one of the most prevalent visitors its flowers(21). In August the Asteraceae family was dominant over Myrtaceae. Asteraceae is the most abundant family in Mexico(22-25) and represents an estimated 10 % of all know plants in the world(26) and its center of diversification is located in Mexico, where it is the largest and most representative group, containing from 7 to 32 % of the country's flora and 12.5 % of Jalisco´s(27). In September, the second most abundant family was Poaceae, but neither species nor genre were determined. This is also an extensive group, with more than 500 species worldwide, which includes the cereals humans consume and the grasses for cattle feed(26). In October, the second most important families, in equal percentages were Fabaceae, represented by L. leucocephala and A. farnesiana, and Lamiaceae, by H. albida. Although the percentages in this study refer to the number of pollen grains and not to their volume, the sizes are still relevant because the ratios change when analyzed in terms of a different variable. E. citriodora pollen grains are small, 25 µm average, and have the shape of a flattened triangular prism. The volume of one these grains averages approximately 3,125 µm3. Contrastingly, the pollen grains of A. farnesiana are 60 µm average, and ellipsoid in shape. Their volume is approximately 78,539.8 µm3. E. citriodora represented 34 % of the sample and A. farnesiana (Fabaceae) 2.4 % in terms of number of grains. Nevertheless, if their total volumes compared, the proportions change radically: 106,250 µm3 for E. citriodora and 196,349.5µm3 for A. farnesiana, almost twice the volume of E. citriodora.

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In November Asteraceae was the second most important family; some pollen species, regardless of their frequency, were present in at least two of the pollen load samples indicating their presence for longer than a single month thus representing a long-term food resource during the year. Such is the case with E. citriodora, present in the four samples, and Asteraceae and L. leucocephala (Fabaceae), present in three. Of the 23 pollen types found in the samples, seven have been reported as pollen sources for honey bees in other states A. farnesiana, Fraxinus uhdei, Heliocarpus terebinthinaceus, L. leucocephala, P. guajava, R. communis, and S. angulatus(11-15,27,28).

Of the total number of plant species in bloom observed in the area throughout the year only 34.21% have been reported to be used by the honeybees(22-26,29,30). This might be explained by the selectiveness of honey bees depending on the relative abundance and quality of nectar, pollen and distance to the sources.

Acknowledgments

This project was funded by the CONACYT México, Universidad de Guadalajara and the Universidad Autónoma Agraria Antonio Narro, Unidad Laguna. We wish to thank Rafael Ordaz-Briseño for his priceless assessment as an expert in beekeeping topics and Arturo Castro-Castro for the supervision in plant specimen preparation and identification. A special mention goes to our friend, fellow researcher and coauthor Jose Francisco Santana Michel who passed away before this publication. Literature cited: 1.

Potts SG, Biesmeijer JC, Kremen C, Neumann P, Schweiger O, Kunin WE. Global pollinator declines: trends, impacts and drivers. Trends Ecol Evol 2010;25:(6)345-353.

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Kostić AŽ, Barać MB, Stanojević SP, Milojković-Opsenica DM, Tešić ŽL, Šikoparija B,et al. Physicochemical composition and techno-functional properties of bee pollen collected in Serbia. LWT-Food Sci Technol 2015;62(1):301-309.

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Roulston TH, Cane JH. Pollen nutritional content and digestibility for animals. Pollen and pollination. Pl Syst Evol 2000;222:187-209.

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Levin MD, Haydak MH. Seasonal variation in weight and ovarian development in the worker honeybee. J Econ Entomol 1951;44(1):54-57.

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Wells H, Wells PH. Honey bee foraging ecology: optimal diet, minimal uncertainty or individual constancy?. J Anim Ecol 1983;52(3):829-836.

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Waller GD. Modification of the OAC pollen trap. Am Bee J 1980;(120):119-121.

10. Kearns CA, Inouye DW. Techniques for pollination biologists. Niwot, Colorado, USA: University Press of Colorado; 1993. 11. SAGADER. Secretaría de Agricultura, Ganadería y Desarrollo Rural. Flora nectarífera y polinífera del estado de Michoacán, México. 1999. 12. Franco OVH, Siqueiros DME, Hernández AEG. Flora apícola del estado de Aguascalientes. Universidad Autónoma de Aguascalientes, México. 2012. 13. SAGARPA. Secretaría de Agricultura, Ganadería, Desarrollo Rural, Pesca y Alimentación. Flora nectarífera y polinífera en el estado de Tamaulipas, México. 2003. 14. SAGADER. Secretaría de Agricultura, Ganadería y Desarrollo Rural. Flora nectarífera y polinífera en el estado de Chiapas, México. 2000. 15. Souza-Novelo N, Barrera-Vásquez A, Suárez-Molina VM. Plantas melif́ eras y polinif́ eras que viven en Yucatán. Fondo Editorial de Yucatán. 2001. 16. Cortopassi LM, Ramalho M. Pollen harvest by Africanized Apis mellifera and Trigona spinipes in São Paulo botanical and ecological views. Apidologie 1988;19(1):1-24. 17. Klein AM, Vaissière BE, Cane JH, Steffan-Dewenter I, Cunningham SA, Kremen C, Tscharntke T. Importance of pollinators in changing landscapes for world crops. Proc R Soc Lond [Biol] 2007;274(1608):303-313. 18. Hanks LM, Paine TD, Millar JG, Hom JL. Variation among Eucalyptus species in resistance to eucalyptus longhorned borer in Southern California. Entomol Exp Appl 1995;74(2):185-194. 19. Zacharin RF. Emigrant eucalypts: gum trees as exotics. Victoria, Australia: Melbourne University Press; 1978.

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20. Griffin A. Floral phenology of a stand of mountain ash (Eucalyptus regnans F. Muell.) in Gippsland, Victoria. Aust J Bot 1980;28(4):393-404. 21. Horskins K, Turner V. Resource use and foraging patterns of honeybees, Apis mellifera, and native insects on flowers of Eucalyptus costata. Austral Ecol 1999;24(3):221-227. 22. Castellanos PBP, Ramírez AE, Zaldivar CJM, Análisis del contenido polínico de mieles producidas por Apis mellifera L. (Hymenoptera: Apidae) en el estado de Tabasco, México. Acta Zool Mex 2012;28(1):13-36. 23. Piedras GB, Quiroz GDL. Estudio melisopalinológico de dos mieles de la porción sur del Valle de México. Polibotánica 2007;23:57-75. 24. Ramírez AE, Navarro CLA, Díaz CE. Botanical characterisation of Mexican honeys from a subtropical region (Oaxaca) based on pollen analysis. Grana 2011;50(1):40-54. 25. Ramírez AE, Martínez BA, Ramírez MN, Martínez HE. Análisis palinológico de mieles y cargas de polen de Apis mellifera (Apidae) de la región Centro y Norte del estado de Guerrero, México. Bot Sci 2016;94(1):141-156. 26. Ordetx GS, Zozaya RJA, Franco MW. Estudio de la flora apícola nacional. Universidad de Chapingo, México, DF 1972. 27. Villaseñor JL, Ibarra G, Ocaña D. Strategies for the conservation of Asteraceae in Mexico. Conserv Biol 1998;12(5):1066-1075. 29. Acosta CS, Quiroz GDL, Arreguín SML, Fernández NR. Análisis polínico de tres muestras de miel de Zacatecas, México. Polibotánica 2011;(32):179-191. 30. Louveaux J. Étude expérimentale de la récolte du pollen. In: Chauvin R, editor. Traité de biologie de l'abeille, Masson et Cie, Paris, France 1968;(3):174-203.

