RMCP Vol. 10, Num. 1 (2019): January-March [english version] by Revista Mexicana de Ciencias Pecuarias

Edición Bilingüe Bilingual Edition

Revista Mexicana de Ciencias Pecuarias Rev. Mex. Cienc. Pecu. Vol. 10 Núm. 1, pp. 1- 266, ENERO-MARZO-2019

ISSN: 2448-6698

Rev. Mex. Cienc. Pecu. Vol. 10 Núm. 1, pp. 1-266, ENERO-MARZO-2019

REVISTA MEXICANA DE CIENCIAS PECUARIAS Volumen 10 Número 1 EneroMarzo, 2019. 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 04-2016-060913393200-203. ISSN: 2448-6698, 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 Enero de 2019. Polinización de cultivos de hortalizas en el Campo Experimental Costa de Hermosillo. Fotografía tomada por: Agustín Alberto Fu Castillo. Concurso de fotografía INIFAP 2010

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

EDITOR EN JEFE Arturo García Fraustro

EDITORES POR DISCIPLINA Dra. Yolanda Beatriz Moguel Ordóñez, INIFAP, México Dr. Ramón Molina Barrios, Instituto Tecnológico de Sonora, México Dra. Maria Cristina Schneider, PAHO, Estados Unidos Dra. Elisa Margarita Rubí Chávez, UNAM, 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. Sergio D. Rodríguez Camarillo, INIFAP, México Dr. Martin Talavera Rojas, Universidad Autónoma del Estado de México, 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 Dra. Silvia Elena Buntinx Dios, Facultad de Medicina Veterinaria y Zootecnia, UNAM, México 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. 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. Fernando Cervantes Escoto, Universidad Autónoma Chapingo, México Dr. Adolfo Guadalupe Álvarez Macías, Universidad Autónoma Metropolitana Xochimilco, México Dr. Alfredo Cesín Vargas, UNAM, México.

TIPOGRAFÍA Y FORMATO Nora del Rocío Alfaro Gómez 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).

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.

total por publicar es de $ 5,600.00 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.

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.

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)

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

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.

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.

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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).

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 $ 325.00 per article in both printed languages.

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

REVISTA MEXICANA DE CIENCIAS PECUARIAS REV. MEX. CIENC. PECU.

VOL. 10 No. 1

ENERO-MARZO-2019

CONTENIDO ARTÍCULOS

Pág. Frecuencia de Cryptosporidium en perros asociados a establos lecheros y en áreas urbanas del estado de Aguascalientes, México Cryptosporidium infection frequency in dogs on dairy farms and in urban areas of the state of Aguascalientes, Mexico Irene Vitela-Mendoza, Kenia Padilla Díaz, Carlos Cruz-Vázquez, Leticia Medina-Esparza, Miguel Ramos-Parra .................................................................................................................................... …..1

Distribución potencial de Musca domestica en el municipio de Jesús María, Aguascalientes, con el uso de escenarios de cambio climático Potential distribution of Musca domestica in Jesús María Municipality, Aguascalientes, Mexico, based on climate change scenarios Antonio de Jesús Meraz Jiménez, Armando López Santos, Carlos Alberto García Munguía, Jorge Alejandro Torres González, Alberto Margarito García Munguía ......................................................... .14

Control de la helmintiasis en becerros criados en una región semiárida cálida de Brasil Helminthiasis control in calves raised in a hot Semi-arid area Ludmilla de Fátima Leal Pereira, Eduardo Robson Duarte, Gabriela Almeida Bastos, Viviane de Oliveira Vasconcelos, Evely Giovanna Leite Costa, Laydiane de Jesus Mendes, Idael Matheus Góes Lopes, Iara Maria Franca Reis ............................................................................................................................... 30

Importancia de la jerarquía social sobre los comportamientos alimenticios y parasitarios de ovinos criados en dos sistemas pastoriles Importance of sheep social hierarchy on feeding behavior and parasite load in silvopastoral and grass monoculture grazing systems Carolina Flota-Bañuelos, Juan A. Rivera-Lorca, Bernardino Candelaria-Martínez.......................... …..52

Aislamiento e identificación de bacterias ácido lácticas con potencial probiótico para becerros del altiplano mexicano Isolation and identification of potentially probiotic lactic acid bacteria for Holstein calves in the Mexican Plateau Patricia Landa-Salgado, Yesenia Caballero-Cervantes, Efrén Ramírez-Bribiesca, Ana María HernándezAnguiano, Luz Mariana Ramírez-Hernández, David Espinosa-Victoria, David Hernández-Sánchez .... 68

III

Efecto de monensina intraruminal sobre el β-hidroxibutirato, enfermedades del periparto, producción de leche y sus componentes en ganado Holstein Effect of an intraruminal monensin bolus on blood β-hydroxybutyrate, peripartum diseases, milk yield and solids in Holstein cows Pedro Melendez, Alejandra Arévalos, Mario Duchens, Pablo Pinedo .................................................. 84

Evaluación y análisis sensorial del Queso Bola de Ocosingo (México) desde la perspectiva del consumidor Consumer evaluation and sensory analysis of Queso Bola de Ocosingo (Mexico) Mónica Agudelo-López, Alfredo Cesín-Vargas, Angélica Espinoza-Ortega, Benito Ramírez-Valverde104

REVISION DE LITERATURA

Factors affecting the ruminal microbial composition and methods to determine microbial protein yield. Review Factores que afectan la composición microbiana ruminal y métodos para determinar el rendimiento de la proteína microbiana. Revisión Ezequias Castillo-López, María G. Domínguez-Ordóñez .................................................................... 120

NOTAS DE INVESTIGACIÓN

Dinámica de infección por Cystoisospora suis (Isospora suis) en una granja piloto ubicada en el estado Carabobo, Venezuela Infection dynamics of Cystoisospora suis (Isospora suis) on a pilot swine farm in Carabobo State, Venezuela Juan Carlos Pinilla León, Natalia Da Silva Borges ............................................................................. 149

Design of an electrochemical prototype to determine relative NaCl content and its application in fresh cheeses Desarrollo y evaluación de un prototipo electroquímico para determinar el contenido relativo de NaCl y su aplicación en quesos frescos Rubén Cázares-Gallegos, Juan Antonio Vidales-Contreras, Alejandro Isabel Luna-Maldonado, Michael E. Hume, Ramón Silva-Vázquez, Armando Quintero-Ramos, Gerardo Méndez-Zamora ................... 161

La calidad sanitaria del chorizo rojo tradicional que se comercializa en la ciudad de Toluca, Estado de México Hygienic quality of the traditional red chorizo commercialized in the city of Toluca, State of Mexico Ana Laura Becerril Sánchez, Octavio Dublán García, Aurelio Domínguez-López, Daniel Arizmendi Cotero, Baciliza Quintero-Salazar ..................................................................................................... 172

Impacto de la vigilancia sanitaria del clembuterol en Guerrero, México: Resultados de 2011 a 2015 Impact of health monitoring of clenbuterol in Guerrero, Mexico: Results from 2011 to 2015 Luis Alberto Chávez-Almazán, Jesús Antonio Díaz-Ortiz, Diana Garibo-Ruiz, Mario Alberto AlarcónRomero, Miguel Angel Mata-Diaz, Beatriz Pérez-Cruz, Elizabeth Godoy-Galeana ............................ 186

Condiciones poblacionales y alimenticias de colonias de abejas melíferas (Apis mellifera) en tres regiones del altiplano semiárido de México Populations and food stores of honey bee (Apis mellifera) colonies from three regions of Mexico’s semiarid high plateau Carlos Aurelio Medina-Flores, Ernesto Guzmán-Novoa, Jairo Iván Aguilera Soto, Marco Antonio López Carlos, Sergio Ernesto Medina-Cuéllar.............................................................................................. 199

Composición botánica y valor nutritivo de la dieta consumida por bovinos en un área invadida por pasto rosado [Melinis repens (willd.) Zizka] Botanical composition and nutritive value of the diet consumed by cattle in an area invaded by natal grass [Melinis repens (Willd.) Zizka] Obed Gabriel Gutiérrez Gutiérrez, Carlos Raúl Morales Nieto, José Carlos Villalobos González, Oscar Ruíz Barrera, Juan Ángel Ortega Gutiérrez, Jorge Palacio Núñez ..................................................... 212

Dosis letal media (DL50) y reducción de crecimiento (GR50) por irradiación gamma en pasto garrapata (Eragrostis superba) Mean lethal dose (LD50) and growth reduction (GR50) due to gamma radiation in Wilman lovegrass (Eragrostis superba) Alan Álvarez-Holguín, Carlos Raúl Morales-Nieto, Carlos Hugo Avendaño-Arrazate, Raúl CorralesLerma, Federico Villarreal-Guerrero, Eduardo Santellano-Estrada, Yaudiel Gómez-Simuta ............. 227

Rendimiento de forraje y sus componentes en variedades de alfalfa en el altiplano de México Yield of forage and its components in alfalfa varieties of the Mexican high plateau Adelaido Rafael Rojas García, Nicolás Torres Salado, María de los Ángeles Maldonado Peralta, Jerónimo Herrera Pérez, Paulino Sánchez Santillán, Aldenamar Cruz Hernández, Félix de Jesús Mayren Mendoza, Alfonso Hernández Garay..................................................................................... 239

Evaluation of clinical, radiological, ultrasonographic and microbiological findings of septic arthritis in 50 calves Evaluación de los hallazgos clínicos, radiológicos, ultrasonográficos y microbiológicos de la artritis séptica en 50 becerros İbrahim Yurdakul .............................................................................................................................. 254

Actualización: abril, 2018 NOTAS AL AUTOR La Revista Mexicana de Ciencias Pecuarias se edita completa en dos idiomas (español e inglés) y publica tres categorías de trabajos: Artículos científicos, Notas de investigación y Revisiones bibliográficas.

indican, empezando cada uno de ellos en página aparte. Página del título Resumen en español Resumen en inglés Texto Agradecimientosy conflicto de interés Literatura citada Cuadros y gráficas

Los autores interesados en publicar en esta revista deberán ajustarse a los lineamientos que más adelante se indican, los cuales en términos generales, están de acuerdo con los elaborados por el Comité Internacional de Editores de Revistas Médicas (CIERM) Bol Oficina Sanit Panam 1989;107:422-437. 1.

Sólo se aceptarán trabajos inéditos. No se admitirán si están basados en pruebas de rutina, ni datos experimentales sin estudio estadístico cuando éste sea indispensable. Tampoco se aceptarán trabajos que previamente hayan sido publicados condensados o in extenso en Memorias o Simposio de Reuniones o Congresos (a excepción de Resúmenes).

Todos los trabajos estarán sujetos a revisión de un Comité Científico Editorial, conformado por Pares de la Disciplina en cuestión, quienes desconocerán el nombre e Institución de los autores proponentes. El Editor notificará al autor la fecha de recepción de su trabajo.

El manuscrito deberá someterse a través del portal de la Revista en la dirección electrónica: http://cienciaspecuarias.inifap.gob.mx, consultando el “Instructivo para envío de artículos en la página de la Revista Mexicana de Ciencias Pecuarias”. Para su elaboración se utilizará el procesador de Microsoft Word, con letra Times New Roman a 12 puntos, a doble espacio. Asimismo se deberán llenar los formatos de postulación, carta de originalidad y no duplicidad y formato de derechos patrimoniales disponibles en el propio sitio oficial de la revista.

Por ser una revista con arbitraje, y para facilitar el trabajo de los revisores, todos los renglones de cada página deben estar numerados; asimismo cada página debe estar numerada, inclusive cuadros, ilustraciones y gráficas.

Página del Título. Solamente debe contener el título del trabajo, que debe ser conciso pero informativo; así como el título traducido al idioma inglés. En el manuscrito no es necesaria información como nombres de autores, departamentos, instituciones, direcciones de correspondencia, etc., ya que estos datos tendrán que ser registrados durante el proceso de captura de la solicitud en la plataforma del OJS (http://ciencias pecuarias.inifap.gob.mx).

Resumen en español. En la segunda página se debe incluir un resumen que no pase de 250 palabras. En él se indicarán los propósitos del estudio o investigación; los procedimientos básicos y la metodología empleada; los resultados más importantes encontrados, y de ser posible, su significación estadística y las conclusiones principales. A continuación del resumen, en punto y aparte, agregue debidamente rotuladas, de 3 a 8 palabras o frases cortas clave que ayuden a los indizadores a clasificar el trabajo, las cuales se publicarán junto con el resumen.

Resumen en inglés. Anotar el título del trabajo en inglés y a continuación redactar el “abstract” con las mismas instrucciones que se señalaron para el resumen en español. Al final en punto y aparte, se deberán escribir las correspondientes palabras clave (“key words”).

10. Texto. Las tres categorías de trabajos que se publican en la Rev. Mex. Cienc. Pecu. consisten en lo siguiente: a) Artículos científicos. Deben ser informes de trabajos originales derivados de resultados parciales o finales de investigaciones. El texto del Artículo científico se divide en secciones que llevan estos encabezamientos:

Los artículos tendrán una extensión máxima de 20 cuartillas a doble espacio, sin incluir páginas de Título, y cuadros o figuras (los cuales no deberán exceder de ocho). Las Notas de investigación tendrán una extensión máxima de 15 cuartillas y 6 cuadros o figuras. Las Revisiones bibliográficas una extensión máxima de 30 cuartillas y 5 cuadros.

Introducción Materiales y Métodos Resultados Discusión Conclusiones e implicaciones

Los manuscritos de las tres categorías de trabajos que se publican en la Rev. Mex. Cienc. Pecu. deberán contener los componentes que a continuación se

En los artículos largos puede ser necesario agregar subtítulos dentro de estas divisiones a fin de hacer más claro el contenido, sobre todo en las secciones de Resultados y de Discusión, las cuales también pueden presentarse como una sola sección.

apellidos compuestos se debe poner un guión entre ambos, ejemplo: Elías-Calles E. Entre las iniciales de un autor no se debe poner ningún signo de puntuación, ni separación; después de cada autor sólo se debe poner una coma, incluso después del penúltimo; después del último autor se debe poner un punto.

b) Notas de investigación. Consisten en modificaciones a técnicas, informes de casos clínicos de interés especial, preliminares de trabajos o investigaciones limitadas, descripción de nuevas variedades de pastos; así como resultados de investigación que a juicio de los editores deban así ser publicados. El texto contendrá la misma información del método experimental señalado en el inciso a), pero su redacción será corrida del principio al final del trabajo; esto no quiere decir que sólo se supriman los subtítulos, sino que se redacte en forma continua y coherente.

El título del trabajo se debe escribir completo (en su idioma original) luego el título abreviado de la revista donde se publicó, sin ningún signo de puntuación; inmediatamente después el año de la publicación, luego el número del volumen, seguido del número (entre paréntesis) de la revista y finalmente el número de páginas (esto en caso de artículo ordinario de revista). Puede incluir en la lista de referencias, los artículos aceptados aunque todavía no se publiquen; indique la revista y agregue “en prensa” (entre corchetes).

c) Revisiones bibliográficas. Consisten en el tratamiento y exposición de un tema o tópico de relevante actualidad e importancia; su finalidad es la de resumir, analizar y discutir, así como poner a disposición del lector información ya publicada sobre un tema específico. El texto se divide en: Introducción, y las secciones que correspondan al desarrollo del tema en cuestión.

En el caso de libros de un solo autor (o más de uno, pero todos responsables del contenido total del libro), después del o los nombres, se debe indicar el título del libro, el número de la edición, el país, la casa editorial y el año. Cuando se trate del capítulo de un libro de varios autores, se debe poner el nombre del autor del capítulo, luego el título del capítulo, después el nombre de los editores y el título del libro, seguido del país, la casa editorial, año y las páginas que abarca el capítulo.