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https://doi.org/10.22319/rmcp.v12i2.5480 Technical note

Efficacy of thymol in control of the fungus Nosema ceranae in Africanized Apis mellifera

Azucena Vargas-Valero a Roberto C. Barrientos-Medina b Luis A. Medina Medina c*

a

Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias. Centro de Investigación Regional del Sureste, Campo Experimental Edzná, Campeche, México. b

Universidad Autónoma de Yucatán. Facultad de Medicina Veterinaria y Zootecnia, Departamento de Ecología, Yucatán, México. c

Universidad Autónoma de Yucatán. Facultad de Medicina Veterinaria y Zootecnia, Departamento de Apicultura, Yucatán, México.

* Corresponding author: mmedina@correo.uady.mx

Abstract: Nosema ceranae is an obligatory parasite of the honeybee midgut. It destroys the epithelial cells, negatively affecting food digestion and assimilation, and impacting bee development and colony survival. Antifungals such as fumagillin effectively control N. ceranae but can be toxic to humans who consume honey from treated hives, and are prohibited in many countries, including Mexico. Essential oils from plants are promising alternative antifungals. An evaluation was done of the efficacy of the essential oil thymol in controlling N. ceranae in Africanized Apis mellifera colonies over a four-week period. A total of 56 colonies were distributed in three experimental groups: G1) 18 colonies treated with fumagillin (25.2 mg fumagillin/week); G2) 19 colonies treated with thymol (66 mg thymol crystals/week); and G3) 19 untreated colonies (control). Infection levels (N. ceranae spores/bee) were estimated in 60 adult bees from each colony. Fumagillin (G1) reduced infection levels from 123,529 to 1,805 spores/bee (95.2 % efficacy). Thymol (G2) reduced infection levels from 133,438 to 633


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28,099 spores/bee (31.1 % efficacy). Infection levels also declined in the control group (G3), from 119,306 to 36,447 spores/bee. The clearly higher efficacy with fumagillin compared to thymol highlights the need for further trials to test different thymol concentrations, and administration frequencies and times. Under the present study conditions thymol was not effective against N. ceranae, but the pressing need for non-toxic antifungals for use in Africanized A. mellifera colonies in the tropics makes research on thymol and other essential oils imperative. Key words: Nosema ceranae, Nosemosis, Fumagillin, Thymol, Efficacy, Apis mellifera.

Received: 20/08/2019 Accepted: 02/09/2020

Nosemosis is a parasitic fungal infection affecting the digestive tract of honeybees Apis mellifera. It is caused by two species of the Nosematidae family: Nosema apis and Nosema ceranae. The former is associated with infection in A. mellifera, while the latter was originally associated with the Asian bee Apis cerana. First diagnosed infecting A. mellifera in central and northern Spain in 2006(1), N. ceranae infection causes reductions in honey production and high colony mortality in winter(2,3).

Both these microsporidia (N. apis and N. ceranae) reproduce rapidly inside the epithelial cells of the midgut (ventricle) of adult bees (queen, workers and drones). Infection causes destruction of the epithelial cells responsible for digestion and food assimilation(3), resulting in nutritional stress(4). At an individual level, other damage includes reduced life span(3,5,6) and compromised orientation and foraging capacities in infected workers(7,8). At the colony level, high Nosema prevalence and infection levels can cause serious damage, such as reductions in breeding areas and the adult population, consequent declines in honey production(9,10) and eventual collapse and loss(11,12).

Since its initial identification in A. mellifera in 2006, N. ceranae has become one of the most widely distributed bee pathogens worldwide(13,14). It has been associated with high colony mortality in Europe(11), North America(15) and South America(16), with a much higher virulence than N. apis(5,17,18).

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Apis mellifera colonies in the state of Yucatan, Mexico, are infected by N. apis or N. ceranae but no massive losses or high colony mortality have been reported as a result. Since 2008(19), high nosemosis prevalence (74 to 100 %) has been reported in commercial apiaries compared to previous years (7.2 %)(20). This high prevalence has been attributed to the presence of N. ceranae in Africanized A. mellifera in Yucatan(21). Moreover, under Yucatan’s tropical conditions N. ceranae infection has been confirmed to negatively affect foraging initiation and duration, as well as worker longevity(22).

The only substance considered effective against this microsporidium is fumagillin (dicyclohexylammonium salt). Since its initial evaluation in the early 1950s(23), this antimicrobial, derived from the fungus Aspergillus fumigatus, has been used to control N. apis in A. mellifera. Its action mechanism is inhibition of microsporidium DNA replication, which suppresses its reproduction, resulting in lower spore counts in the bee ventricle(24,25).

Fumagillin is approved in the United States and is widely used to control N. apis and N. ceranae infections. However, in many European countries(26), as well as in Mexico, it is prohibited for nosemosis control due to its toxicity in humans; any residue remaining in honey from colonies under treatment represents a direct risk to the consumer(27). Alternative nosemosis control products have been proposed. These include essential oils from plants, such as thymol from Thymus vulgaris and vetiver from Chrysopogon zizanioides, as well as resveratrol, a natural polyphenol presents in numerous plants and fruits such as grapes. These essential oils, particularly thymol, have been shown to exercise some control of nosemosis(28,29). When treated with thymol (0.44 mM) administered via sugar syrup, Nosemainfected colonies are reported to exhibit reduced spore counts per bee, expansion of brood areas, increased adult bee populations and greater honey production compared to untreated infected colonies(28). These natural-source alternative essential oils products represent no toxicity risk for bees, a low probability of leaving residues in honey(30), and are less expensive than commercial pharmaceuticals.

As part of the search for alternative products for nosemosis control, the present study objective was to compare the efficacy of the essential oil thymol in controlling nosemosis caused by N. ceranae infection in Africanized A. mellifera under tropical conditions in Yucatan, Mexico.

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The experiment was carried out in two apiaries at the Faculty of Veterinary Medicine and Zootechnics of the Autonomous University of Yucatan (Universidad Autónoma de Yucatán - UADY), Xmatkuil, Yucatan (20º51’51” N, 89º36’45” W; 20º51’55” N, 89º36’46” W). Regional climate is warm sub-humid with summer rains (Awo). Average annual rainfall is 985 mm, average annual temperature is 26.8 ºC and average annual relative humidity is 78 %(31).

The colonies in both apiaries were double colonies (brood chamber and super) housed in Langstroth-type hives. All hives had naturally-fertilized Africanized queens, an adult population covering 7 to 9 combs in the brood chamber, 6 to 8 combs containing brood at different stages (eggs, larvae and pupae), as well as combs containing honey and pollen. The colonies were distributed in a similar way among the experimental groups. Infection with N. ceranae was identified by endpoint PCR(32) of forage bees collected at the entrance to each experimental colony.

Before starting the evaluations, a preliminary diagnosis was made in both apiaries to quantify N. ceranae infection level (spores/bee) in all colonies. This ensured that all three experimental groups had a comparable initial infection level. Adult bees (~100 to 150 workers) were collected from the entrance of each experimental colony. Sixty individuals from each sample were analyzed to identify the presence of N. ceranae spores and quantify infection severity based on spore count per bee in the digestive tract. The abdomen was removed from each of the 60 bees, placed in a mortar and 60 ml distilled water added(9,33). The abdomens were macerated until creating a homogeneous mixture and this was filtered through gauze to remove impurities. One drop of the resulting solution was placed in each reticule of a Neubauer chamber and viewed at 400x magnification. The spore counts were used to calculate average infection level (i.e. spores/bee).

Efficacy of the fumagillin (Fumagilin-B®) and thymol crystals (Sigma-Aldrich; ≥99.5% purity) in control of N. ceranae was evaluated over a period of four weeks with treatments applied once a week. The colonies in both apiaries were divided into three experimental groups:

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Group 1 (G1): 18 colonies treated with fumagillin (Fumagilin-B®) administered at 1.2 g product (25.2 mg fumagillin)/colony/week in one liter sugar syrup (2:1, sugar:water); Group 2 (G2): 19 colonies treated with 66 mg thymol crystals (99.5% purity)/colony/week in one liter sugar syrup (2:1, sugar:water); Group 3 (G3): a control consisting of 19 colonies administered only one-liter sugar syrup (2:1, sugar: water), and no antifungals, per colony/week.

At the end of each week, adult bees were collected from the entrance of each colony and processed following the methodology described above to quantify infection level in each group.

Spore counts per bee were divided by one thousand to facilitate statistical analysis. The BoxCox transformation(34) was applied to normalize variable distribution. Finally, a repeated measures analysis of variance was used to compare the means per treatment (i.e., experimental group) and week, and the interaction between both factors (treatment x week). Significance level was P= 0.05 and calculations were run with the PAST ver. 3.20 software program(35).

In Group 1 (colonies administered fumagillin) infection levels (𝑋±SE) dropped from 123,529 ± 41,200 spores/bee on d-0 to 1,805 ± 527 spores per bee on d-28, representing a 95.2 % overall efficacy against N. ceranae (Table 1). In Group 2 (colonies administered thymol crystals) infection levels declined from 133,438 ± 59,291 to 28,099 ± 17,574 spores/bee, representing 31.1 % efficacy. The decreases in infection levels in Group 3 (control) may be the result of seasonal fluctuations, as reported elsewhere(36).

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Table 1: Nosema ceranae spore counts per bee (𝑋 ± SE) in response to administration of fumagillin or thymol Fumagillin Thymol Control H G1 G2 G3 Day 0

123,529±41,220 a 133,438±59,291 a

119,306±53,100 a

0.5587

Day 7 (1st application) Day 14 (2nd application) Day 21 (3rd application) Day 28 (4th application)

104,688±42,293 a

67,812±14,426 a

80,394±22,381 a

1.8960

57,666±14,827 a

84,500±23,054 a

96,666±25,476 a

2.1100

30,468±11,190 a

27,058±9,779 a

42,631±9,055 a

4.9040

1,805±527 a

28,099±17,574 b

36,447±17,554 c

24.0900

95.2

31.1

-

Overall efficacy, % abc

𝑋 ± SE= Average ± standard error; H = Kruskal-Wallis test result. Different letter superscripts in the same row indicate difference (P<0.05).

Initial N. ceranae infection levels did not differ between the three experimental groups based on a Kruskal-Wallis test (H= 0.5587, P= 0.7563) (Table 1); indeed, levels did not differ between the groups during the first three weeks of the experiment. It was not until the fourth week did differences become apparent, with G1 (fumagillin) exhibiting the highest efficacy. Clearly, administration of 100.8 mg fumagillin (4.8 g Fumagilin-B®), following manufacturer recommendations, effectively controlled N. ceranae reproduction in this group.

Application of fumagillin in G1 significantly decreased N. ceranae infection levels after four weeks at an efficacy over three times those of G2 (thymol crystals) and G3 (control). This coincides with previous reports indicating that fumagillin remains appropriate for control of N. ceranae infection(37-40). Though efficient at temporarily reducing N. ceranae infection levels, it does not prevent reinfections within six months of the last application(38).

The 31.1 % efficacy of thymol observed in the present study was lower than the 40 % reported in a study of N. ceranae-infected bees fed sugar syrup containing thymol under laboratory conditions(41). Of note is that thymol is reported to have greater efficacy in controlling nosemosis after three consecutive years of application(28); this is much longer than the fourweek period used in the present study. Continued application of thymol for an additional two years would be vital to verifying the effectiveness of the dose used here.

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Fumagillin was effective in reducing N. ceranae infection levels in Africanized A. mellifera under tropical conditions. However, its use in bees is prohibited in Mexico, and its application at the doses used in the present study is only recommended when infection levels exceed two million spores/bee(28). Considering that the highest initial infection level recorded in the present results was only 192,729 spores/bee, substantially lower than two million, application of thymol may yet exhibit a controlling effect against N. ceranae under the experimental conditions, just at higher infection levels. Further research will be needed to determine the potential of thymol as an alternative fungus control in Africanized A. mellifera under tropical conditions. Evaluations are needed in which higher doses and/or different application frequencies are tested. Because of its lower toxicity risk in both bees and humans, and the low residues it leaves in honey, the potential of thymol as an alternative antifungal in honeybees is well worth pursuing.