11. Agradecimientos y conflicto de interés. Siempre que corresponda, se deben especificar las colaboraciones que necesitan ser reconocidas, tales como a) la ayuda técnica recibida; b) el agradecimiento por el apoyo financiero y material, especificando la índole del mismo; c) las relaciones financieras que pudieran suscitar un conflicto de intereses. Las personas que colaboraron pueden ser citadas por su nombre, añadiendo su función o tipo de colaboración; por ejemplo: “asesor científico”, “revisión crítica de la propuesta para el estudio”, “recolección de datos”, etc. Siempre que corresponda los autores deberán mencionar si existe algún conflicto de interés. 12. Literatura citada. Numere las referencias consecutivamente en el orden en que se mencionan por primera vez en el texto. Las referencias en el texto, en los cuadros y en las ilustraciones se deben identificar mediante números arábigos entre paréntesis, sin señalar el año de la referencia. Evite hasta donde sea posible, el tener que mencionar en el texto el nombre de los autores de las referencias. Procure abstenerse de utilizar los resúmenes como referencias; las “observaciones inéditas” y las “comunicaciones personales” no deben usarse como referencias, aunque pueden insertarse en el texto (entre paréntesis).

En el caso de tesis, se debe indicar el nombre del autor, el título del trabajo, luego entre corchetes el grado (licenciatura, maestría, doctorado), luego el nombre de la ciudad, estado y en su caso país, seguidamente el nombre de la Universidad (no el de la escuela), y finalmente el año. Emplee el estilo de los ejemplos que aparecen a continuación, los cuales están parcialmente basados en el formato que la Biblioteca Nacional de Medicina de los Estados Unidos usa en el Index Medicus. Revistas

Artículo ordinario, con volumen y número. (Incluya el nombre de todos los autores cuando sean seis o menos; si son siete o más, anote sólo el nombre de los seis primeros y agregue “et al.”). I)

Reglas básicas para la Literatura citada Nombre de los autores, con mayúsculas sólo las iniciales, empezando por el apellido paterno, luego iniciales del materno y nombre(s). En caso de

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.

Sólo número sin indicar volumen. II) Stephano HA, Gay GM, Ramírez TC. Encephalomielitis, reproductive failure and corneal opacity (blue eye) in

VII

pigs associated with a paramyxovirus infection. Vet Rec 1988;(122):6-10.

Beltsville Symposium: Biotechnology’s role in genetic improvement of farm animals. USDA. 1996:13.

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

No se indica el autor. IV) Cancer in South Africa [editorial]. S Afr Med J 1994;84:15.

Suplemento de revista. 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.

Organización, como autor. VI) The Cardiac Society of Australia and New Zealand. Clinical exercise stress testing. Safety and performance guidelines. Med J Aust 1996;(164):282-284.

En proceso de publicación. VII) Scifres CJ, Kothmann MM. Differential grazing use of herbicide treated area by cattle. J Range Manage [in press] 2000.

Libros y otras monografías

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

Autor de capítulo. IX)

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

Memorias de reuniones. 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

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

Organización como autor. 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. Oficial 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.

Publicaciones electrónicas 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. Accessed 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 Ago, 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/03016226. Accessed Sep 12, 2003. 13. Cuadros, Gráficas e Ilustraciones. Es preferible que sean pocos, concisos, contando con los datos

VIII

necesarios para que sean autosuficientes, que se entiendan por sí mismos sin necesidad de leer el texto. Para las notas al pie se deberán utilizar los símbolos convencionales.

km kilómetro (s) L litro (s) log logaritmo decimal Mcal megacaloría (s) MJ megajoule (s) m metro (s) msnm metros sobre el nivel del mar µg microgramo (s) µl microlitro (s) µm micrómetro (s)(micra(s)) mg miligramo (s) ml mililitro (s) mm milímetro (s) min minuto (s) ng nanogramo (s)Pprobabilidad (estadística) p página PC proteína cruda PCR reacción en cadena de la polimerasa pp páginas ppm partes por millón % por ciento (con número) rpm revoluciones por minuto seg segundo (s) t tonelada (s) TND total de nutrientes digestibles UA unidad animal UI unidades internacionales

14 Versión final. Es el documento en el cual los autores ya integraron las correcciones y modificaciones indicadas por el Comité Revisor. Los trabajos deberán ser elaborados con Microsoft Word. Las gráficas y figuras se deberán elaborar en Word, Power Point, Corel Draw y enviadas en archivo aparte (nunca insertarlas como imágenes en el texto). Los cuadros no deberán contener ninguna línea vertical, y las horizontales solamente las que delimitan los encabezados de columna, y la línea al final del cuadro. 15. Una vez recibida la versión final, ésta se mandará para su traducción al idioma inglés o español, según corresponda. Si los autores lo consideran conveniente podrán enviar su manuscrito final en ambos idiomas. 16. Tesis. Se publicarán como Artículo o Nota de Investigación, siempre y cuando se ajusten a las normas de esta revista. 17. Los trabajos no aceptados para su publicación se regresarán al autor, con un anexo en el que se explicarán los motivos por los que se rechaza o las modificaciones que deberán hacerse para ser reevaluados. 18. Abreviaturas de uso frecuente: cal cm °C DL50 g ha h i.m. i.v. J kg

caloría (s) centímetro (s) grado centígrado (s) dosis letal 50% gramo (s) hectárea (s) hora (s) intramuscular (mente) intravenosa (mente) joule (s) kilogramo (s)

versus

gravedades

Cualquier otra abreviatura se pondrá entre paréntesis inmediatamente después de la(s) palabra(s) completa(s). 19. Los nombres científicos y otras locuciones latinas se deben escribir en cursivas.

Updated: April, 2018 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.

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 â&#x20AC;&#x153;Guide for submit articles in the Web site of the Revista Mexicana de Ciencias Pecuariasâ&#x20AC;?. Manuscripts should be prepared, typed in a 12 points font at double space (including the abstract and tables). At the time of submission, the application form, must be filled out, as well as a letter of originality and no duplication and patrimonial rights format, available on the official website of the journal.

References Tables and Graphics 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).

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.

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: Introduction Materials and Methods Results Discussion Conclusions and implications

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.

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.

Research articles will not exceed 20 double spaced pages, without including Title page and Tables and Figures (8 maximum). 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.

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

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.

c) Reviews. The purpose of these papers is to

Title page Abstract Text Acknowledgments

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. References. 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 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.

Key rules for references 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).

Organization, as author

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 names(s), the number of the edition, the country, the printing house and the year.

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

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.

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

XVIII) SAS. SAS/STAT User’s Guide (Release 6.03). Cary NC, USA: SAS Inst. Inc. 1988.

Books and other monographs

Author(s)

XIX) SAS. SAS User´s Guide: Statistics (version 5 ed.). Cary NC, USA: SAS Inst. Inc. 1985.

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

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.

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.

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.

Conference paper X)

XI)

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.

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.

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 incorporated all the corrections and modifications asked for by the editors. Graphs and figures should be submitted separately in Microsoft Word, MS Power Point, or Corel Draw. Figures must not be inserted as images within the text. In Tables do not use internal horizontal or vertical lines.

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

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.

Organization as author XV) NRC. National Research Council. The nutrient requirements of beef cattle. 6th ed. Washington, DC, USA: National Academy Press; 1984.

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.

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.

17. List of abbreviations:

XVII) AOAC. Official methods of analysis. 15th ed. Arlington, VA, USA: Association of Official Analytical Chemists. 1990.

cal cm °C

XII

calorie (s) centimeter (s) degree Celsius

DL50 g ha h i.m. i.v. J kg km L log Mcal MJ m Âľl Âľm mg ml mm min ng

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) mega joule (s) meter (s) micro liter (s) micro meter (s) milligram (s) milliliter (s) millimeter (s) minute (s) nanogram (s)

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

versus

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.

XIII

http://dx.doi.org/10.22319/rmcp.v10i1.4758 Article

Cryptosporidium infection frequency in dogs on dairy farms and in urban areas of the state of Aguascalientes, Mexico

Irene Vitela-Mendozaa* Kenia Padilla Díaza Carlos Cruz-Vázqueza Leticia Medina-Esparzaa Miguel Ramos-Parraa

Instituto Tecnológico El Llano Aguascalientes, Km 18 Carretera Ags-SLP., Municipio de El Llano, Ags., 20330, Aguascalientes, México.

* Corresponding author: vitelairene@yahoo.com.mx

Abstract The intestinal parasite Cryptosporidium spp. is highly infectious in wild and domestic animals and humans. Infection frequency in dogs can vary between rural and urban environments. Cryptosporidium spp. infection frequency was quantified in dogs on dairy farms and in an urban area in the state of Aguascalientes, Mexico, and some possible risk factors analyzed. Feces samples were collected from 168 dogs at 30 dairy farms distributed among the state’s ten municipalities (rural), and from 144 dogs at the Aguascalientes municipal Animal Control, Care and Welfare Center (urban area). Fecal smears were stained with Kinyoun to identify and count parasite oocysts. A questionnaire was applied to gather information on factors that could increase infection risk, and a risk analysis run using logistic regression. Overall infection frequency was 20.5 % (64/312; CI95% 16-25). In farm dogs it was 30 % (51/168; 95% CI 23-38) and in urban dogs 9 % (13/144; 95% CI 5-15). Seventy percent (70 %) of the dairy farms had positive dogs, average number of dogs per farm was 5.6, and dog density per farm was 2 to 12. Diarrheic feces was the only identified risk factor for Cryptosporidium infection, in both urban dogs (OR, 3.2; 95% CI 1.06-9.79 P<0.03) and farm dogs (OR, 2.7; CI95% 1.36-5.49 P<0.001). Infection frequency was highest in farm dogs, suggesting a consequently higher probability of cross-infection in this type of environment. 1

Rev Mex Cienc Pecu 2019;10(1):1-13

Key words: Cryptosporidium, Frequency, Dogs, Risk factors.

Received: 29/01/2018 Accepted: 06/03/2018

Introduction

Cryptosporidiosis is an intestinal parasitic infection caused by protozoans of the genus Cryptosporidium (Apicomplexa: Cryptosporiidae). Unlike other coccidia, Cryptosporidium spp. oocysts are infectious from the moment excreted by an infected individual and can infect another host through ingestion. They have a cosmopolitan distribution and are considered opportunistic parasites, causing severe digestive disorders in young individuals. They affect many domestic and wild animals, as well as humans(1). Dogs and cats are common pets because they can develop a bond with humans. However, they are also exposed to numerous parasite infections, representing a risk of transmission to other animals and humans(2). Dogs may be naturally infected by C. canis(3), C. parvum(4), C. meleagridis(5), and C. muris(6). Infection is typically asymptomatic, but can cause severe clinical manifestations including watery diarrhea, fever, and pathologies of the respiratory system, liver, and pancreas, especially in immunocompromised animals(7, 8) . Canine cryptosporidiosis is widely distributed. It has been reported worldwide in dogs in private homes, in kennels, in shelters and in stray dogs; reports are largely from urban areas but it has been reported in some rural communities(9,10,11). Little data exists in Mexico on the epidemiological traits of this disease in dog populations in urban and rural areas and communities, which would help to better understand the infection transmission and maintenance process in other domestic animals, livestock and humans. The present study objective was to quantify Cryptosporidium spp. frequency and identify risk factors associated with the infection in dogs from rural environments associated with dairy farms and from an urban area in Aguascalientes, Mexico.

Rev Mex Cienc Pecu 2019;10(1):1-13

Material and methods

The study was carried out in the state of Aguascalientes, Mexico (21°37', 22°01' N; 101°52', 102°35' W). Altitude in the region ranges from 1,765 and 2,400 m asl, average annual temperature is 17.4 °C, and annual average rainfall is 526 mm, mostly in the summer(12).

Dairy farm sampling sites

Samples were collected at 30 dairy farms in 10 of the state’s municipalities. In each municipality, three farms with at least one domestic dog were sampled; only farms where owners could provide the necessary facilities were included.

Rev Mex Cienc Pecu 2019;10(1):1-13

Figure 1: Location of sampled dairy farms (numbered 1, 2, 3 in each municipality) and CCABA

Municipality codes: Pabellón de Arteaga (PA), Asientos (ASI), San José de Gracia (SJG), Cosío (COS), Tepezalá (TEP), Rincón de Romos (RR), San Francisco de los Romo (SFR), Calvillo (CAL), Jesús María (JM), Aguascalientes (AGS) and El Llano (ELL).

Urban sampling site

Samples were collected from dogs housed at the Aguascalientes Municipal Center for Animal Control, Care and Welfare (Centro de Control, Atención y Bienestar Animal del Municipio de Aguascalientes - CCABA). Dogs here are strays collected from city streets or have been left here. After 72 h, unclaimed dogs are humanely sacrificed following established procedures (NOM-033-SAG/ZOO-2014).

Rev Mex Cienc Pecu 2019;10(1):1-13

Sample collection

A single visit was made to each dairy farm and a feces sample (approx. 25 g) collected from each clinically healthy dog on site. A total of 168 samples were collected. Weekly visits were made to the CCABA for 3 mo. On each visit, a post mortem feces sample (approx. 25 g) was collected from twelve randomly chosen clinically healthy dogs. A total of 144 samples were collected. Samples were transported to the laboratory under refrigeration and processed the day of collection. Data were recorded on animal sex and age (based on dental evaluation) and sample consistency (firm/diarrheal). For the farm dogs, data were also recorded on food type (dry balanced/prepared at home/combined), water access (exclusively for dog(s)/shared with other species), and any preventive medicine program (vaccination/deworming).

Parasitotic diagnosis

Samples were processed according to Castillo et al(13) Briefly, a 10 g feces sample was diluted in oxygenated water (1:1). Six fecal smears were made on a slide, dried for 24 h at room temperature and stained following the Kinyoun acid-alcohol staining technique. Smears were observed under a microscope (LCD Digital, LeicaÂŽ) at 100x magnification. False positive readings were minimized by classifying a sample as positive when â&#x2030;Ľ5 Cryptosporidium spp. oocysts were identified in at least six smears (dying causes oocysts to appear as pale pink spheres).

Data analysis

Cryptosporidium spp. infection frequency in the sampled dogs was calculated based on total sample parasitosis results and characteristics of the two sampled populations. A logistic regression risk analysis was done(14), in which the dependent variable was parasitic infection condition and the independent variables were selected by the "backward step-by-step" method and a Ď&#x2021;2 test; non-significant variables were excluded (P<0.05). Odds ratios (OR) were estimated for independent variables shown to be 5

Rev Mex Cienc Pecu 2019;10(1):1-13

significant in the multivariate analysis (P<0.05). Statistical analyses were run with the Statistics Data Analysis v. 9.1 program (STATA).

Results

Overall Cryptosporidium spp. infection frequency in the sampled dogs was 20.5 % (64/312; CI95% 16-25). Frequency in urban dogs was 9 % (13/144; CI95% 5-15), and in farm dogs it was 30 % (51/168; CI95% 23-38). Infection frequency among farm dogs was highest in Jesús María municipality (58 %) and lowest in Cosío municipality (15 %) (Table 1). All the municipalities contained positive animals, whereas 70 % of the farms did (21/30). The average number of dogs per farm was 5.6, and density was 2 to 12 dogs.

Rev Mex Cienc Pecu 2019;10(1):1-13

Table 1: Cryptosporidium spp. infection distribution in farm dogs in ten municipalities in the state of Aguascalientes, Mexico Municipality/Farm Aguascalientes 1 2 3 Asientos 1 2 3 Cosío 1 2 3 El Llano 1 2 3 Jesús María 1 2 3 Pabellón de Arteaga 1 2 3 Rincón de Romos 1 2 3 San Fco. de los Romo 1 2 3 San José de Gracia 1 2 3 Tepezalá 1 2 3 Total

Positives

18 9 5 4 14 7 2 5 13 2 6 5 31 12 10 9 19 2 8 9 22 11 6 5 11 5 4 2 16 5 4 7 12 4 4 4 12 3 5 4 168

4 4 3 2 1 2 1 1 12 6 4 2 11 2 6 3 4 2 2 0 4 4 4 1 3 2 2 5 3 2 51

* CI: 95% Confidence interval.