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https://doi.org/10.22319/rmcp.v12i2.5519 Technical note

Characterization of the lactation curve and milk quality in Santa Cruz sheep (Ovis aries)

Ingrid Merchant a Agustín Orihuela a* Reyes Vázquez a Virginio Aguirre a

a

Universidad Autónoma del Estado de Morelos. Facultad de Ciencias Agropecuarias. Avenida Universidad 1001 Colonia Chamilpa, Cuernavaca Morelos 62210, México.

* Corresponding author: aorihuela@uaem.mx

Abstract: Milk production and quality during lactation in hair sheep is vital to lamb survival and maintenance. Despite their importance, little data is currently available on these characteristics. An experiment was done to characterize the lactation curve and milk quality in ewes of the Santa Cruz hair sheep breed. Animals were 18 multiparous ewes that had lambed within four days. Milk production was recorded every 72 h from 6 to 60 d postpartum (dpp), and milk quality was quantified once a week from a sample of the day’s total production. Milk production was 1.95 L at 6 dpp, 2.31 L at 12 dpp and 1.01 at 57 dpp. Total solids were 18% at week two and increased to 20.5 % at week eight. Milkfat was 8% at week two and increased to 9.8 % at week eight. The protein (4.86 to 5.18 %) and lactose (4.68 to 4.74 %) percentages remained relatively uniform throughout lactation. Milk production in Santa Cruz ewes is highest in the second week of lactation and then decreases steadily and gradually. Milk total solids and fat percentages increased over time, while protein and lactose percentages remained constant. Key words: Protein, Lactose, Fat, Total solids, Milk production, Sheep.

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Received: 26/09/2019 Accepted: 23/07/2020

Sheep farming in the tropics is mainly focused on meat production. Hair breeds are widely used due to their adaptability to high temperatures, resistance to parasites and high prolificacy(1). Extensive systems are the most common production system in the tropics. Lamb production is the highest value product of these systems and represents the main income source for producers(2).

Milk production in hair breeds is fundamental to lamb survival, growth and weaning weight(3,4), with any surplus used in human foods. Despite its importance, information on milk production and quality in hair sheep during lactation is limited to a few studies in breeds such as Santa Cruz, Blackbelly, and Katahdin(5-7), as well as some West African breeds(8). Sheep milk nutritional composition has only been characterized in Blackbelly x Katahdin sheep(9,10). This lack of research is puzzling since sheep milk is popular among human consumers in tropical North and Central America(11,12).

Daily milk intake is the most important factor influencing lamb growth rates. Offspring survival, growth potential and weaning weight therefore depend on milk production during the mother’s lactation(3,4). Genotypes vary widely between tropical sheep breeds. This means that estimation of milk production during lactation, as well as variation in milk composition, are essential data for establishing sheep and lamb management strategies for specific breeds. The present study objective was to characterize milk production and quality in Santa Cruz ewes, from parturition to weaning.

The study was carried out at the Faculty of Agricultural Sciences, Autonomous University of the State of Morelos (Universidad Autónoma del Estado de Morelos). The experimental field is located at 18°56' N and 99°13' W, at an altitude of 2,160 m asl. Average annual temperature in the region is 20 °C, and average annual rainfall is 1,243 mm.

The experimental animals were eighteen multiparous Santa Cruz ewes with a 2.0 years’ average age and 51.22 ± 2.36 kg weight. All had lambed within four 4 d of the beginning of the experiment. Of the ewes included in the study, 12 gave birth to twins, 2 had triple births and 4 single births. During gestation, the ewes were kept in a single group, grazing from 0800

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to 1400 h in a pasture with African star grass (Cynodon nlemfluensis). During the remaining hours they were penned and provided a supplement of 300 g commercial concentrate. This concentrate contributed 16 % crude protein (CP) and 2.79 Mcal/kg metabolizable energy (ME), while the forage (alfalfa + sorghum) provided 7.6 % CP and 1.78 Mcal/kg ME. The diet consisted of 50 % concentrate and 50 % forage, meaning it covered the nutritional requirements of a 60 kg sheep, with two young, producing between 0.79 and 1.48 kg milk per day(13).

During lactation, the ewes were given free access to a forage mixture (30 % alfalfa and 70 % sorghum straw), 1 kg of the same commercial concentrate feed, and water. For the first 5 days postpartum (dpp) each ewe was housed with her offspring in individual 2 x 2 m roofed pens with a cement floor, individual feeder and drinker. From 6 dpp to weaning (60 dpp) all ewes and their lambs were kept in a single group inside a roofed pen (4 m2/ewe), with concrete floor, a trough and a shared drinker. Beginning at 14 dpp, the pen was equipped with a creep feeder to provide the lambs free access to an 18 % CP commercial concentrate.

Starting at 6 dpp, ewe milk production was measured every three days using the “oxytocin method”. This consists of separating the lambs from the ewes, intravenously administering 5 IU synthetic oxytocin (Oxitopisa; Pisa; Hidalgo, México), and completely milking the udder manually. Four hours after the first hormone application, a second dose is applied, the udder milked again, and milk volume recorded. This value is multiplied by six to estimate daily production(14).

Milk quality was measured once a week using a 50 mL milk sample collected from the daily milk production. Milk protein, fat, lactose, and total solids contents were quantified using an infrared spectrophotometry method(15) applied by an outside laboratory (Alimenlab; Jalisco, Mexico).

Statistical analysis of milk production and quality was done by applying a polynomial regression to produce the equation, the R2 value and its probability. All analyses were run using the PROC REG procedure(16).

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Milk production at 6 dpp was 1.95 L, increased to a maximum of 2.31 L at 12 dpp, and decreased to 1.01 L at 57 dpp. The lactation curve was divided into five periods of 9 d each. Production during the first two periods (equivalent to 18 dpp) did not differ (P>0.05). However, when compared to the first two periods, production began to gradually decrease (P<0.05) thereafter; 15 % in the 3rd period (27 dpp), 26 % in the 4th (36 dpp) and 39 % in the 5th (45 dpp). Average ewe weight did not differ during lactation (P>0.05): 52.24 ± 1.19 kg at parturition and 52.00 ± 1.63 kg at weaning. The corresponding regression analysis (Figure 1) identified an inversely proportional relationship over time, adjusted to a polynomial trend line: r2= 0.88; y= -0.0003x2-0.0513x+2.1079 (P= 0.0001).

Figure 1: Lactation curve for Santa Cruz ewes during 60 days postpartum (mean ± SE) (P≤0.001). Polynomic regression

Total solids percentage began at 18 % in week two of lactation and increased to 20.5 % by week eight (Figure 2). The corresponding regression analysis showed a proportional relationship over time: r2=0.92; y=- 0.0993x2+1.1487x+17.276 (P=0.01).

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Figure 2: Composition of milk from Santa Cruz breed ewes during first 60 days postpartum (mean ± SE) (P≤0.001)

Milkfat increased from 8 % in week two of lactation to 9.8 % at the end of lactation (week eight). The regression analysis confirmed this trend: r2 = 0.61; y= -0.3929x2 + 2.8471x + 5.32 (P =0.23). The protein percentage increased from 4.86 % in week two to 5.18 % at the end of lactation while the lactose percentage increased from 4.68 to 4.75 %. The regression analysis identified minimal fluctuation throughout lactation for both variables: protein, r2 = 0.84, y= 0.0029x2+0.0029x+4.672 (P=0.90); lactose, r2 =0.60; y= 0.1779x2–1.0201x+5.83 (P= 0.05).

Milk production in the evaluated ewes was highest at 12 dpp, without a clear peak, and then decreased gradually and constantly. Maximum milk secretion in different sheep breeds is generally reported between the second and fourth weeks of lactation(17). The maximum production at 12 d observed in the present study coincides with previous reports for Katahdin sheep(7), Ile de France sheep(18) and other breeds(19). However, the quantity of milk produced during this same period was higher in Santa Cruz (2.33 L/d) than in the aforementioned meat breeds (Katahdin =1.38, Ile de France = 0.50 and Others = 0.43 L/d). This highlights the relatively higher milk production in hair breeds(20) when compared to meat breeds of European origin. The lack of a clear peak in milk production in Santa Cruz ewes has been reported elsewhere(7). This may be due to high dietary energy content(21-23); in the present study and the previous one(7), the same feed concentrate was offered, although the forage was different (alfalfa + sorghum straw vs. corn silage), and feed was freely available.

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In milk composition, the total solids and fat percentages were higher at the end of lactation. This is generally to be expected since as milk production decreases, total solids and fat become more concentrated. This is reported in other breeds(24), including specialized milk production breeds(25-26). Higher total solids and fat contents are associated with lower quality milk(27).

Of note in the present results is that the protein and lactose percentages remained constant throughout lactation. Given the total decrease in milk production as lactation progresses, this suggests an increase in these substances over time. This could be an important advantage in the nutritional characteristics of milk from Santa Cruz ewes, but further research is needed to confirm this finding.

Higher protein and lactose concentration in milk may be a response to the fact that tropical sheep live under humid conditions, reducing the need for lambs to receive water via mother’s milk. An inverse situation has been reported in other species inhabiting desert climates, in which milk water content increases(27). Tropical breeds are also lighter in weight than European breeds, suggesting that their lower maintenance requirements could allow for greater nutrient allocation and consequently better milk quality(19).

In conclusion, milk production in Santa Cruz sheep reaches a maximum around the second week of lactation and then decreases constantly and gradually. As a result, the percentages of total solids and fat increase over time, while those of protein and lactose remain constant.

Conflict of interests

The authors declare no conflict of interest in the present study.

Acknowledgements

The research reported here forms part of doctoral research by Ingrid Merchant Fuentes who received a scholarship from the CONACyT (No. 410994).

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Literature cited: 1. Quintanilla-Medina JJ, González-Reyna A, Hernández-Meléndez J, Limas-Martínez AG, Carreón-Pérez A, Martínez-González JC. Producción de ovinos de pelo bajo condiciones de pastoreo en el noreste de México. Rev Invest Vet Peru 2018;(29):544– 551. 2. FAOSTAT. Estadísticas | FAO | Organización de las Naciones Unidas para la Alimentación y la Agricultura. División de las Estadísticas de la Organización de las Naciones Unidas para la Alimentación (FAO). 2013. 3. Banchero GE, Quintans G, Milton JT, Lindsay DR. Alimentación estratégica para mejorar la lactogénesis de la oveja al parto. Seminario de actualización técnica: Reproducción Ovina. INIA 2005;(33 Tacuarembó):127–136. 4. Millanao I, Herdener N, Parada D, Sepúlveda N. Producción de leche , curvas de lactancia y crecimiento de sus corderos, en dos razas de ovejas en la región de la Araucanía Chile. Sitio Argentino Prod Anim 2007;(APPA-ALPA):1–4. 5. Godfrey RW, Gray ML, Collins JR. Lamb growth and milk production of hair and wool sheep in a semi-arid tropical environment. Small Ruminant Res 1997;(24):77–83. 6. Peniche-Gonzalez I, Sarmiento-Franco L, Santos-Ricalde R. Estimation of milk production in hair ewes by two methods of measurement. Rev MVZ Córdoba 2015;(20):4629–4635. 7. Burgos-González C, Huerta-Aparicio M, Aguirre V, Vazquez R, Orihuela A, Pedernera M. Short communication : Milk production and lamb development in Saint Croix and Katahdin hair sheep breeds (Ovis aries). Trop Anim Health Prod 2017;(3):683-687. 8. Ünal N, Akçapinar H, Atasoy F, Yakan A, Uǧurlu M. Milk yield and milking traits measured with different methods in Bafra sheep. Rev Med Vet (Toulouse). 2008;(159):494–501. 9. Araujo RC, Pires AV., Susin I, Mendes CQ, Rodrigues GH, Packer IU, et al. Milk yield, milk composition, eating behavior, and lamb performance of ewes fed diets containing soybean hulls replacing coastcross (Cynodon species). J Anim Sci 2008;(86):3511– 3521. 10. Peniche-Gonzalez I, Sarmiento-Franco LA, Santos-Ricalde RH. Utilization of Mucuna pruriens whole pods to feed lactating hair ewes. Trop Anim Health Prod 2018;(7):14551461. 11. Notter DR. Effects of ewe age and season of lambing on prolificacy in US Targhee, Suffolk, and Polypay sheep. Small Ruminant Res 2000;(38):1–7.