Frequency (%)

CI 95%*

7-48

5-51

2-46

22-57

33-78

6-41

12-68

8-52

3-49

16-71

23-38

Rev Mex Cienc Pecu 2019;10(1):1-13

Most of the studied dogs were young (â&#x2030;¤18 mo of age), and infection frequency was highest in this age group (Table 2). Farm dogs exhibited a higher frequency (37 %) than urban dogs (12 %). In both populations, females were more frequently positive than males. Feces samples described as diarrheal had a higher frequency (31 %) than those described as firm (11 %). In farm dogs, frequency by food type was 22 % for dry food, 32 % for prepared food and 36% for a combination of these. Farm dogs that had their own water had a higher frequency than those that shared water with other animals. Frequency was nearly the same in vaccinated (usually against rabies) and unvaccinated dogs, but those that had not been dewormed exhibited a higher frequency.

Table 2: Cryptosporidium spp. frequency as diagnosed by microscope in dogs in the state of Aguascalientes, Mexico, by different variables

Variable

Urban dogs n Posit. %

Farms dogs n Posit. %

Age: 0-6 mo 7-18 mo 19-66 mo > 66 mo

58 41 28 17

7 3 1 2

12 7 3 12

67 49 20 32

25 15 3 8

37 31 15 25

125 90 48 49

32 18 4 10

26 20 8 20

Sex: Male Female

74 70

6 7

8 10

78 90

20 31

25.6 34

152 160

24 40

16 25

Feces texture: Firm Diarrheal

90 54

5 8

5 15

77 91

14 37

18 41

167 145

19 45

11 31

37 28 103

8 10 33

22 36 32

37 28 103

8 10 33

22 36 32

98 70

42 9

43 13

98 70

42 9

43 13

121 47 37 131

36 15 7 44

30 32 19 33

121 47 37 131

36 15 7 44

30 32 19 33

Food: Dry Prepared Combined

Water: Exclusive Shared

Preventive care: Vaccination No vaccination Deparasitization No deparasitization

Total Posit. %

na: not applicable.

Risk analysis identified the variable of diarrheal feces in urban dogs (OR, 3.2; CI95% 1.06-9.79 P<0.03) and farm dogs (OR, 2.7; CI95% 1.36-5.49 P<0.001) as related to

Rev Mex Cienc Pecu 2019;10(1):1-13

infection frequency diagnosed by parasitological analysis. No other analyzed variable exhibited a significant association.

Discussion

The prevalence of Cryptosporidium infection in dogs, be they pets, street dogs or farm dogs, ranges from 1 to 45 %, and is higher in puppies than adults(9-11,15-21). Results can vary in response to characteristics such as experimental design, diagnostic test, geographic region and environmental conditions. The 9 % infection frequency observed here in urban dogs is relatively low, and similar to the 11.5 % reported in pet dogs in Mexico City as determined by FRECU Gum Infection(22). The farm dogs exhibited a frequency of 30 %, which is significantly higher than among the urban dogs. In addition, infected farm dogs were widely distributed among the sampled farms, highlighting this parasiteâ&#x20AC;&#x2122;s cosmopolitan nature. Higher frequencies have been previously reported in street dogs and pet dogs in rural communities than in urban dogs(9). The present study is the first report of Cryptosporidium spp. in dogs at dairy farms. Of note is that cryptosporidiosis is widely distributed in dairy cattle in Aguascalientes, with a significant presence in replacement heifers (40 â&#x20AC;&#x201C; 67 %). The only species identified to date is C. parvum(13,23). In the present results, Cryptosporidium spp. infection frequency was highest in young dogs; this agrees with previous studies(15,22). Infection prevalence tends to decrease in naturally infected puppies as they grow(24). However, age is not considered a risk factor for contracting this parasite(25,26), which is also supported by the present data. Sex had no effect on frequency in the studied populations, although females exhibited higher values than males. The same has been reported elsewhere(25, 27, 28). Presence of diarrhea is considered the principal clinical sign if canine cryptosporidiosis(8). The present results support this in that dogs with diarrheal feces had a higher infection frequency than those with firm feces; it was identified as a risk factor in both urban dogs (OR 3.2) and farm dogs (OR 2.7). Samples came from clinically healthy animals, that is, asymptomatic carriers. Dogs with diarrhea are known to excrete more oocysts than those lacking clinical signs(29), making it a recognized risk factor(15,25,27). Asymptomatic dogs or those with sporadic episodes of diarrhea are the source of soil and water contamination in the environments they inhabit. Because oocysts are highly environmentally resist, they

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represent a significant risk of transmission to humans, and domestic and wild animals. This is the case in rural, agricultural, urban and peridomestic environments(1). Food type in farm dogs was not identified as a risk factor, which has been reported previously(25). However, the studied farm dogs roamed freely about the dairy facilities, providing them easy access to fetuses and placental waste, and allowing them to sporadically hunt birds and rodents. Drinking water is an effective vehicle for Cryptosporidium transmission, especially in humans(1). In the present study, only the use of the recipient form which the dogs drank water was assessed, and this variable was not identified as a risk factor. Another study in which drinking water source was assessed did not find it to be a risk factor(25). Application of a vaccination regime in the farm dogs had no apparent effect on infection frequency since vaccinated and unvaccinated dogs exhibited similar frequencies. In contrast, farm dogs that had received deparasitization treatment had a lower frequency than those that had not received it; nonetheless, this variable was not identified as a risk or a protection factor. The present data suggest that the prevailing environment at dairy farms favors transmission and maintenance of Cryptosporidium spp. infection. Contributing factors include dog density at each farm, their high mobility and their interaction with other domestic and wild animals. The studied urban dogs were largely strays but faced a distinct environmental situation and were therefore less exposed to possible Cryptosporidium spp. infection.

Conclusions and implications

Cryptosporidium spp. infection was identified in both urban and dairy farm dogs. Infection frequency was relatively low in the urban dogs, but high among the farm dogs. Infection distribution was broad throughout the sampled rural areas, reflecting this protozoanâ&#x20AC;&#x2122;s high infective capacity. Further research is needed on the possible effects of the dog-cattle relationship on this diseaseâ&#x20AC;&#x2122;s epidemiology. Both dog populations represent a transmission risk to humans since they can be carriers of both C. canis and C. parvum.

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Acknowledgements

Thanks are due the personnel of the CCABA in Aguascalientes municipality, and the ranchers who participated in the study. The research reported here forms part of a project financed by the Tecnológico Nacional de México.

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Fayer R. General Biology. In: Fayer R, Xiao L. editors. Cryptosporidium and Cryptosporidiosis. 2nd ed., Boca Raton, FL: CRC Press; 2008:1-35.

Robertson ID, Irwin PJ, Lymbery AJ, Thompson RCA. The role of companion animals in the emergence of parasitic zoonoses. Int J Parasitol 2000;(30):1369-1377.

Xiao L, Morgan UM, Limor J, Escalante A, Arrowood M, Shulaw W, et al. Genetic diversity within Cryptosporidium parvum and related Cryptosporidium species. Appl Environ Microbiol 1999;(65):3386-3391.

Fayer R, Trout JM, Xiao L, Morgan UM, Lal AA, Dubey JP. Cryptosporidium canis n. sp. from domestic dogs. J Parasitol 2001;(87):1415-1422.

Hajdusek O, Ditrich O, Slapeta J. Molecular identification of Cryptosporidium spp. in animal and human hosts from the Czech Republic. Vet Parasitol 2004;(122):183192.

Lupo PJ. Cryptosporidium muris in a Texas canine population. Am J Trop Med Hyg 2008;(78):917-921.

Irwin PJ. Companion animal parasitology: a clinical perspective. Int J Parasitol 2002;(32):581-593.

Santin M. Clinical and subclinical infections with Cryptosporidium in animals. N Z Vet J 2013;(61):1-10.

Dubná S, Langrová I, Nápravník J, Jankovská I, Vadlejch J, Pekár S, et al. The prevalence of intestinal parasites in dogs from Prague, rural areas, and shelters of the Czech Republic. Vet Parasitol 2007;(145):120-128.

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10. Jian F, Qi M, He X, Wang R, Zhang S, Dong H, et al. Occurrence and molecular characterization of Cryptosporodium in dogs in Henan Province, China. BMC Vet Res 2014;(10):26. 11. Ferreira JIGS, Pena HFJ, Azevedo SS, Labruna MB, Gennari SM. Occurrences of gastrointestinal parasites in fecal samples from domestic dogs in São Paulo, Brazil. Braz J Vet Parasitol 2016;(25):435-440. 12. INEGI. Instituto Nacional de Estadística, Geografía e Informática. Anuario Estadístico del Estado de Aguascalientes. México. 2011. 13. Castillo GC, Cruz-Vázquez C, López RR, Sánchez GM, Rosario CR, Vitela MI, et al. Frecuencia e identificación molecular de Cryptosporidium spp en becerras lactantes mantenidas en confinamiento en Aguascalientes, México. Téc Pecu Méx 2009;(47):425-434. 14. Hosmer DW, Lemeshow S, Sturdivant RX. Applied logistic regression. 3th ed. New Jersey, USA: Wiley; 2013. 15. Causapé AC, Quilez J, Sanchez-Acedo C, Del Cacho E. Prevalence of intestinal parasites, including Cryptosporidium parvum, in dogs in Zaragoza city, Spain. Vet Parasitol 1996;(67):161-167. 16. Abe N, Sawano Y, Yamada K, Kimata I, Iseki, M. Cryptosporidium infection in dogs in Osaka, Japan. Vet Parasitol 2002;(108):185-193. 17. Hackett T, Lappin MR. Prevalence of enteric pathogens in dogs of north-central Colorado. J Am Anim Hosp Assoc 2003;(39):52-56. 18. Ederli BB, Rodrigues MFG, Carvalho CB. Oocistos do gênero Cryptosporidium em cães domiciliados na Cidade de Campos dos Goytacazes, Estado do Rio de Janeiro. Rev Bras Parasitol Vet 2005;(14):129-131. 19. Shukla R, Giraldo P, Kraliz A, Finnigan M, AL Sanchez. Cryptosporidium spp. and other zoonotic enteric parasites in a sample of domestic dogs and cats in the Niagara region of Ontario. Can Vet J 2006;(47):1179-1184. 20. Katagiri A, Oliveira-Sequeira TC. Prevalence of dog intestinal parasites and risk perception of zoonotic infection by dog owners in Sao Paulo State, Brazil. Zoonoses Public Health 2008;(55):406-413. 21. Overgaauw PA, Zutphen L, Hoek D, Yaya FO, Roelfsema J, Pinelli E, et al. Zoonotic parasites in fecal samples and fur from dogs and cats in The Netherlands. Vet Parasitol 2009;(163):115-122.

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22. Martínez-Barbosa I, Gutiérrez M, Ruiz LA, Fernández AM, Gutiérrez EM, Aguilar JM, et al. Detección de Cryptosporidium spp y otros parásitos zoonoticos entéricos en perros domiciliados de la Ciudad de México. Arch Med Vet 2015;(47):347-353. 23. García-Romo D, Cruz-Vázquez C, Quezada-Tristán T, Silva-Peña E, ValdiviaFlores A, Vázquez-Flores S, et al. Prevalencia y factores de riesgo asociados a la infección por Cryptosporidium spp. en becerras lactantes en Aguascalientes, México. Vet Mex OA. 2014;(1):1 julio-septiembre. 24. Hamnes IS, Gjerde BK, Robertson LJ. A longitudinal study on the occurrence of Cryptosporidium and Giardia in dogs during their first year of life. Acta Vet Scand 2007;(49):22. 25. Ederli BB, Ederli NB, Oliveira FCR, Quirino CR, Carvalho C. Fatores de risco associados á infeccçãon por Cryptosporidium spp, em cäes domiciliados na cidade de Campos dos Goytacazes, estado do Rio de Janeiro, Brasil. Rev Bras Parasitol Vet 2008;(17):250-266. 26. Lallo MA, Bondan EF. Prevalência de Cryptosporidium sp. em cães de instituições da Cidade de São Paulo. Rev Saúde Púb 2006;(40):120-125. 27. Rodríguez BE, Manrique-Abril F, Pulido MM, Ospina-Díaz J. Frecuencia de Cryptosporidium spp en caninos de la ciudad de Tunja-Colombia. Rev MVZ Córdoba 2009;(14):1697-1704. 28. Mundim MJS, Rosa LAG, Hortêncio SM, Faria ESM, Rodrigues RM, Cury MC. Prevalence of Giardia duodenalis and Cryptosporodium spp. in dogs from different living conditions in Uberlândia, Brazil. Vet Parasitol 2007;(144):356-359. 29. Hill SL, Lappin MR. Cryptosporidiosis in the dog and cat. In: Bonagura J. editor. Kirk’s Current Veterinary Therapy XII, Philadephia (PA):WB Saunders; 1995:728731.

http://dx.doi.org/10.22319/rmcp.v10i1.4241 Article

Potential distribution of Musca domestica in Jesús María Municipality, Aguascalientes, Mexico, based on climate change scenarios

Antonio de Jesús Meraz Jiméneza Armando López Santosb Carlos Alberto García Munguíac Jorge Alejandro Torres Gonzáleza Alberto Margarito García Munguíaa*

Universidad Autónoma de Aguascalientes. Centro de Ciencias Agropecuarias, Jesús María, Aguascalientes, México. b

Universidad Autónoma Chapingo. Unidad Regional Universitaria de Zonas Áridas. Bermejillo, Durango, México. c

Universidad de Guanajuato. Departamento de Veterinaria y Zootecnia, DICIVA. Irapuato, Guanajuato, México.

Corresponding author: almagamu@hotmail.com

Abstract The housefly M. domestica is a primary domestic pest responsible for food decomposition, and is a vector for more than 100 pathogens in humans and animals. Climate conditions including temperature and relative humidity influence M. domestica development and prevalence. As climate change advances control programs for this species will need to adapt to evolving conditions. A development assay was done of M. domestica at different temperatures and relative humidities to estimate its current potential incidence in Jesús María Municipality, Aguascalientes, Mexico. Local climate is temperate semi-dry (BS1k) with 16 to 18 °C annual average temperature and 500 to 600 mm annual average rainfall. In a completely randomized design, six treatments involving different temperatures and relative 14

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humidities during the entire fly lifecycle were analyzed. Development conditions were ideal between 20 and 30 Â°C, conditions present in the study area between June and August. The CNRMCM5 (RCP 4.5) climate change model was used to predict extreme minimum temperatures in three time horizons: Short (2015-2039); Medium (2040-2060); and Long (2075-2090). Under the Medium and Long scenarios ideal development conditions could last as long as five months, representing a potential increase in the time M. domestica is present in the region, and in the duration of the public and animal health challenges it generates. The present results are important for planning future prevention, monitoring and control programs and strategies. Key words: Housefly, Vector, Temperature, Relative humidity, Precipitation.

Received: 02/08/2016 Accepted: 05/03/2018

Introduction The housefly Musca domestica is a synanthropic insect in close association with humans and their environment. It is present wherever humans live, but is also associated with livestock such as poultry, cattle, horses and swine(1). It is therefore a potential disease vector for various diseases among humans and for zoonoses(2). Prevention, monitoring and controlling M. domestica is vital because it is the principal domestic parasite responsible for food decomposition and a vector for more than 100 pathogens(3). It can also propagate approximately thirty bacterial and protozoan diseases, although M. domestica can thrive without causing infection(4). Controlling M. domestica is costly and ongoing; for example, an estimated 1.6 million dollars annually is spent in the United States of America on insecticides for control of this parasite on poultry farms(5). Survival in ectotherms such as flies is limited by temperature. They often remain exposed to extreme thermal variations in their natural habitat, especially during the summer months (6). Optimum development of M. domestica occurs at about 25 Â°C(7). Environmental factors such as temperature, precipitation, relative humidity and soil type and use directly affect M. domestica population dynamics(8).