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12. Sánchez-Dávila F, Bernal H, Colín J, Olivares E, del Bosque AS, Ledezma R, et al. Environmental factors and interval from the introduction of rams to estrus in postpartum Saint Croix sheep. Trop Anim Health Prod 2011;(43):887–891. 13. Nutrient requirements of small ruminants; Sheep, goats, cervids, and new world camelids. Animal Nutrition Series, National Research Council of the National Academies. 2007. 14. Velasco S, Cañeque V, Díaz MT, Pérez C, Lauzurica S, Huidobro F. Producción lechera y composición lipídica de la leche de ovejas Talaveranas durante el período de lactancia. Investig Agrar Prod y Sanid Anim 2001;(16):182–192. 15. ISO. Determination of milkfat, protein and lactose content. 1999. 16. SAS. Proceedings of the Twenty Eighth Annual SAS Users Group International Conference. SAS Instit. Cary, NC; 2003. 17. Church D. Alimentos y alimentación del ganado. 2da ed. Montevideo, Uruguay; 1989. 18. Lopes-Zeola BNM, da Silva-Sobrinho GA, Hatsumura CT, Borghi TH, Viegas CR, Barbosa JC. Production, composition and processing of milk from ewes fed soybean seeds. Rev Bras Zootec 2015;(44):146–154. 19. De Souza-Emediato RM, Ramos-De Siqueira E, De Melo-Stradiotto M, Maestá SA, Gonçalves HC. Desempenho de ovelhas da raça Bergamácia alimentadas com dieta contendo gordura protegida. Rev Bras Zootec 2009;(38):1812–1818. 20. Forcada F, Thos J, Lopez M, Sierra I. Producción de leche de la raza Rasa Aragonesa en la fase de amamantamiento del cordero. Actas IX Jornadas SEOC 1984:161–164. 21. Resksupaphon J. Nutritional effects on mammary development and milk production: effects of prepartum protein supplements [Master thesis]. Universiy of New England; 1996. 22. Ripoll-Bosch R, Álvarez-Rodríguez J, Blasco I, Picazo R, Joy M. Producción de leche y crecimiento de corderos en la raza Ojinegra de Teruel. Inf Téc Económ Agrar 2012;(108):298–311. 23. Manterola H, Cerda D, Mira J, Pavlic A. Producción y composición de la leche en ovejas Merino precoz, Suffolk y Suffolk x Merino. Adv Prod Anim 2007;(32):59–70. 24. Pulina G, Nudda A. La produzione del latte. In: Pulina G, editor. L’alimentazione degli ovini da latte. Avenue Media, Bologna, Italy; 2001:9-31. 25. Bencini R, Pulina G. The quality of sheep milk: a review. Aust J Exp Agric 1997;(37):485–504.

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26. Pulina G, Macciotta N, Nudda A. Milk composition and feeding in the Italian dairy sheep. Ital J Anim Sci 2005;(4 Suppl. 1):5–14. 27. Hinde K, Milligan LA. Primate milk: Proximate mechanisms and ultimate perspectives. Evol Anthropol 2011;(20):9–23.

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https://doi.org/10.22319/rmcp.v12i2.5635 Technical note

Optimization of a DNA extraction protocol for hemolyzed and coagulated bovine blood for use in molecular detection of Anaplasma spp.

Tomás Humberto Landázuri Rafael a,b Andrés Carrazco a Renato León a Lenin Vinueza c Verónica Barragán a*

a

Universidad San Francisco de Quito. Colegio de Ciencias Biológicas y Ambientales, Campus Cumbayá, Diego de Robles s/n, 170901. Quito, Ecuador. b

Pontificia Universidad Católica del Ecuador. Facultad de Ciencias Exactas y Naturales. Quito, Ecuador. c

Universidad San Francisco de Quito. Colegio de Ciencias de la Salud, Escuela de Medicina Veterinaria. Quito, Ecuador.

*Corresponding author: vbarragan@usfq.edu.ec

Abstract: Anaplasma spp. bacteria cause anaplasmosis, a disease which negatively affects livestock production worldwide. Molecular detection by PCR requires efficient extraction of DNA from whole blood, which in turn depends on blood sample quality. Failures in sampling procedures and/or sample storage can lead to hemolysis and blood clotting, which can hamper diagnosis. An established DNA extraction protocol using Chelex® 100 resin was modified to optimize detection of Anaplasma spp. in hemolyzed and coagulated bovine blood samples, as well as reduce its cost. The optimized protocol extracted highly pure DNA effective in PCR analysis. Efficiency of the optimized protocol was compared with two commercial DNA extraction kits. When used in PCR detection of Anaplasma spp., the concordance values for all three were high (Cohen’s Kappa = 0.72). The optimized

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protocol is effective at extracting DNA from complex blood samples and is much less costly than commercial methods, a clear advantage when operating under limited budgets. Key words: Anaplasma, Anaplasmosis, Molecular detection, DNA extraction, Chelex® 100, Blood.

Received: 09/03/2020 Accepted: 10/08/2020

Anaplasmosis is a disease recognized for its worldwide impact on public health and livestock production(1,2). Caused by bacteria of the genus Anaplasma, it results in a debilitating disease in cattle that can be fatal in some cases. The presence of anaplasmosis in a livestock production system can lead to economic losses from decreased milk production, delayed growth and low weight gain(3,4). Due to a lack of epidemiological data in Latin American countries, it is difficult to quantify the true economic impact of bovine anaplasmosis in the region(5). Managing anaplasmosis can be complex because of the existence of asymptomatic carriers. These act as reservoirs, contributing to the disease’s spread and raising infection rates in susceptible populations(5).

Compared to conventional methods such as culture, serology and light microscopy, the polymerase chain reaction (PCR) method provides greater specificity and sensitivity in detecting Anaplasma spp.(6,7). Furthermore, the probability of cross-detection of other hemoparasites is minimal when using PCR(6). Extraction of DNA from clinical samples is a vital step prior to PCR analysis. This is why DNA extraction efficiency is essential to producing reliable and repeatable results. Detection of Anaplasma spp. by PCR ideally requires a whole blood sample since this genus can parasitize different blood cells(7). However, the presence of various elements of the blood and/or failures in sampling, and/or sample transport or conservation can generate changes that make it difficult to extract genetic material or that inhibit the PCR reaction(8,9). For example, alterations can occur in sample homogeneity, and hemolysis and clots can be observed, all of which complicate cell lysis and genetic material release during extraction. In addition, hemolyzed blood contains a higher concentration of hemoglobin and its derivatives, which can compromise PCR diagnostic efficacy. This is why hemolyzed and clotted blood is generally not used in molecular screening tests.

Several DNA extraction kits are currently available on the market. They are designed to extract low concentrations of high quality DNA(10) from complex or poor quality samples such as clotted and hemolyzed blood(11). However, high cost limits generally their use in

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research subject to limited budgets, a common situation in developing countries. One exception is the Chelex® 100 resin DNA extraction method, which is simple and inexpensive, and is therefore used with a wide variety of tissues(12,13). Initially, the cells are lysed to release the DNA, be it with heat treatment or, if necessary, tissue maceration. The Chelex® 100 resin acts as a chelator by capturing magnesium ions, consequently preventing DNA degradation due to nuclease action(12). The Chelex® 100 resin protocol of Singh et al(14) is particularly efficient at extracting high quantities of highly pure DNA. Designed for analysis of dried blood on filter paper, use of this protocol has not yet been described for other types of samples. The present study objective was to optimize this DNA extraction protocol for hemolyzed and coagulated bovine blood samples, to make it applicable for molecular detection of pathogens in animals, specifically, Anaplasma spp. in cattle.