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Livestock can exacerbate M. domestica presence and persistence. In 2015 the state of Aguascalientes, Mexico, had a dairy cattle population of approximately twenty thousand head(9). Public health problems can emerge when dairy cattle production is in proximity to densely populated urban areas; for example, in livestock regions such as the Comarca Lagunera, in the states of Coahuila and Durango, and Jesús María Municipality in the state of Aguascalientes. Musca domestica can then effectively transmit myriad diseases from livestock to human populations, and extreme measures are required to control its propagation. The present study objective was to evaluate the effects of variations in temperature and relative humidity on M. domestica population development in Jesús María Municipality, Aguascalientes, and estimate its potential distribution under climate change scenarios based on the CNRMCM5 (RCP 4.5) model for three periods: Near (2015-2039), Middle (20452069) and Long (2075-2099).

Material and methods

Development of M. domestica was evaluated under temperature and humidity conditions similar to the study area. Jesús María Municipality, Aguascalientes, has a temperate semidry (BS1k) climate with 16 to 18 °C annual average temperature and 500 to 600 mm annual average rainfall. Fly pupae for use as progenitors were collected from the livestock area of the Agricultural Sciences Center (Centro de Ciencias Agriculturales - CCA) of the Autonomous University of Aguascalientes (Universidad Autónoma de AguascalientesUAA). These were placed in stainless steel wire cages (30 x 30 x 30 cm), covered with 100% nylon fabric and incubated at 24 ± 2 °C in the Veterinary Clinic and Greenhouse Research Laboratory of the UAA. Once emerged the flies were fed a 10% sugar water solution in which pieces of cotton were saturated. The substrate for oviposition and larvae feeding was a mixture of wheat bran and water (70 %) or wheat bran, powdered milk and water (30 %). The resulting pupae were used in the evaluation of development under different temperatures and relative humidities (RH) done at the Laboratory of Natural Resources and Agrarian Systems Analysis of the CCA at UAA. Each pupa was placed in a one-ounce polypropylene container with lid to prevent copulation between females and males. After emergence they were sexed and placed in different cages (30 x 30 x 30 cm). Females and males were removed from these cages, three of each sex placed in stainless steel cages (size 10 x 10 x 10 cm), and these covered with nylon fabric. Each cage was subjected to one of six temperature/RH treatments (Table 1). Experimental design was completely random, with three replicates per 16

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treatment. A Tukey test was used to compare the means for the larvae count, pupae count, and fly emergence per cage variables (α= 0.005). Statistical analyses were run using the STATISTICA® ver. 13 program.

Table 1: Temperature and relative humidity in M. domestica development treatments Treatments T1 T2 T3 T4 T5 T6

Temperature (°C) 27.5 ± 2.5 22.5 ± 2.5 32.5 ± 2.5 32.5 ± 2.5 35 32.5 ± 2.5

Relative humidity (%) 90 - 95 60 - 65 20 - 25 35 - 40 90 15 - 20

Data for maximum, minimum and mean temperature, as well as HR, for Jesús María municipality were acquired from the National Network of State Agroclimatological Stations (a.k.a., Agroclima)(10) of the National Institute of Forestry, Agriculture and Livestock Research (Instituto Nacional de Investigación Forestal, Agrícola y Pecuaria - INIFAP). These were analyzed considering the M. domestica development variables and the species’ possible infestation in the study area. Climate data were interpolated by the method based on inverse distance weighting (IDW), which has been described and applied previously(11,12). Geospatial processing first produced a raster image using the maximum and minimum temperatures as extreme values. The second product was an image classified based on changes in its properties in five classes associated with its distribution at the municipal level. The minimum temperature raster images were built based on the model created by the National Center for Meteorological Research (Centre National de Recherche Météorologique - CNRM), under the nomenclature CNRMCM5 (RCO 4.5)(13), which formed part of the IPCC’s 5th Climate Change Assessment Report(14). After testing and rescaling from 0.5° x 0.5° (55 x 55 km, approximately) to 30" x 30" (926 x 926 m) for application in the Mexico, southern United States and Caribbean region, this and other models (GDFL-CM3, HADGEM2-ES, etc.) were downloaded from the webpage of the Atmospheric and Environmental Sciences Data Unit (Unidad de Informática para las Ciencias Atmosféricas y Ambientales - UNIATMOS) of the Atmospheric Sciences Center of the National Autonomous University of Mexico (Universidad Nacional Autónoma de México UNAM)(15). Using different modules of the ARCMAP 10.2.2® program (ESRI, Redlands,

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CA), the CNRMCM5 model was processed for three time horizons: Short (2015-2039), Medium (2045-2069) and Long (2075-2099).

Results and discussion

Larvae development

Comparison of median number of larvae per treatment showed treatment one (T1) to have the highest number (161 larvae per cage) (Figure 1). Treatments T3, T4 and T6 produced no larvae due to temperature variability, since larval development depends on there being at least 8 °C(16,17). Musca domestica larvae prefer to develop at 35 °C and high humidity, but when fully developed prefer 15 to 20 °C with low HR, and do not withstand temperatures above 45 °C(18). In another study fly larva distribution was higher in manure at temperatures from 17 to 35 °C(19). Figure 1: Comparison of median M. domestica larvae count per treatment 180

160

Larvae Count

140

120 100 C

80 60 40 20

0 T1

Treatments *Different letters on different bars indicate significant difference (P≤0.01).

Treatment T5 had the highest larvae count with 122 larvae per cage. The discrepancy between these treatments was a lower initial temperature in T1 (25 to 30 °C for T1 vs 35 °C for T5)

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and constant RH in T5. Relative humidity (RH) determines larvae survival, since insufficient RH will dry them out, while excess moisture can cause them to drown(20).

Larvae to pupae development

Larvae were not present in treatments T3, T4 and T6 because initial conditions (>30 °C and low RH) did not allow for egg development. Maximum temperature for M. domestica oviposition is 25 to 30 °C, and eggs must remain moist or they will not hatch(21). Larvae did hatch in treatments T1, T2 and T5. Transition from larva to pupa was better in T1 than in the other treatments: an average of 115 pupae survived of the 160 larvae per cage. Treatment T2 had 62 pupae develop from 72 larvae per cage (Figure 2), and in T5 12 pupae survived from 122 larvae. The very low development rate in T5 and slightly lower rate in T1 may be due to the 90 % RH in both. In a previous study maximum larva mortality occurred at 100 % RH and temperatures higher than 30 °C(22). Pupae tolerate less moisture than larvae and can tolerate temperatures from 35 to 40 °C, but only for a minimum period of 3 to 4 d(18). In the present study the pupae remained for sixteen days at temperatures as high as 35 °C. Temperature clearly affects survival in different stages of M. domestica. In one study it was found that at 48 °C for 15 min all lifecycle stages died, at 37 °C all stages survived for just over 4 h, and at 42 °C adults died after approximately one hour; pupae were found to resist temperatures of 44 to 46 °C(23). Exposure periods in this study were relatively short (a few hours at most), in contrast the periods used in the present study for the different treatments were until completion of the fly lifecycle, that is, from 19 to 22 d. An analysis of variance between treatments comparing larva to pupa transformation rates found T1 (74 %) and T2 (86 %) to have the best rates.

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200

*Pupae Count (R)

150 100

C T6

80 60

D *BD

0 T1

Larvae Count(L)

Treatments

*BD

Larva to Pupa (%)

140 120 100 80 60 40 20 0

Larvae Count

Pupae Count

Figure 2: Comparison of median M. domestica pupae count per treatment

*B 0

Treatments

*Different letters on different bars indicate significant difference (P≤0.01).

Pupa to adult transition

Treatment 1 (T1) had the highest adult emergence per cage (n= 85), followed by T2 (n= 54) (Figure 3). This suggests that the ideal temperature for M. domestica development in the present study was 20 to 30 °C. This agrees with a previous study in which fly density was highest at an average temperature of 20 to 25 ºC and no flies were present at temperatures higher than 45 °C or lower than 10 °C(17). In another similar study the highest adult fly counts were observed at temperatures between 25 and 35 ºC(24).

120

90 80 100 *A *Adult Fly Count (R) 70 B 80 60 B 50 60 40 40 30 20 C 20 *B C *B C *B C *B 10 C C C C 0 0 T1 T2 T3 T4 T5 T6 T1 T2 letters T3on different T4 T5 indicate T6 *Different bars significant difference (P≤0.01). *A

Pupae Count (L)

Treatments

Pupa to Adult (%)

90 80 70 60 50 40 30 20 10 0

Pupae Count

Adult Fly Count

Figure 3: Comparison of median M. domestica adult fly count per treatment

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Treatment 2 (T2) had the highest pupa to adult transformation rate (84 %), followed by T1 (74 %). The 62.5 ± 2.5% RH used in T2 is near the 65 to 75 % RH reported as optimal for fly development(22), which is why this treatment exhibited a more consistent development rate among the different stages. In T5, counts for both pupae (n= 11) and adults (n= 1) were minimal (Figure 3).

Larva to adult transition

Larva to adult development was highest in T2 (73 %), followed by T1 (55 %)(Figure 4).

180 160 140 120 100 80 60 40 20 0

Larvae Count (L) *Larvae to Adult (%) (R)

B *A C

D T1

*B T3

D *B T4

*B T5

90 80 70 60 50 40 30 20 10 0

Larva to Adult (%)

Larvae Count

Figure 4: Musca domestica larva counts and larva to adult transition rates

Treatments

*Different letters on different bars indicate significant difference (P≤0.01).

Role of temperature and relative humidity in M. domestica development An analysis was done incorporating temperature and RH data for Jesús María municipality in 2015, M. domestica frequency, and the experimental results. Population increase was highest in June (extreme minimum= 11.8 °C) to August (extreme minimum= 10 °C)(Figure 5). The latter temperature is the lower limit for egg hatching and at which adults can barely 21

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fly(17); it can be inferred that little copulation occurs. Oviposition generally does not happen below 15 °C(18), which is probably why M. domestica populations are lower in April and May than in warmer months. This data agrees with reports of higher activity in this species at milder temperatures (30 to 33 °C) and low RH, and lower activity at very high temperatures and high RH(17,25). In another study in which temperature remained nearly constant year round fly abundance was only influenced by changes in rainfall and RH(24). A study done in horse farms also found that temperature and RH affected fly populations, causing them to grow in the spring when temperatures rise and decrease in autumn when temperatures fall(26). Temperature is known to influence daytime M. domestica physical activity. As temperature increases (10 to 30-35 °C) during the day so does activity, and consequently pathogen dispersion and transmission, but when it surpasses 35 °C activity decreases notably(27). This species therefore has a wide temperature range within which to function, which is important information when designing disease outbreak prevention measures.

Figure 5: Temperature and relative humidity in Jesús María Municipality in 2015 72

Relative humidity (L) Maximum (R)

Minimum (R)

Median (R)

Extreme minimum (R)

62 20

60 58

56 54

52 50

48 46

44 42

-5 1

Month

Source: Red Nacional de Estaciones Estatales Agroclimatológicas, Agroclima (INIFAP).

Temperature °C

Relative humidity %

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Minimum temperature projection model

Prediction of future extreme minimum temperatures in JesĂşs MarĂa Municipality can indicate when M. domestica could have ideal development conditions. The experimental results demonstrated that temperature is the most significant parameter influencing mortality in this species(22), while RH was important in regulating the viability of different stages within a moderate temperature range. In the Short time horizon model, current conditions are predicted to remain relatively unchanged and M. domestica development will peak from June to August. Under the Medium and Long horizon models favorable development conditions will exist for a total of five months, from May to September (Figure 6). These projections will also depend on other factors such as wind, food availability, light and RH in the region. If these scenarios hold true, M. domestica populations will remain stable until 2039, but could then increase due to the longer periods apt for development. A similar prediction has been made for the United Kingdom, for which climate change scenarios predict increases of up to 244 % in the fly population in the summer months by 2080(28).

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Figure 6: Extreme minimum temperatures in Jesús María Municipality in 2015, and its projection over three time horizons: Short, 2015-2039; Medium, 2045-2069; and Long, 2075-2099 14

Short

Medium

Long

Inifap 2015

Extreme minimum temperature °C

0 1 -2

Month

Source: (15) and Red Nacional de Estaciones Estatales Agroclimatológicas, Agroclima INIFAP.

This predictive information can help in planning control programs during more favorable fly development periods. Reducing M. domestica proliferation can help to avoid negative effects on livestock farms, reduce food contamination in the food industry and lower disease occurrence in human populations. The species’ high reproductive potential requires effective and timely control practices to protect human and animal health(29). Control measures in developed countries have been established, especially for agriculture and the dairy industry, control agents have been formulated, and they are applied in both urban and rural areas(1). If insecticide is to be used, the present data can help to program application schedules and efficacy. It must be considered that these projections do not take into account biotic factors such as predators and parasitoids that could arise in coming years(28). Prediction of temperature ranges in Jesús María Municipality over the Short horizon shows that approximately 100,000 inhabitants in the municipality’s 235 settlements(30) could be affected by increased M. domestica populations (Figure 7). The problem could be most acute 24

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in the map’s red-toned areas where most of the population is concentrated (219 villages; 99,046 inhabitants). Musca domestica is often associated with livestock and household waste disposal facilities, since accumulation of organic matter provides appropriate breeding conditions(28). It also prefers to feed on decomposing vegetal and animal matter, which puts it in contact with the pathogenic organisms present in human garbage and animal waste, making it a disease vector for humans and animals(31).

Figure 7: Distribution of average annual minimum temperature in Short horizon (20152039) in Jesús María Municipality)

Conclusions and implications

Under the experimental conditions M. domestica development was ideal between 20 and 30 °C, a temperature range that currently occurs in the study area for three months a year (June to August). Predictive analysis of regional climate suggested that this species will be favored by longer periods of ideal temperatures in the Medium and Long horizons; these will probably stretch over the five months from May to September. Longer periods with apt conditions for M. domestica development could exacerbate contamination problems in livestock and agricultural production and the food industry, and promote the spread of 25

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diseases among animal and human populations. Almost all the populated areas in Jesús María Municipality will experience this climate change, highlighting the need to consider it when designing monitoring and control programs.

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Malik A, Singh N, Satya S. House fly (Musca domestica): A review of control strategies for a challenging pest. J Env Sci & Health, Part B 2007;42(4):453-469. doi: http://dx.doi.org/10.1080/03601230701316481.

Mehrabi MR, Zoghimofrad I, Mazinani M, Akbarzadeh, A, Rahimi A. A study of the effect of Bacillus thuringiensis serotype H14 (subspecies israelensis) delta endotoxin on Musca larva. Turk J Med Sci 2015;45(4):794-799. doi: http://dx.doi.org/10.3906/sag1406-91.

Burgess ER, King BH. Compatibility of the parasitoid Wasp Spalangia endius (Hymenoptera: Pteromalidae) and insecticides against Musca domestica (Diptera: Muscidae) as evaluated by a new index. J Econ Entomol 2015;108(3):986-992. doi: http://dx.doi.org/10.1093/jee/tov104.

Kumar P, Mishra S, Malik A, Satya S. Insecticidal evaluation of essential oils of Citrus sinensis L. (Myrtales: Myrtaceae) against housefly Musca domestica L. (Diptera: Muscidae). Parasitol Res 2012;(110):1929–1936.

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17. Stafford KC. A Guide to biology, dispersal, and management of the housefly and related flies for farmers, Municipalities, and Public Health Officials. 2008 Bulletin 1013. Conn Agr Exp Sta, New Haven http://www.ct.gov/caes/lib/caes/documents/publications/ bulletins/b1013.pdf. Consultado 5 Nov, 2015. 18. WHO. World Health Organization. The housefly: Training and information guide. Vector control series Geneva; 1991. http://www.who.int/iris/handle/10665/58637. Consultado 9 Oct, 2015. 19. Stanfford KC, Bay DE. Dispersion pattern and association of housefly, Musca domestica (Diptera: Muscidae), larvae and both sexes of Macrocheles muscaedomesticae (Acari: Macrochelidae) in response to poultry manure moisture, temperature, and accumulation. Environ Entomol 1987;16(1):159-164. doi: http://dx.doi.org/10.1093/ee/16.1.159. 20. Feldmeyer B, Kozielska M, Kuijper B, Weissing FJ, Beukeboom LW, Pen I. Climatic variation and the geographical distribution of sex-determining mechanisms in the housefly. Evol Ecol Res 2008;10:797–809. 21. Capinera JL. House fly, Musca domestica L. (Diptera: Muscidae). In: Capirera JL editor. Encyclopedia of entomology. 2nd ed. Springer; 2008:1877–1880. doi: 10.1007/978-14020-6359-6. 22. Mishra S, Kumar P, Malik A. Effect of temperature and humidity on pathogenicity of native Beauveria bassiana isolate against Musca domestica L. J Parasit Dis 2015;39(4):697-704. doi: http://dx.doi.org/10.1007/s12639-013-0408-0. 23. Tiwari PK, Archana J, Mohan DRK. Thermotolerance and heat shock response in Musca domestica. Curr Sci 1997;72(7):501-506. 24. Bong LJ, Zairi J. Temporal changes in the abundance of Musca domestica Linn (Diptera: Muscidae) in poultry farms in Penang, Malaysia. Trop Biomed 2009;26(2):140–148. 25. Dakshinamurty S. The common House-fly, Musca domestica, L., and its behaviour to temperature and humidity. Bull Entomol Res 1948;(39):339-357. doi: https://doi.org/10.1017/S000748530002246X. 26. Machtinger TE, Geden JCh, Kaufman EP, House MA. Use of pupal parasitoids as biological control agents of filth flies on equine facilities. J Integr Pest Manage 2015;6(1):1-16. doi: http://dx.doi.org/10.1093/jipm/pmv015.

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27. Schou TM, Faurby S, Kjærsgaard A, Pertoldi C, Loeschcke V, Hald B, Bahrndorff S. Temperature and population density effects on locomotor activity of Musca domestica (Diptera: Muscidae). Environ Entomol 2013;42(6):1322-1328. doi: http://dx.doi.org/10.1603/EN13039. 28. Goulson D, Derwent lC, Hanley ME, Dunn DW, Abolins SR. Predicting calyptrate fly populations from the weather, and probable consequences of climate change. J Appl Ecol 2005;42(5):795-804. doi: http://dx.doi.org/10.1111/j.1365-2664.2005.01078.x. 29. Selem GS, El-Sheikh EA. Toxicity and biochemical effects of Neem Azal T/S, willow (Salix aegyptiaca L.) and Chasteberry (Vitex agnus-castus L.) on housefly, Musca domestica L. (Diptra: Muscidae). J Biopest 2015;8(1):37-44. ISSN: 0974-391X. 30. INEGI. Instituto Nacional de Estadística y Geografía. Vectorial de localidades amanzanadas y números exteriores, rurales, cierre de planeación del censo de población y vivienda. Jesús María, Aguascalientes. México. 2010. 31. Butler JF, Garcia-Maruniak A, Meek F, Maruniak JE. Wild Florida house flies (Musca domestica) as carriers of pathogenic bacteria. Fla Entomol 2010;93(2):218-223. doi: http://dx.doi.org/10.1653/024.093.0211.

http://dx.doi.org/10.22319/rmcp.v10i1.4597 Article

Helminthiasis control in calves raised in a hot Semi-arid area

Ludmilla de Fátima Leal Pereiraa Eduardo Robson Duartea* Gabriela Almeida Bastosa Viviane de Oliveira Vasconcelosb Evely Giovanna Leite Costaa Laydiane de Jesus Mendesa Idael Matheus Góes Lopesa Iara Maria Franca Reisa

Universidade Federal de Minas Gerais, Instituto de Ciências Agrárias, Avenida Universitária, 1000, Tel.: + 55 38-2101-7707; Fax: + 55 38 2101-7703. Bairro Universitário, Montes Claros, Minas Gerais 39400-006, Brasil. b

Universidade Federal Estadual de Montes Claros. Montes Claros, Minas Gerais, Brasil.

* Corresponding author: duartevet@hotmail.com

Abstract: This study aimed to characterize the helminthiasis and anthelminthic effectiveness in calf herds raised in a hot semi-arid area. Sixty (60) cattle farms from the northern area of Minas Gerais, Brazilian sertão, were categorized by semi-structured questionnaires. It was also performed the fecal egg counts (FEC) reduction test to analyze the profile of anthelminthic resistance in eight herds. The study selected groups of at least 10 homogeneous calves with FEC ≥ 150 per treatment. After 12 h of fast, calf groups were treated with albendazole, levamisole, ivermectin, doramectin or abamectin, except the

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control groups (untreated). It was collected feces before treatments and 14 d later larvae genera of nematodes were identified after coproculture. Extensive grazing was the predominant creation system for beef calves, deworming was employed every 6 mo in 64 % of the farms and macrocyclic lactones was the most frequently used anthelminthic group. The anthelminthic efficacy varied from 62 to 98.9 %. The resistance profile to ivermectin, levaminosole, albendazole and (or) doramectin verified in this research is alarming as the genus Haemonchus was the most frequent one before and after the treatments. It was detected variations in the creation systems, in control practices and in anthelminthic susceptibility profiles between herds. Therefore, this work emphasize the importance of using strategic control with FEC reduction test for choice of anthelminthic and the encouragement of practices of alternative control. Key words: Cattle, Anthelminthic resistance, Nematodes, Parasites, Strategic control.

Received: 15/08/2017 Accepted: 30/03/2018

Introduction

Cattle production represents an important economic activity in tropical and subtropical areas(1) and it is the main source of income for a large group of the rural population (2). However, diseases such as gastrointestinal helminthiasis can influence the development of calves, increasing production costs(3,4). Gastrointestinal nematodes (GN) are responsible for severe harm in young animals and in primiparous females, promoting reduction in development, low productivity, economic losses, and, in extreme cases, increasing the mortality rate in highly infected calves(3,5,6). The synthetic anthelminthics (AH) benzimidazoles (BZ), macrocyclic lactones (ML) and imidazothiazole (IMZ) have been intensively used for the control of bovine GN(7,8). However, inappropriate usage, under dosing, wrong diagnosis, and the lack of knowledge about epidemiology have contributed to the selection of resistant GN(4,9). Therefore, efficacy tests of these products must be performed on the farms at least once a year, to replace AH classes with low efficiencies(4,10). Compared to small ruminants, 31

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only a few researches have investigated the occurrence of AH resistance of cattle GN in tropical areas, so the number of cases might be considerably underestimated(11). Reports of AH multi-resistance described bovine herds that were raised in different continents(4,12). However, little is known about the susceptibility profile to AH, epidemiology and the control management of bovine helminthiasis in regions with hot semi-arid climate. This study characterized the control of gastrointestinal nematodes and AH effectiveness in calves raised in the northern of the Minas Gerais State, Brazil.

Material and methods

Study area and cattle farms investigated

It was applied questionnaires in 59 farms obtaining information about management, infrastructure, use of AH, and measures employed to GN control. It was conducted the study during dry seasons (April to September of 2013-2015) in farms located in the northern of Minas Gerais State, Brazilian sertão (Table 1 and Figure 1). During these periods the monthly average rainfall, humidity and temperature were respectively 17.14 mm, 57.57 % and 20.82 ºC, respectively (5o Distrito, Instituto Nacional de Metereologia, Brazil). This area’s climate is characterized as hot semi-arid (BSh) according to the Köppen-Geiger climate classification, warm with a short rainy season (summer) and a long drought (winter)(13).

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Table 1: Distribution and geographical characterization of cattle herds evaluated in the northern of Minas Gerais, Brazil Number Number of of animals farms 1. Capitão Enéas 54 4 2. Claro dos Poções 1 3. Coração de Jesus 4 4. Engenheiro Navarro 30 1 5. Francisco Dumont 3 6. Francisco Sá 6 7. Ibiaí 1 8. Jaíba 1 9. Janaúba 1 10. Januária 2 11. Jequitaí 44 2 12. Juramento 1 13. Lagoa dos Patos 1 14. Matias Cardoso 1 15. Mirabela 1 16. Montes Claros 108 19 17. Pedras de Maria da Cruz 1 18. São João da Lagoa 59 3 19. São João da Ponte 3 20. São João do Pacuí 1 21. Varzelândia 1 22. Verdelândia 1 Total 295 59 Cities

Latitude

Longitude

-16º19’28” -17º04’47” -16º41’47” -17°16’47” -17°31’33” -16°47’61” -16º51’40” -15º20’18” -15º48’09” -15º29’17” -17º14’08” -16º84’81” -16º59’00” -14º51’17” -16º15’46” -16°73’50” -15°60’58” -16º51’11” -15º55’45” -15º32’31” -15°70’17” -15º35’21”

-43º42’38” -44º12’31” -44º21’54” -43°57’00” -44°23’42” -43°48’86” -44º54’52” -43º40’28” -43º18’32” -44º21’42” -44º26’44” -43º58’67” -44º34’56” -43º55’19” -44º09’52” -43°86’22” -44°39’19” -44º21’07” -44º00’28” -44º30’58” -44°02’72” -43º36’10”

Latitude and Longitude of Brazilian cities, available at: <http://www.apolo11.com/latlon.php?uf=mg>. Accessed on: August 7th, 2014.

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Figure 1: Geographical distribution of the cities of the calf herds evaluated in the northern of Minas Gerais, Brazil. The numbers represent the cities according to Table 1.

Among the evaluated herds, it was selected five farms to perform the efficacy tests. Besides the geographic location, we chose cutting herds which had not received AH in the last 2 mo. The groups were homogeneous in weight, age and quantity of at least 30 calves.

Parasitological exams and anthelminthic resistance test

It was evaluated Nellore or Girolando calves of 6-14 mo old, naturally infected by GN, sampling a minimum of 10 g of faces from the rectal ampulla. The samples were identified in plastic bags and kept refrigerated to determine fecal egg counts (FEC) and for obtainment of larvae in fecal cultures. FEC was performed by the usage of saturated sodium chloride solution and a reading under a microscope by using the 10X objective into two McMaster chambers for each sample, obtaining a medium value per animal(14). Fecal egg counts were determined via 34

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the McMaster technique - 4 g of feces and a detection sensitivity of 25 (EPG)(15). For identification of the main genera present in the herds, fecal culture(16) was performed before and after the treatments, in which approximately 100 third-stage larvae for each respective treatment group were identified(17). The animals were identified, weighed and grouped in homogeneous groups of breed, age, sex and body weight (bw) and, on day one, calves were distributed according to their parasite loads (balanced) into experimental groups, containing at least ten animals per treatment. The Ethics Committee on Animal Experiments of the Federal University of Minas Gerais approved all procedures adopted under the protocol 42/2008. Fecal egg count reduction test (FECRT) was performed as it is recommended by the World Association for the Advancement of Veterinary Parasitology, to diagnose AH resistance(18). The inclusion criteria for the selection of the test of AH efficacies were: (i) herds with a population of homogeneous calves, (ii) calves not dewormed during 60 days prior to the study and (iii) herds with calves excreting more than 150 eggs per gram (EPG) of feces. The major factor that limited the number of herds evaluated was the lack of homogeneous animals excreting more than 150 EPG. The AH choice for each farm varied according to its historical control, and the number of products tested depended on the availability of animals with infections > 150 EPG. Prior to the treatment, animals were weighed individually for the correct administration of AH doses. Therefore, variability was avoided among the doses used for treatments. The AHs evaluated were albendazole (10 mg/kg bw), levamisole chloridrate (7.5 mg/kg bw), ivermectin, doramectin or abamectin (0.2 mg/kg bw). The products were administered subcutaneously, according to the manufacturer recommendations. Fourteen days (14) after the treatment other fecal samples were obtained for calculation of FEC and new coprocultures were performed per group, as mentioned previously, to identify the GN genera (third larval stage) involved with resistance. The AH effectiveness was estimated using the following equation(18): Efficacy = [1- (FEC average of treated group / FEC average of control group)] x 100 After FEC reduction tests, cattle farmers were instructed about parasitism control with the distribution of technical reports and information on specific parasitological examinations of each herd. Evaluation of the AH effectiveness was based on the determination proposed by Common Market Group (CMG), being highly effective when it reduces more than 98 % of the EPG, effective with 90 to 98 %, moderately effective from 80 to 89 %, insufficiently active with less than 80 % reduction, and, non-registrable(19). Nematodes were considered 35

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resistant when the FEC reduction percentage was less than 95 % and the lower limit of the confidence interval was smaller than 90 %(20).

Statistical analyses

FEC data was compared by nonparametric Kruskal-Wallis or Wilcoxon tests. To compare the frequencies of nematode genera and questionnaire information it was used chi-square test. Data were evaluated at 5% significance by SAEG 9.1 statistical package software(21).

Results

Characterization of the production systems and animals

Beef cattle business was considered the most important one for 96.2 % of the farms. 3.7 % of farms produced both, beef and dairy calves. The predominant production system was extensive, representing 83.9 % of the farms. Among forage species, 49.5 % of farms cultivated Urochloa spp., 19.5 % Panicum sp., 17.53 % Andropogon gayanus, 5.84 % Cynodon sp., 3.59 % Hyparrhenia rufa, 3 % Cechrus cilliaris and 0.64 belong to Penninsetum purpureum. Rotational grazing system were used in 54.5 % of them and 68.5% of the herds parted the animals into age group. The pastures for the calves were in lower areas if compared to older animals in 83 % of investigated herds and only 55.5 % of the farms owned a maternity picket. The greater frequency breed (P<0.05) was Nellore, representing 56.1 % of beef herds. Nellore crossbred population was raised in 10.3 % of farms and Caracu, Sindhi, Guzera 36

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or Red Angus were reported in 8.4 % of farms, respectively. In 146 dairy farms, Girolando represented the single breed in the evaluated herds.

Control of helminthiasis

Macrocyclic lactones was the most frequent active principle of AH used to evaluate beef farms (P<0.01), and ivermectin was its most common component (Table 2). In 78.9 % of the farms, the practice of weighing animals was not used before treatments and dosing was calculated by body score evaluation. Just 14.54 % of them used fast before the treatments.

Table 2: Anthelminthic used in beef herds in the North of Minas Gerais, Brazil Anthelminthics class

Observation

Frequency (%)

Macrocyclic lactones Ivermectin Abamectin Doramectin Moxidectin

71* 52 6 10 3

86.4 62.9 7.4 12.3 3.7

Benzimidazoles (Albendazole)

4.9

Imidothiazoles (Levamisole)

4.9

Associations Abamectin + Ivermectin Fluazuron + Abamectin

2 1 1

2.5 1.2 1.2

Homeopathy

1.2

Total

100.00

*Class of products used with higher frequency by chi-square test P<0.05). *Frequency= number of farms using the commercial product/total number of products reported. *Number of farms is different from the total number of observations due to the use of more than one product for control of helminthiasis in the same farm.

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All cattle categories were treated in 72.7 % of herds and only the calves were treated in 26.3 % of herds. Females at peripartum were wormed in only 33.3 % of these farms. The frequency of AH treatments varied according to each farm, being that 60 % followed the vaccine schedule for control of foot-and-mouth disease virus in May and November. The use of strategic control with AH during dry season was only performed in 33.2 % of the farms and the alternation of active principles of AH products were occurring in 66.8 % of them.