Analyses were run using 40 blood samples collected in September 2018 as part of the “Farm Plans” (Planes de Finca) project(15). The project is promoted by the Autonomous Decentralized Government of the Province of Esmeraldas (Gobierno Autónomo Descentralizado de la Provincia de Esmeraldas - GADPE) and the Inter-American Institute for Cooperation in Agriculture (Instituto Interamericano de Cooperación para la Agricultura - IICA), with the participation of San Francisco University Quito (Universidad San Francisco de Quito). The samples were collected from crossbreed Bos taurus cattle with at least 50 ticks per animal. Blood samples (5 ml each) were taken from the coccygeal or jugular vein in tubes containing anticoagulant. The samples were refrigerated at 4 to 5 °C during transport to the laboratory of the Teaching Veterinary Hospital of San Francisco University Quito, where they were frozen until processing.

Upon thawing, the samples were confirmed to be hemolyzed and to contain small- to medium-sized clots. Extraction of DNA was done in a subgroup of 10 samples with these characteristics and previously confirmed to be positive for Anaplasma sp. The analysis was done following the protocol designed by Singh et al (see Table 1 for summary)(14). Because this protocol was designed for dried blood samples on filter paper, an assay was performed using different volumes of blood (5 µl, 50 µl, and 100 µl). Steps were added to the protocol, specifically in the protein precipitation phase, to improve DNA purity using the sample volume defined in the protocol. Five steps were added: a) Add 75% alcohol at a 1:1 ratio with the volume of supernatant recovered in step 10; b) Let it rest overnight (approx. 16 h) at -20 °C; c) Centrifuge mixture at 13,000 rpm for 1.5 min; d) Recover supernatant; and e) Implement step 11 as shown in Table 1.

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Table 1: DNA extraction protocol of Singh et al(14)

DNA Extraction 1. 2. 3. 4. 5.

Heat to 100 °C, 300 μl 7% Chelex® 100 resin stock solution for 10 min. Add 5 μl blood and heat mixture for 8 min at 100 °C. Mix with a vortex for 15 sec and reheat for 7 min at 100 °C. Centrifuge for 1.5 min at 12,000 rpm. Recover supernatant and discard pellet.

Protein precipitation 6. Add 7.5 M ammonium acetate stock solution to supernatant such that the final solution has a 2.5 M concentration. 7. Rest mixture for 5 min on ice. 8. Mix with a vortex for 10 sec. 9. Centrifuge at 13,000 rpm for 10 min at -4 °C. 10. Recover supernatant in new tube. DNA precipitation 11. Add 3 M ammonium acetate stock solution to supernatant such that the final solution has a 0.3 M concentration. 12. Add 200 μL absolute alcohol. 13. Mix with a vortex for 5 sec. 14. Rest for 4 h at -20 °C. 15. Centrifuge at 13,000 rpm for 10 min at -4 °C. Discard supernatant. 16. Wash pellet two times: first with 200 μL cold 75% alcohol; second with 200 μL cold 100% alcohol. Follow each with a centrifugation at 13,000 rpm for 10 min at 4 °C and discard the supernatant. 17. Allow pellet to air dry for 10 min.

The quantity and purity of extracted DNA was compared between the reference protocol(14) and that with modifications in the protein precipitation phase. The concentration and quality of sample DNA were measured by spectrophotometry in a NanoVue Plus Spectrophotometer (GE Healthcare, USA). The molecular analysis was done under the Framework Contract for Access to Genetic Resources No. MAE-DNBCM-2018-0106.

To demonstrate the efficiency of the modifications made to the established protocol(14), DNA was extracted from 30 hemolyzed and coagulated blood samples for which Anaplasma spp. positivity was unknown. Extraction of DNA was done using the modified protocol as described above, hereafter referred to as the modified Chelex protocol (MCP). From the same samples, DNA was extracted using the commercial kits DNeasy Blood & Tissue Kits Print Qiagen® and AccuPrep® Genomic DNA Extraction Kit Bioneer®,

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following the manufacturers’ recommendations for DNA extraction from whole blood. Confirmation of MCP efficacy in molecular detection of Anaplasma spp. was done by applying a PCR reaction specific to the Anaplasma bacterial genus(16). The amplicons obtained from 13 positive samples (n = 40) were sequenced at Functional Biosciences, Inc. (Wisconsin, USA) to confirm the presence of Anaplasma spp. DNA. The constitutive gene that codes for the protein β-Actin, always present in bovine blood samples(17), was used to rule out the possibility of false negatives due to inhibition of the PCR reaction. The details of the primers and the product size of both PCR reactions are shown in Table 2.

Table 2: Primer sequences Gene

Primer

Sequence: 5' - 3'

16S rDNA

AnaplsppF AnaplR3 XAHR 17 XAHR 20

AGAAGAAGTCCCGGCAAACT GAGACGACTTTTACGGATTAGCTC CGGAACCGCTCATTGCC ACCCACACTGTGCCCATCTA

β-actin

Size

Ref.

800 bp

(18)

289 bp

(19)

The results were analyzed with a Shapiro-Wilks normality test and non-parametric tests. Differences in the amount of DNA extracted between blood volumes (5 µl, 50 µl and 100 µl) were identified with the Friedman test and a Wilcoxon post-hoc analysis; the P values were adjusted with the Bonferroni correction(19). Comparison of DNA purity from the protein precipitation assays was done with the Wilcoxon non-parametric test. The Cohen’s Kappa test and McNemar test were applied to identify concordance between the PCR results from the three extraction methods(20,21). All statistical tests were run at a 95% significance level and using the R v.3.3.0 software(18).

The reference protocol(14) was used in 10 hemolyzed and coagulated blood samples. To define optimum sample volume, three different volumes (5 µl, 50 µl and 100 µl) of liquid blood from each sample were tested. The DNA concentrations differed between the 5 µl volume and 50 µL and 100 µL volumes (Friedman test: χ2(2) = 16.800, P= 0.017) (Figure 1), but not between the 50 µL and 100 µL volumes (Wilcoxon: Z= -2,293, P= 0.063). With the intent of using the lowest possible volume, the 50 µl volume was used in the following steps.