Occurrence of helminthiasis

The FEC averages were low for both beef (174.0 Âą 84.8) and dairy (162.4 Âą 122) calves raised in the North of Minas Gerais and no significant differences were observed between these two animal groups (P>0.05) (Table 3). The herds 4 and 7 showed the lower FEC with beef and dairy calves, respectively (P<0.05).

Table 3: Average of fecal egg count (FEC) in calves raised in the Northern Minas Gerais and percentage of nematode genus identified before worming Farms Beef calves 1 2 3 4 5 Dairy calves 2 6 7 8 CV (%)

EPG (day 0)

Haem (%)*

Trich (%)

Oeso (%)

Coop (%)

Bunos (%)

158.87 a 138.06 ab 190.00 a 11.80 c 50.00 b

70 97 89 92 70

15 1 11

2 10 4 12

15 5

4 2

248.50 a 80.00 bc 69.50 c 145.10 ab 82.2

95 88 92 93

2 1

3 12 8 4

Haem= Haemonchus spp., Trich= Trichostrongylus spp., Oeso= Oesophagostomum spp., Coop= Cooperia spp., Bunos= Bunostomum spp., (-)= off. abc Means followed by the same letter in the column are not different (P<0.05). CV= Coefficient of variation 38

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On day 0 (zero), GN Haemonchus, Trichostrongylus, Cooperia, Oesophagostomum and Bunostomum genera infections were found. The profile of nematodes genera was not different (P>0.05) among the herds, and the most frequent GN for both calf groups and all evaluated farms was the Haemonchus spp. (P<0.01) (Table 3).

Anthelminthic efficacies

It was observed FEC reduction in all deworming calf groups if compared with untreated groups of all evaluated herds (P<0.05). Nevertheless, ivermectin and doramectin were note efficient, showing only 24.28 % at 81.63 % of FEC reduction (Table 4). High AH efficacies (>98 %) were observed to albendazole or levamisole treatments in beef calves of farm 2, but the levamisole administrated to dairy calves showed lower efficacy than with beef calves (P<0.05) (Table 5).

Table 4: Average of fecal egg count per gram of in beef calves after worming and anthelminthic efficacy (%) Herds 1 2 3

Control Albendazole % Levamisole % Ivermectin % CV% 490.0a 77.5b 84.18 90.00b 81.63 91.3 a c c b 233.3 2.77 98.81 3.57 98.47 118.75 49.09 88.2 175.0a 22.5b 87.14 47.90b 72.62 42.50b 24.28 85.3 abc

CV%= coefficient of variation. Averages followed of different letters on line differs (P<0.05).

Table 5: Average of fecal egg count per gram of in dairy calves after worming and efficacy of synthetic anthelmintics Herds Untreated Albendazole

Levamisole

Doramectin

289.5 a

57.1B

80.27

150.83 a

32.2 b

78.65

54.2 b

CV%= coefficient of variation. Averages followed of different letters on line differs (P<0.05). 39

% CV% -

87.3

64.06 90.4

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Genus of nematodes identified post-treatment

The most frequent post-treatment nematode for both treated and untreated calves was the Haemonchus genus (P<0.01). For the herd 1, the genus Trichostrongilus represents 13 % of the L3 identified from coproculture of calves treated with ivermectin (Table 6). For the herds 2 and 8, the Haemonchus spp. was also more frequent (87-93 %); despite that, L3 numbers retrieved from treated groups were insufficient for statistical analysis.

Table 6: Profile of nematode genera (%) from beef calves after anthelminthic treatment

Genera Haemonchus

Herd number 1

Herd number 3

Control Ivermec Albend

Control Ivermec Albend Levam

93*

80*

93*

83*

96*

97*

Trichostrongylus

Cooperia

Oesophagostomum

Bunostomum

*Genus with greater frequency in the Chi-square test (P<0.01). Ivermec= ivermectin, Albend= albendazole, Levam= levamisole.

Discussion

Characterization of the creation systems and animals

In Brazilian livestock, there is a predominance of the extensive system with continuous grazing. Although pasture is the main food source, it also represents the main source of L3 infection of GN(22,23). 40

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The wide distribution of cultivated pastures of the genus Urochloa sp. (Brachiaria sp.) in the evaluated tropical region can be justified by its adaptation in acid and low fertility soils in addition to considerable drought tolerance(24). Pasture management strategies are essential to the control of GN when reducing the contamination and ingestion of L3 by animals(25). Environmental conditions are important for the development and survival of free-living stages and for L3 migration along forage grasses. The morphological differences among forage species influence the development and survival of eggs and larvae due to the different microclimates that were provided by plants(26). The reserving areas for Brachiaria spp. (Urochloa spp.) grazing in late summer and grazing deferment, is a seasonal strategy to enable the excess of forage produced in late summer to be used during the dry season(27). This strategy has been widely used by cattle farmers in the North of Minas Gerais and probably it could drastically reduce the survival of NG larvae in pastures, which could have contributed to the low FEC observed in the present study. A study in SĂŁo Paulo, Brazil, indicated a significant higher overall recovery rate of Haemonchus sp. larvae from feces after depositing fecal samples on Panicum sp. If compared to Urochloa sp. and Cynodon grasses in August, February, and May(28). A research on the retrieval of Trichostrongylus colubriformis infective larvae from contaminated grass in winter and in spring compared Urochloa, Coast-cross and Aruana forage grasses. Urochloa (Brachiaria) spp. showed to be the densest forage and the effect of the higher density was dilution of L3, leading it to present the lowest concentrations of L3/kg of dry matter(26). In this study, the use of rotational grazing was found in 54.5 % of the farms, so farmersâ&#x20AC;&#x2122; attention to the number of animal units introduced for grazing is mandatory. The period to rotate the pickets should be greater than that one, which allows inactivation of eggs and larvae, reducing L3 infection(29). Age separation of animals was used in 68.5% of the herds in this study, being this strategy crucial, as young individuals are more susceptible than adult ones(5). Racial composition influences the intensity of parasitism; zebu breeds are more resistant than European breeds(2,9). In the northern region of Minas Gerais, herds with Zebu and Nellore were predominant, justifying the low FEC observed in beef herds. Studies of progeny resulting from crosses between taurine and zebu breeds have intermediate levels of susceptibility to GN(2,9). Genetic selection for resistant cattle constitutes a relevant alternative to GN control. It was observed that within each herd, few calves (5-8 %) presented higher FEC, indicating greater susceptibility to it and should not be selected to breeding programs. Bovine 41

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selection can increase the frequency of resistant animals to these parasites and should be included in strategic programs of GNs control(30,31).

Control of helminthiasis

In this investigation, the predominant the use of macrocyclic lactone group can confer higher selection pressure for resistant GN. Resistance to ivermectin was described in different regions such as Northern California, United States(32), Buenos Aires, Argentina(33) and in Brazil, more precisely, in SĂŁo Paulo and Minas Gerais(30,34). Thus the evaluation of AH susceptibility profile in each region or herd is important to ensure effective GN control(33). AH efficacy depends on chemical class alternation at proper periods(35). In this study, only 66.8 % of the farms performed rotation practices, which could favor the selection of resistant GN. Therefore, change frequency of these products should be highlighted, since it may favor the selection of multi-resistant GN(35,36). The AH must be replaced immediately by other classes when it presents effectiveness that are smaller than 80% in order to avoid the establishment of resistant populations of GN(37). All bovine categories were treated in most herds (72.7 %) of this study and it can favor the selection of resistant GN. The categories of cattle that should be prioritized for this control represent calves up to 24 mo old and females at peripartum. These young animals are significantly more susceptible to helminthes, up to 2 yr old(38,39,40). In this study, only 33.3 % of farms treated cows at peripartum. The practice is relevant for heifers in development and they have compromised immunity, making them more susceptible to endoparasitoses in pre and post-partum. Multiparous beef Zebu cows did not require deworming; these animals have showed natural resistance to GN and low potential for contamination when well managed(5,41). A different GN control should be advocated(38) according to the bovine categories and should follow climate and regional criteria that consider the profile of resistant GN populations(37). The criteria adopted for the worming period of the herds varied in this study. Most (60 %) of the properties treated all animals at the beginning (May) and at the end of the dry season (November) simultaneously with vaccination against foot-and-mouth disease. 42

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For the northern region of Minas Gerais, the treatment should also be performed in September to cover the whole period of the season. Another study in Central Brazil observed that the treatment could increase weight gain in Nellore calves during the growth phase. AH protocol in May, August and November, using AHs of long action, increased weight gains up to 34.1 kg (31.9 %) compared with animals that were not treated. Treatment during the vaccination periods against foot-andmouth disease in May and November has not increased weight gains(6). The climatic conditions of this area is the closest to the northern of Minas Gerais; despite presenting more rainfall, the strategic control proposed by(6) can also be applied to hot semi-arid areas, increasing weight gain of calves in the rearing. According to the literature, climate changes and the intensive management of farms have influenced risks of infections and transmission(42). Thus, the probability of alteration in the epidemiological of GN infections by climatic alterations, together with high frequencies of AH resistance, required adjustments to the practice of the current controls42). Future studies should also consider these climatic changes for the definitions of GN control practices in cattle herds raised in areas with hot semi-arid climates. The study of homeopathic products is not focal to this study. This control alternative should be performed carefully and scientific studies should monitor it with discussions of applicability, as well as circumscription of the correct doses(43).

Occurrence of helminthiasis in cattle herds

Cattle herds in the Northern of Minas Gerais showed lower FEC, even though this kind of contamination differed between farms. The low averages observed to farms 4, 6 and 7 can be attributed to management conditions of calves. In the beef herd 4, the calves were weighed before applying AH, annual AH change; separation by age group could be a better GN control. The calves of dairy herds 6 and 7 were raised confined in pickets without pastures; the feces were weekly collected and send for composting, and the calves were fed with silage. Thus, the survival of L3 larvae was impaired, contributing to the lowest FEC observed. The beef herds 1, 2, 3 and 5 presented similarities in GN control such as the epochs of annual deworming or during periods of higher infestation of flies and ticks. AH was used, 43

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being ivermectin the most common anthelmintic in farms with rotation of AH class and lack of strategic control. The dairy farms 6 and 7 in Montes Claros showed herds composed of Girolando crossbred with higher FEC averages if compared to 1, 2, 3 and 5. The low value detected could be related to the confinement system of calves in pickets of land without vegetation. The most frequent GN for beef and dairy herds in the area was Haemonchus spp. Frequently this genus was reported with higher prevalence in small ruminants, while the genus Cooperia sp. tends to be the most frequent with the Brazilian cattle(35,40). Haemonchus spp. represented the most common pathogenic nematode to cattle in tropical regions. In calves, it promotes reduction in the mean hematocrit values and reduced weight. The (L4) of Haemonchus is a bloodsucker in the abomasum and therefore animals infected with large numbers of larvae may present anaemia before FEC is detected in feces. The genera Trichostrongylus, Cooperia, Oesophagostomum and Bunostomum were also identified in coproculture before treatment. Infections with GNs frequently involve several different species, which can have an additive pathogenic effect on the calves(42).

Anthelminthic efficacies

Albendazole and levamisole were the most effective AH to GN from beef calves in the farm number 2, but resistant nematodes to levamisole were detected in feces of dairy calves of this same farm. The profile of resistance to ivermectin, levaminosole, albendazole and or doramectin displayed by this study is worrisome. Multi resistant GN were present in herds 1, 3 and 8, what shows that no class of AH tested was effective for FEC reduction. Ivermectin, doramectin and abamectin presented the lowest effectiveness to FEC reduction. Low efficacy observed by the macrocyclic lactones could be associated with historic use of these AHs in this region, which favored the selection of resistant GN populations. In this study, most of the farms (72.7 %) treated all cattle of herds, not favoring refuge to sensible nematode population. The larvae on pasture, the percentage of animals left untreated and the arrested larval stages were not affected by treatment of the host 44

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determined by the GN in refuge. The proportion of these nematodes in refuge needs to be optimal in order to dilute out the resistant genes in the pool of susceptible genes(44). Data reported in this study corroborate with Gasbarre et al(45) who observed macrocyclic lactone resistance in GN from cattle in the United States. The indiscriminate use of these in arid and semiarid regions for infection control were compelled for higher efficacy and prolonged anthelmintic activity, resulting in nematode resistance due to higher usage drugs. However, it promoted high selection pressure of GN resistant ones(46). In Santa Catarina, in Brazil, efficacies >95 % for ivermectin were verified in seven beef cattle farms. Two farms detected efficacies <14 % showing evident resistance to ivermectin. Levamisole and albendazole were effective to GN control in accordance with the CMG, with efficiencies above 95 %(35). The genus Haemonchus sp. was the most frequent nematode in treated beef calves of herds number 1 and 3 (80-97 % of identified L3 larvae) and it was characterized as multiresistant to benzimidazoles, imidothiazoles and macrocyclic lactones. Trichostrongylus, Oesophagostomum, Cooperia and Bunostomum were also detected from fecal culture and post-treatments indicated an initial selection of resistant strains of these GNs. The greater pathogenicity and higher biotic potential of Haemonchus sp. have led to a higher frequency of AH treatments and higher selection pressure of resistant strains of this nematode(35). In Betim, Minas Gerais, Brazil, resistance to ivermectin and doramectin was also observed for the genera Haemonchus (72 %) and Cooperia (85 %), respectively(46). Macrocyclic lactones resistance to genera Haemonchus and Oesophagostomum was reported, in TeĂłfilo Otoni, Minas Gerais(40). The authors reported that macrocyclic lactones were also the most common ones for the control in the farms of this area. This research confirms the study performed in the state of Santa Catarina, when assessing resistance to ivermectin, phosphate of levamisole and dimethyl sulfoxide albendazole for cattle herds. There, Haemonchus spp. was predominant after deworming, showing evident multi-resistance(35). In the United States, records of resistance to macrocyclic lactones are frequent in commercial herds for Cooperia and Haemonchus genera, for ivermectin and doramectin specifically. However, the Cooperia genus was sensitive to benzimidazoles(46). In Veracruz, MĂŠxico, a high frequency of farms with GN population that is resistant to ivermectin was also observed and these nematodes genera were the most frequent ones(4). In Europe, a study involving Germany, France, Italy and the United Kingdom farms has shown low efficacy for ivermectin and moxidectin, and confirmed cases of resistance in 45

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12 % of 40 herds. Thus, the most frequent genera among treatments were Cooperia and Ostertagia, mainly in the United Kingdom and Germany farms(47).

Conclusions and implications

The most assessed farms did not practice strategic or tactical controls, promoted inappropriate and indiscriminate use of synthetic anthelminthics and macrocyclic lactones was common. All evaluated herds showed at least one anthelmintics with low efficacy, two beef farms presented multi-resistant nematodes and Haemonchus genus was the most frequent one. The applicability of strategic control in calves and tactics in heifers at peripartum, the alternation of AH classes, as well as the implementation of alternative measures such as the selection of resistant animals, the use of fungi for biological control and plant extracts to reduce resistant populations of these nematodes is essential for more sustainable control.

Acknowledgements

To Programas de Bolsa de Extensão (PBEXT), Banco do Nordeste, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).

Conflict of interest statement The authors of this manuscript have no financial or personal relationship with people or organizations that could inappropriately influence or bias the content of the paper.

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http://dx.doi.org/10.22319/rmcp.v10i1.4655 Article

Importance of sheep social hierarchy on feeding behavior and parasite load in silvopastoral and grass monoculture grazing systems

Carolina Flota-Bañuelosa Juan A. Rivera-Lorcab Bernardino Candelaria-Martínezc*

Conacyt-Colegio de Postgraduados Campus Campeche, Km 17.5 Carretera Federal Haltunchen-Edzná, Sihochac, Champotón, Campeche. México. b

Instituto Tecnológico de Conkal, Yucatán. México.

Instituto Tecnológico de Chiná, Chiná, Campeche. México.

* Corresponding author: bcm8003@gmail.com

Abstract: In sheep the interaction between social hierarchy, forage preference and parasite load effects production. A study was done of this interaction in two grazing systems (silvopastoral, SSP; star grass monoculture, PE) with twenty-two Pelibuey sheep per system. Tests were done of social hierarchy to calculate dominance index values, of forage plant species (C. nlemfuensis, L. leucocephala, G. sepium, G. ulmifolia and H. rosa-sinensis) preference, of parasite load (gastrointestinal nematode egg count per gram of feces), and of hematocrit levels. A generally nonlinear hierarchy was present in both systems, with linear dominance (h=0.75) in the SSP and bidirectional dominance (h=0.5) in the PE. In both systems the most dominant individuals had the highest number of aggressive behaviors (SSP: rs= 0.790909, P=0.05; PE: rs= 0.845455, P=0.05) and the lowest parasite loads (SSP: rs= -0.909091, P=0.05; PE: rs = 0.727273, P=0.05). In the SSP, the animals had greater preference for C. nlemfuensis but those that consumed more L. leucocephala had higher hematocrit levels (rs=0.694269, P=0.05). Sheep grazing in silvopastoral systems consume more arboreal and shrub species

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foliage which helps to control parasite load and maintain stable hematocrit levels regardless of group social rank. Key words: Animal behavior, Feeding preferences, Parasites, Small ruminants.

Received: 07/10/2017 Accepted: 06/01/2018

Introduction

The estimated worldwide sheep population is 1,173 billion(1), which represents a per capita consumption level of 2.5 kg(2). Breeding occurs mainly in Europe, Asia, South America, Australia and New Zealand. There are approximately 8.7 million head of sheep in Mexico(3), a portion of which accounts for the 55,605 t of annual meat production in 2017(4). Sheep production in the state of Yucatan is currently growing at one of the fastest rates in the country(5), although producers struggle with problems such as herd management, nutrition and health(6). Herd management involves important aspects such as herd hierarchical structure, which requires understanding the traits, functions and characteristics of animal social organization(7,8). This helps to promote efficient handling of the groups within a flock(9), and optimal management of production systems. In sheep, flock hierarchy determines access to food resources, consequently affecting the quality and quantity of harvested forage species and nutrient intake(10). As part of an integrated strategy, manipulating feed type during grazing provides useful options for controlling gastrointestinal parasites in sheep(11). Selection of non-grass forage species in silvopastoral systems has been reported to improve animal health by reducing intake of nematode larvae via infested grasses(4); this is reflected in lower fecal egg counts(12). Optimizing forage resource use by grazing ruminants requires quantification of forage selection(13). With the goal of increasing production system efficiency, the present study objective was to evaluate the relationship between flock hierarchy, food preference and degree of nematode parasite infestation in Pelibuey sheep grazing either a silvopastoral system or star grass pastures. 53

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Material and methods

Study area

The study was carry out in sheep flocks in Conkal, Yucatán, México (21°04'30.1" N; 89°30'18.4" W). With an altitude of 8 m asl, the region has a warm subhumid climate (Awo), a 26.5 °C average annual temperature, and 900 mm annual average precipitation. Soils are calcareous and shallow, with high rockiness (Lithosols and Rendzinas)(14). The experimental animals were 22 Pelibuey sheep, divided into two groups of 11 animals (five males and six females) per treatment. Average animal age was 78 d and average weight was 19.2 ± 1.4 kg. The sheep were individually marked and identified. They were managed in accordance with the Official Mexican Standard (NOM-062-ZOO-1999), which follows technical specifications for the production, care and use of experimental animals. Prior to the experiment, the animals were vaccinated with 2.5 ml triple typhoid bacterin and deparasitized with Ivomec® (0.2 mg per kilo live weight). Two grazing systems were tested. The silvopastoral system (SSP) covered a 130 x 24 m area and was planted with a mixture of forage species: African star grass (Cynodon nlemfuensis) as a base forage, Leucaena leucocephala established in rows (0.5 m between plants, 3 m between rows); a living fence consisting of Hibiscus rosa-sinensis sown every 0.25 m and interspersed with Gliricidia sepium every 2 m; and a centerline of Guazuma ulmifolia planted at 3 m intervals. The African star grass (C. nlemfuensis) pasture (PE) covered a 130 x 24 m area and contained only this forage species. The total area of each grazing system (3,120 m2) was divided into eleven paddocks measuring 9 x 22 m each. These were bounded by a mobile electric fence. Before it was grazed, each paddock was homogenized by pruning tree and shrub species to 50 cm height and star grass to 10 cm above ground level. The animals were rotated through the paddocks using a 3-d occupation to 30-d fallow ratio, with an animal load equivalent to 1 AU/ha. Over a fivemonth period (August-December) the animals were grazed daily from 0700 to 1400 h. When not grazing they were kept in individual pens, fed a commercial balanced feed (1% live weight) and provided free access to water.

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Social hierarchy tests

Sheep behavior was evaluated using a list of behaviors with forms of dominance expression(15,16). Dominance tests were done by placing two sheep from the same lot in a test pen after 18 h food restriction. They were then offered 20 g of commercial balanced feed and conflicts allowed to occur between them. For five minutes, the frequency of each conduct in the catalogue was observed and recorded using focal-animal sampling for each sheep(17), and dominance and subordination attitudes documented for each animal. This test was done once a month with all sheep in each group (SSP and PE), and results synthesized in a contingency table of paired tests(18).

Forage selection

Using direct observation(19), records were made of the first 100 bites taken by sheep of forage plants in the paddocks. Observations were made every 15 d over two consecutive days between 0700 and 1200 h in each paddock. The data collected also included time, day and animal identification number. In the SSP system, the bites were classified by the species consumed: C. nlemfuensis; L. leucocephala; G. sepium; G. ulmifolia; and H. rosa-sinensis. In the PE system, the bites were classified as star grass or weeds.

Eggs per gram feces (EPG)

Samples (10 g) of fresh feces were collected every 15 d directly from the rectum of each animal and placed in previously marked polyethylene bags. The manure from each animal was homogenized and processed individually to quantify gastrointestinal nematode egg counts per gram of feces using the McMaster technique(20).

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Hematocrit quantification (HT)

A blood sample (3 ml) was taken directly from the jugular vein of each animal every fifteen days. Each sample was placed in a previously marked test tube containing disodium EDTA and processed with the capillary microhematocrit technique(21).

Group social hierarchy analysis

Group hierarchy linearity was estimated with the Landau hierarchy(18), which allows calculation of the degree of stratification in a lot using the linearity formula: â&#x201E;&#x17D; = [12/(đ?&#x2018;&#x203A;3 â&#x20AC;&#x201C; đ?&#x2018;&#x203A;)] đ?&#x203A;´ [đ?&#x2018;&#x2030;đ?&#x2018;&#x17D; â&#x2C6;&#x2019; (đ?&#x2018;&#x203A; â&#x2C6;&#x2019; 1)/2]2 , Where: h= linearity index, n= number of animals in group, Va= number of animals dominating each individual.

Aggressiveness, dominance and movement efficiency were estimated using equations applied in grazing ruminants(22). Values in these indicators range from 0 to 1, with 1 representing absolute linearity, maximum aggressiveness, absolute dominance and maximum movement efficiency.

Aggressiveness was estimated with the equation: đ??´đ?&#x2018;&#x201D;đ?&#x2018;&#x2013;

(đ??´đ?&#x2018;&#x201D; = đ??´đ?&#x2018;&#x201D;đ?&#x2018;Ą), Where: Ag= aggressiveness index, Agi= aggressions initiated by individual, Agt= total aggressions participated in.

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Dominance was calculated with: (đ??ˇđ??ź = đ??ˇâ&#x2C6;&#x2014; Exr) Where: DI= dominance index, D= intragroup dominance index, Exr= relative movement success.

The intragroup dominance index (D) was calculated using: đ??ˇđ?&#x2018;&#x153;

đ??ˇ = đ??ˇđ?&#x2018;&#x153;+đ??ˇđ?&#x2018;&#x153;đ?&#x2018;&#x203A; , Where: Do= individuals dominated, Don= individuals not dominated

Relative movement success (Exr) was calculated with: đ??ˇđ?&#x2018;§

đ??¸đ?&#x2018;Ľđ?&#x2018;&#x; = đ??ˇđ?&#x2018;§+đ??ˇđ?&#x2018;§đ?&#x2018;&#x153; , Where: Dz= number of times the individual moved, Dzo= number of times the individual was moved.

Movement efficiency was calculated with the formula:

đ??ˇđ?&#x2018;§

đ??¸đ?&#x2018;&#x201C;đ?&#x2018;&#x2018;đ?&#x2018;§ = đ??ˇđ?&#x2018;§+đ?&#x2018; đ?&#x2018;&#x2018;đ?&#x2018;§ , Where: Efdz= individual movement efficiency, Dz= number of times the individual moved, Ndz= number of times the individual did not move.

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Social rank level was estimated based on the dominance index (DI); high= dominated â&#x2030;Ľ50 % of adversaries; medium = dominated 10 to 49 % of adversaries; and low = dominated <10 % of adversaries. The variables of dominance, feed preference, hematocrit level, EPG and the interactions between them were analyzed with a mixed linear model for repeated measurements over time, using the MIXED procedure(23). Spearman correlation tests were also run (P< 0.05) to identify the relationships between food preferences, parasite infection levels, hematocrit levels, dominance, movement efficiency and aggression. Data were analyzed with the SASÂŽ ver. 9.0 statistical package.

Results and discussion

Dominance tests

Dominance test results identified a linear hierarchy (1 dominant and 10 subordinates) in the SSP and a bidirectional hierarchy (2 dominants and 9 subordinates) in the PE (Figure 1). In small groups containing animals of the same sex and size, social structure is often linear or nearly linear(24). Hierarchy level exhibited only slight linear tendencies in the two systems: SSP, h= 0.75 and r2 = 0.9198; PE, h = 0.50 and r2 = 0.9822 (Figure 1). A hierarchy is considered linear when its Landau index value surpasses 0.9. This occurs in groups of male animals(17,18), stabled goats, which exhibit clear hierarchical gradation (h= 0.92 and 0.99)(25), and lambs, which have a significantly hierarchical social structure(26). Buffalo heifers have largely semi-linear hierarchies, with 55.24% unidirectional dominance when in large pastures, and 54 to 63% in small pastures(27). Worth noting is that no prior reports exist of hierarchical ranks in mixed groups of sheep under grazing conditions. The most dominant sheep in both studied groups showed a greater amount of aggressive behaviors (F1, 21= 0.65256, P= 0.000154) involving attacks or threats(28). In combination with knowledge of the function of each animal, an understanding of the characteristics of social organization is essential to more efficient management of animal groups and 58

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development of optimum production systems(29). Social hierarchy in a group of animals is influenced by different factors and defined as inhibition of the behavior of a submissive animal by a dominant animal through threats, butting and other aggression(30). A notable effect of being dominant in the present study was a lower parasite load (Figure 2). This coincides with a report of higher EPG values in animals belonging to middle and low (i.e. subordinate) hierarchical categories(31).

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Dominance index

Figure 1: Social hierarchy in grazing flocks in a silvopastoral system (SSP) and a star grass pasture

0.42 0.40 0.38 0.36 0.34 0.32 0.30 0.28 0.26 0.24 0.22 0.20 0.18 0.16 0.14 0.12 0.10 0.08 0.06 0.04 0.02 0.00

SSP

y = 0.043x - 0.0672 RÂ˛ = 0.9198

Dominance index

0.38 0.36 0.34 0.32 0.30 0.28 0.26 0.24 0.22 0.20 0.18 0.16 0.14 0.12 0.10 0.08 0.06 0.04 0.02 0.00

y = 0.0379x - 0.0332 RÂ˛ = 0.984

Number of animals 60

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Figure 2: Dominance level ( ) and gastrointestinal nematode egg counts per gram feces ( ) in sheep in silvopastoral (SSP) and star grass monoculture pasture (PE) grazing systems

SSP 0.45

1400

0.40

1200

0.35

Dominance

0.25

800

0.20

600

0.15

Egg counts

1000

0.30

400

0.10 200

0.05 0.00

0 1

PE 0.40

1400

0.35

1200 1000

0.25

800

0.20 600

0.15

Egg counts

Dominance

0.30

400

0.10

200

0.05 0.00

5 6 7 8 Number of animals

Forage selection

Animal forage preference in the SSP was highest for C. nlemfuensis (68 %), followed by H. rosa-sinensis (22 %) and L. leucocephala (10 %)(F2, 11= 15.95349, P= 0.00034); neither G. sepium nor G. ulmifolia were consumed. This same trend in species preference has been 61

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reported in empty adult ewes in the same kind of silvopastoral system(32). This coincides with reported sheep grazing behavior in that they are intermediate-selectivity consumers that prefer ground grasses, but will occasionally graze trees and bushes(33). Forage selection in sheep is also heavily influenced by social interactions; indeed, these can communicate aversion to certain plants that have caused unpleasant effects in the past(34). Of note is that animals which consumed the most H. rosa-sinensis had a lower number of bites of C. nlemfuensis (rs= -0.763636, P= 0.05) (Figure 3), even though C. nlemfuensis had greater biomass availability in the system(32). This was most probably due to the fact that H. rosasinensis foliage contains fewer antinutritional compounds(35,36,37), which strongly influence rejection behaviors(38).

100 90 80 70 60 50 40 30 20 10 0

33.0 32.0 31.0 30.0 29.0 28.0

Hematocrit (%)

Forage preference (%)

Figure 3: Forage preference and hematocrit levels in sheep in a silvopastoral system

27.0 1

Number of animals H. rosa-sinensis

L. leucocephala

C. nlemfuensis

Hematocrito

The sheep in the SSP that consumed the most L. leucocephala exhibited higher amounts of hematocrit (rs= 0.694269, P= 0.05). This coincides with a report of hematocrit values higher than 28 in Pelibuey sheep grazed in silvopastoral systems containing L. leucocephala, G. sepium, A. lebbeck and P. maximum grass. It is also similar to the higher hemoglobin and cell volume values reported for Pelibuey ewes and lambs that had consumed a diet supplemented with L. leucocephala or L. pallida foliage(39,40). These are favorable indicators for progeny growth and breeder health(41), and therefore have a positive impact on system productivity and sustainability(42). Part of this impact may be due to the iron (Fe) content of L. leucocephala (average= 381.30 mg Fe kg-1 DM)(43). Consumption of 94.38 g DM L. leucocephala by sheep provides 200 ppm Fe(44), an amount higher than the 30 to 50 ppm required by sheep(45). Adequate Fe intake promotes accelerated growth; increased resistance to infection; absence of anemia (reflected in the hematocrit), lethargy and increased respiratory rate; and decreased mortality rates from Fe deficiency(46). An additional benefit 62

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of L. leucocephala consumption is the reduction in gastrointestinal nematode EPG values in response to its secondary metabolites content (total phenols and saponins)(47); in fact, it has an inhibitory effect >50% (at 100 mg/ml) on third stage larvae (L3)(48). A consequent effect in the present results for the SSP was that the dominant sheep, which had more access to forage, also exhibited greater resistance to parasites and increased hematocrit levels. This agrees with the established knowledge that higher social status individuals tend to have higher productivity(49).

Conclusions and implications

The sheep in the studied silvopastoral and star grass pasture systems exhibited no significant linear tendencies in their hierarchical levels. However, when correlated with parasite egg count in feces it was observed that those animals with the highest dominance index values also had lower parasite loads. In the silvopastoral system, the sheep preferred C. nlemfuensis, followed by H. rosa-sinensis and L. leucocephala. Those that consumed L. leucocephala had higher hematocrit levels due to the contribution of iron from this legume.