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Figure 1: DNA concentration (ng/µl) obtained from different volumes of blood (n=10), using extraction method of Singh et al(14) (χ2(2) = 16,800; P=0.017*)

When using the reference protocol(14), the purity of the DNA extracted from the coagulated and hemolyzed blood samples yielded a median A260/280 ratio of 0.820 (n = 10). In the MCP, modification of the protein precipitation phase increased the median A260/280 ratio to 1.970 (n= 10). Compared to the reference protocol(14), the MCP allows significant increases in the 260/280 (Wilcoxon: Z= -2.803, P= 0.005) and 260/230 (Wilcoxon: Z= -2.666, P= 0.002) ratios (Figure 2). Worth mentioning is that the DNA concentration in these samples decreased significantly (Wilcoxon: Z= -2.803, P= 0.005) compared to that obtained with the reference protocol(14). However, this did not interfere with molecular detection of Anaplasma spp. in any of the samples. An added advantage is that the nonspecific bands observed when amplifying samples extracted with the reference protocol(14) did not appear when using the MCP. Figure 2: Comparison between the Singh et al(14) extraction protocol and the modified Chelex protocol (MCP) in terms of A) DNA purity and B) DNA quantity (n=10)

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The DNA extracted from 30 samples of coagulated and hemolyzed blood with two commercial kits and the MCP exhibited no inhibition of the PCR reaction. The same was true in terms of analysis of the presence of Anaplasma spp. (Table 3), with high Cohen’s Kappa concordance index values (0.72) between the MCP and the commercial kits. The McNemar exact test identified no significant differences between the kits and the MCP in the proportion of positive samples detected by PCR (McNemar’s Chi-squared 0.500; P= 0.5).

Table 3: Anaplasma spp. positivity results in blood samples processed with different methods (n=30) Qiagen Kit Bioneer Kit Positives Negatives Positives Negatives MCP Positives 25 0 25 0 Negatives 2 3 2 3 MCP= modified Chelex protocol.

Bovine anaplasmosis’ negative impacts in the livestock sector(1,2) can include anemia, weakness, reduced growth and milk production, abortions and even mortality in infected cattle(22). The true prevalence of anaplasmosis in cattle in Latin America and the Caribbean is unknown. This is partially due to the fact that 80 % of livestock producers in these regions are small family farmers living in rural and marginal areas (23), and their meagre financial resources limit efforts towards vaccination and infectious disease control(24). Limited resources in developing countries is also a problem when doing research or implementing disease prevention campaigns since laboratory supplies can cost two to ten times more than in developed countries(25). This highlights the need to develop techniques that accurately detect Anaplasma spp. and are affordable for both the agencies in charge of controlling anaplasmosis and for small and large farmers.

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Molecular detection of pathogens by PCR from clinical samples has become a widely used methodology for infectious disease diagnosis and monitoring(26). This technique also allows subsequent characterization of the pathogen by sequencing its genetic material, which produces data useful in understanding disease epidemiology. A vital step prior to molecular detection is extraction of genetic material from samples. This procedure can be affected by sample collection, transport and storage practices. Each of these steps must ensure that pathogen genetic material remains intact until extraction procedure implementation. However, pre-extraction conditions are not always ideal. For example, sample collection from animals in difficult-to-access rural areas makes optimal sample collection and conservation a challenge. Under these conditions samples commonly exhibit hemolysis and clots, which make subsequent analysis difficult because they can inhibit the pathogen molecular detection reaction.

The present results confirmed that the modifications made to the DNA extraction protocol of Singh et al(14) allow DNA extraction from hemolyzed and coagulated blood which can then be used in molecular detection of Anaplasma spp. When the MCP was used to extract DNA from 50 µL of sample, the purity values in both the 260/280 and 260/230 ratios were higher than when using the reference protocol(14). The MCP did produce less DNA than the tested commercial kits, but with no differences in terms of Anaplasma spp. positivity. The Kappa concordance index value (0.72) indicates high concordance among the results from all three extraction methods(20). Therefore, blood volume standardization and modification of the reference protocol(14) produced equivalent results in the MCP and the commercial kits. Future research could determine if the MCP is also effective at detecting other pathogens found in the blood of cattle and other animals.

The MCP also allowed DNA extraction from Anaplasma spp. from bovine blood samples at considerably less cost than the tested commercial kits. This relative cost effectiveness is based on the cost of reagents from authorized suppliers in Ecuador. Extraction of DNA from 250 blood samples using the MCP would cost approximately US$ 60, considering only reagents. In contrast, the cost of processing the same number of samples with the tested commercial kits would be US$ 600 with the Bioneer® kit and US$ 2,000 with the Qiagen® kit; again this includes only reagents and not the equipment needed to run the extraction (the Bioneer® kit requires its own specialized equipment).

One of the principal reasons for the high cost of reagents in countries such as Ecuador, Colombia and Mexico, among others, is that they are not manufactured in Latin America. Import fees and the commissions charged by local suppliers therefore greatly increase the cost of scientific analyses. A chronic lack of financial resources is perhaps the greatest limiting factor when attempting to carry out research in developing countries. Functioning under these circumstances requires creative development of reliable low-cost techniques for infectious disease research and monitoring. This is an important challenge to 660


Rev Mex Cienc Pecu 2021;12(2):653-664

overcome to better understand disease epidemiology, and to design and implement effective control/monitoring plans that benefit animal production and protect exposed human populations.

The low-cost modified Chelex® resin protocol developed here for DNA extraction from hemolyzed and clotted blood produces DNA of high quality for molecular detection of Anaplasma spp. by PCR. Results are equivalent to those obtained with commercial kits. The proposed protocol is ideal for monitoring Anaplasma spp. in cattle under limited research and/or disease control budgets. Creation of alternative low-cost protocols for pathogen detection and molecular analysis makes research more accessible, even under the conditions prevailing in developing countries. This will increase the ability of livestock sector and public health agencies to proceed efficiently and effectively. Considering the cost effectiveness of the modified Chelex protocol (MCP), it is well worth testing its usefulness in detecting other pathogens and its extraction efficiency with other sample types.

Acknowledgements

The research reported was supported by the Gobierno Autónomo Descentralizado de la Provincia de Esmeraldas (GADPE) and the Instituto Interamericano de Cooperación para la Agricultura (IICA). It was financed with research funds from the Colegio de Ciencias Biológicas-USFQ (2019-2020) granted to Verónica Barragán as well as research funds from the Escuela de Medicina Veterinaria-USFQ (2017-2018) granted to Lenin Vinueza. Publication of this article was financed by the Fondo para Publicación de Artículos Académicos of the Universidad San Francisco de Quito USFQ. Thanks are due to Fernanda Loaiza for technical suggestions at the beginning of the research.

Conflicts of interest

The authors declare no conflict of interest.

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Rev. Mex. Cienc. Pecu. Vol. 12 Núm 2, pp. 318-664, ABRIL-JUNIO-2021

ISSN: 2448-6698

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