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Morris ST. Overview of sheep production systems. In: Ferguson D, Lee C, Fisher A. editors. Advances in sheep welfare; 1rst ed. Duxford, United Kingdom: Woodhead Publishing; 2017:19-35.

Pérez-Hernández P, Vilaboa-Arroniz J, Chalate-Molina H, Candelaria-Martinez B, Díaz-Rivera P, López-Ortiz S. Análisis descriptivo de los sistemas de producción con ovinos en el estado de Veracruz. México. Rev Cient FCV-LUZ 2011;21(4):327-334.

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SIAP. Servicio de Información Agroalimentaria y Pesquera. 2017. Población ganadera ovina. https://www.gob.mx/cms/uploads/attachment/file/166001/ ovino.pdf Consultado 15 Feb, 2017.

Góngora-Pérez RD, Góngora-González SF, Magaña-Magaña MA Lara-Lara PE. Caracterización técnica y socioeconómica de la producción ovina en el estado de Yucatán. México. Agron Mesoam 2010;21(1):131-144.

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Damián JP, Ungerfeld R. Efecto de la jerarquía social sobre la respuesta de estrés en carneros. Agrociencia 2009;13(3):84.

Vázquez R, Orihuela A, Aguirre V. Effect of dominance-subordinate relationship and familiarity of an audience male on young rams libido and semen characteristics. J Vet Behav 2012;7(2):80-83.

Šárová R, Špinka M, Stěhulová Ll, Ceacero F, Šimečková M, Kotrba R. Pay respect to the elders: age, more than body mass, determines dominance in female beef cattle. Anim Behaviour 2013;86(6):1315-1323.

10. Waghorn CG, Shelton ID. Effect of condensed tannins in Lotus corniculatus on the nutritive value of pasture for sheep. J Agric Sci 1997;128(3):365-372. 11. Hoste H, Torres-Acosta JFJ, Quijada J, Chan-Perez I, Dakheel MM, Kommuru DS, et al. Chapter Seven. Interactions between nutrition and infections with Haemonchus contortus and related gastrointestinal nematodes in small ruminants. Robin B, et al editors. Advances in parasitology 2016;93:239-351. 12. Soca M, Simón L, García D, Roche Y, Aguilar A, Carmona L. Efecto de la velocidad de descomposición en el comportamiento del HPG en excretas de bovinos jóvenes bajo condiciones silvopastoriles. Taller Internacional sobre utilización de los sistemas silvopastoriles en la producción animal. Estación Experimental de Pastos y Forrajes Indio Hatuey. Cuba. CD-ROM. 2002. 13. Lippke H. Estimation of forage intake by ruminants on pastures. Crop Sci 2002;42(3):869-872. 14. García E. Modificaciones al sistema de clasificación climática de Köeppen. Serie libros. Instituto de Geografia. Universidad Nacional Autonoma de México. 5th ed. México, DF. 1988.

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15. Fraser AF, Broom DM. Farm animal behaviour and welfare. 3th ed. New York, USA: Sanders. CAB-International; 1997. 16. Solon EA, Lay DC, Von Borell E. Farm animal well-being. Stress physiology animal behaviour and environmental design. 1st ed. New Yersey, USA Prentice Hall; 1999. 17. Martín P, Batenson P. La medición del comportamiento. 1a ed. Madrid, España; Castellano; 1991. 18. Lehner PN. Handbook of ethological methods. 2nd ed. UK: Cambridge University Press; 1996. 19. Altman J. Observational study of behaviour: sampling methods. Behaviour 1974;49(3,4):227-265. 20. Rodríguez-Vivas RI, Arieta-Román RJ, Cob-Galera LA. Técnicas diagnósticas en parasitología veterinaria. 2a ed. Yucatán, México. Universidad Autónoma de Yucatán; 2005. 21. Benjamín MM. Manual de patología clínica en veterinaria. México DF: Limusa; 1984. 22. Galindo F. The relationship between social behaviour of dairy cow and the occurrence of lameness in the three herds. Res Vet Sci 2000;69(1):75-79. 23. Litell RC, Henry PR, Ammerman CB. Statistical analysis of repeated measures data using SAS procedures. J Anim Sci 1998;76(4):1216-1231. 24. Arave CW, Albright JL. Social ranck and physiological traits of dairy cows as influenced by changing group membership. J Dairy Sci 1976;59(5):974-981. 25. Ortíz AM, Montes de Oca C, Dzul D, Xiu R. Jerarquía y dominancia social en el macho cabrío bajo condiciones de trópico subhúmedo. Rev Cubana Cienc Agríc 2001;35(4):323-330. 26. Zine MJ, Krausman PR. Behaviour of captive mountain sheep in a Mojave desert envieronment. Southwest Nat 2000;45(2):184-195. 27. Madella-Oliveira, AF, Celia Raquel Quirino, Carlos Ramon Ruiz-Miranda, Francisco Aloizio Fonseca, Social behaviour of buffalo heifers during the establishment of a dominance hierarchy. Livestock Sci 2012;146(1):73-79. 28. Ungerfeld R, Nuñez ML. Jerarquía y dominancia en grupos de carneros: establecimiento y efectos sobre la reproducción. Veterinaria 2011;48(184):11-16. 29. Stricklin E, Mench A. Social organization. Vet. Clin. North. Am. Food Anim Pract 1987;3(1):307-320. 65

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30. Arave CW, Albright JL. The Behavior of Cattle. 1ª ed. Cambridge. UK. University Press; 1997. 31. Ungerfeld R, Correa O. Social dominance of female dairy goats influences the dynamics of gastrointestinal parasite eggs. Applied Anim Behav Sci 2007;10(1-3):249-253. 32. Candelaria-Martínez B, Rivera-Lorca JA, Flota-Bañuelos C. Disponibilidad de biomasa y hábitos alimenticios de ovinos en un sistema silvopastoril con Leucaena leucocephala, Hibiscus rosa-sinensis y Cynodon nlemfuensis. Agronomía Costarricense 201741(1):121-131. 33. Van Soest PJ. Nutritional ecology of the ruminant. 2nd ed. London, UK: Cornell University Press; 1994. 34. Provenza FD. Foraging behavior: managing to survive in a world of change. Washington, DC. USDA; 2003. 35. Alem AZM, Salem MZM, El-Adawy MM, Robinson PH. Nutritive evaluations of some browse tree foliages during the dry season: Secundary compounds, feed intake and in vivo digestibility in sheep and goats. Anim Feed Sci Technol 2006;127(3-4):251-267. 36. Gomes ME, Costa HR, Moreira RR, Pegas HJA, Ramos ALLP, Saffi J. Pharmacological evidences for the extracts and secundary metabolites from plants of the genus Hibiscus. Food Chemistry 2010;118(1):1-10. 37. Soltan YA, Morsy AS, Lucas RC, Yand AAL. Potential of minosine of Leucaena leucocephala for modulating nutrent degradability and methanogenesis. Anim Feed Sci Technol 2017;223(2017):30-41. 38. Catanese F, Fernández P, Villalba JJ, Distel RA. The physiological consecuences of ingesting a toxic plant (Diplotoxis tenuifolia) influence subsequent foraging decisions by sheep (ovis aries). Physiol Behaiv 2016;167(12):238-247. 39. Medina R, Sánches A. Efecto de la suplementación con follaje de Leucaena leucocephala sobe la ganancia de peso de ovinos desparasitados y no desparasitados contra estrongílidos digestivos. Zoot Trop 2006;24(1):55-68. 40. Chala M, Temesgen A, Tegegn G. Effect of feeding Leucaena pallida with concentrate and antihelmentic treatment on growth performance and nematode parasite infestation of Horro ewe lambs in Ethiopia. Int J Livest Prod 2013;4(10):155-160. 41. López Y, Arece J, León E, Aróstica N. Comportamiento productivo de reproductoras ovinas en un sistema silvopastoril. Pastos y Forrajes 2011;34(1):87-95.

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42. Barros-Rodríguez, M, Sandoval-Castro CA, Solorio-Sánchez J, Sarmiento-Franco LA, Rojas-Herrera R, Klieve AV. Leucaena leucocephala in ruminant nutrition. Trop Subtrop Agroecosystems 2014;17(2):173-183. 43. Garcia GW, Ferguson TU, Neckles A, Archibal KAE. The nutritive value and forage productivity of Leucaena leucocephala. Anim Feed Sci Technol 1996;60 (1-2):29-41. 44. Asaolu VO, Binuomote RT, Akinlade JA, Oyelami OS, Kolapo KO. Utilization of Moringa oleifera Fodder combinations with Leucaena leucocephala and Gliricidia sepium fodders by West African Dwarf goats. Int J Agr Res 2011;6(8):607-619. 45. NRC. National Research Council. Mineral tolerance of domestic animals. 2nd ed. National Academy of Sciences. Washington, DC. USA: National Academy Press; 2005. 46. McDonald P, Edwards RA, Greenhalgh JFD, Morgan CA. Animal nutrition. 6th ed. Essex, England: Pearson Prentice Hall; 2002. 47. Hernández PM, Salem AZ, Elghandour MM, Cipriano-Salazar M, Cruz-Lagunas B, Camacho LM. Anthelmintic effects of Salix babylonica L. and Leucaena leucocephala Lam. extracts in growing lambs. Trop Anim Health Prod 2014;46(1):173-178. 48. Jamous RM, Ali-Shtayeh MS, Abu-Zaitoun SY, Markovics A, Azaizeh H. Effects of selected Palestinian plants on the in vitro exsheathment of the third stage larvae of gastrointestinal nematodes. Vet Res 2017;13:308. 49. Engelhardt A, Heistermann M, Hodges JK, Nürnberg P, Niemitz C. Determinants of male reproductive success in wild long-tailed macaques (Macaca fascicularis) e male monopolisation, female mate choice or postcopulatory mechanisms?. Behav Ecol Sociobiol 2006;59(6):740-752.

http://dx.doi.org/10.22319/rmcp.v10i1.4512 Article

Isolation and identification of potentially probiotic lactic acid bacteria for Holstein calves in the Mexican Plateau

Patricia Landa-Salgadoa Yesenia Caballero-Cervantesa Efrén Ramírez-Bribiescaa* Ana María Hernández-Anguianoa Luz Mariana Ramírez-Hernándezb David Espinosa-Victoriaa David Hernández-Sáncheza

Colegio de Postgraduados, Campus Montecillo. Km 36.5 Carretera México Texcoco. Montecillo Estado de México. CP 56230. b

Benemérita Universidad Autónoma de Puebla. Facultad de Medicina.

* Corresponding author: efrenrb@colpos.mx

Abstract: Neonate calves are continuously exposed to a wide range of microorganisms in the environment, including diarrhea-causing enteropathogens. Lactic acid bacteria (LAB) was isolated from the oral mucosa of calves, and colostrum and milk from Holstein cows, the strains identified and their resistance to acid pH and bile salts tested. Isolation was done on plated de Man-Rogosa-Sharpe agar. Once decontaminated, the LAB colonies were morphologically and biochemically characterized. Sixteen of the isolated bacterial strains were selected: 12 from oral mucosa, 2 from milk and 2 from colostrum. After testing for resistance to an acid environment (pH 4 and 4.5) and bile salts (0.3 and 1.5 g), the five most resistant species (pH 4 and 1.5 g bile salts) were identified with the API 50 CHL system:

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Leuconostoc mesenteroides, Pediococcus pentosaceus, Lactobacillus plantarum, Lactobacillus crispatus and Lactococcus lactis. These strains have probiotic potential in calves. Key words: Calves, Probiotics, Isolation, Resistance.

Received: 01/06/2017 Accepted: 27/02/2018

Introduction

A number of problems can arise when breeding heifers for replacement, including poor colostrum supply, feeding with low quality milk substitutes and sudden changes in ration(1). These substandard breeding practices can lead to diarrhea, caused mainly by enteropathogens, with mortality rates exceeding 10 % during the first weeks of life(2). Antibiotics are used to reduce mortality, but many pathogenic strains have developed resistance, negatively affecting animal health(3,4). Several veterinary pharmaceutical laboratories now promote the use of probiotics containing lactic acid bacteria (LAB) and claim benefits such as prevention and reduction of diarrhea, and improved weight gain. However, to qualify as efficient probiotics these products must comply with certain requirements. For example, the minimum number of microorganisms required in a calfâ&#x20AC;&#x2122;s intestine to generate adequate health is 106 colony-forming units (CFU)/ml(1). Clinical trials done over the last ten years have found that 45% of probiotics on the market contain LAB with null efficiency in the prevention of diarrhea in heifers. Some even seemed to aggravate diarrhea incidence and severity(4,5), and provided no improvements in daily weight gain and feed conversion(6,7). The same still holds true for the probiotics marketed to dairy cattle production units: low viability probiotic microorganisms are used, and bacteria species other than those on the label have been identified(8). Some strains come from different geographical regions and/or other animal species, which causes low viability and probiotic activity(4). The present study objective was to isolate and identify bacteria with probiotic potential (i.e. resistance to acid pH and bile salts) in Holstein cattle in the Plateau region of Mexico. 69

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Material and methods

Isolation of bacteria from oral mucosa and colostrum

The experimental animals consisted of five lactating calves (30 d of age) and five multiparous adult cows in lactation, all Friesian Holstein from College of Postgraduates (Colegio de Postgraduados, Campus Montecillo) installations. Colostrum samples were taken from five newly-calved Holstein cows on the private Xalapango ranch. Both sites are located in the Texcoco Valley, in the State of Mexico, Mexico (18°21’ and 20°17’ N; 98°36’ and 100°36’ W)(9).

Sampling

Oral mucosa: Duplicate exudate samples were taken of the oral mucosa from each lactating calf, by rubbing the mucosa for 3 sec with a swab (3MTMSwab-sampler) prior to the morning feeding. Each swab was placed inside a sterile tube with 10 ml buffered peptone water (RS96010BPW). Colostrum and milk: Before sampling, the cows’ nipples were cleaned, disinfected and pulled down, and 5 ml of colostrum and 10 ml of milk collected per group of cows. Samples were deposited in sterile vials, kept at 4 °C and immediately transferred to the laboratory for analysis following standardized procedures(10).

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Sample processing

The samples were pre-enriched (to favor LAB growth) in liquid culture medium(11). Duplicate samples (1 ml) of the oral mucosa bacterial suspension were taken and placed in tubes containing 5 ml de Man/Rogosa/Sharp (MRS) broth. The inoculated tubes were divided into two random groups: one under aerobic conditions and the other under anaerobic conditions, both were incubated at 37 °C for 18 h. In the colostrum and milk samples, 200 μl were taken in duplicate and deposited in tubes containing 5 ml MRS broth, and kept in a desiccator under an anaerobic environment (induced by a burning candle) for 18 h at 37 °C. Samples were then taken from the tubes with an inoculation loop and sown in Petri dishes containing MRS agar(12), and incubated at 37 °C for 48 h under anaerobic and aerobic conditions. A strain of Lactobacillus casei ATCC was used as a positive control and one of E. coli O42 as a negative control (both donated by the Universidad Autónoma de Querétaro).

Bacteria selection

During the sowing process the cultures were seriated according to sample duplication in the solid MRS medium. The result was a total of 54 colonies with LAB characteristics based on colony size, shape, surface, elevation, edge and color(13). Strain characterization was done by the Gram stain test, cell morphology, spore staining and the catalase test(12). Indole production and motility tests were done in SIM (hydrogen sulfide, indole, motility) culture medium; gelatin hydrolysis and nitrate reduction tests were also done(14). A second selection of the isolated colonies was made based on the best scores and ideal coccobacilli and bacilli morphology. A total of 27 colonies were identified which were cultured in 5 ml MRS broth for 18 h for later evaluation as probiotic bacteria. Duplicate 800 µl samples were taken from each bacterial suspension and transferred to Eppendorf tubes containing 800 µl sterile 50% glycerol as a cryoprotectant. These were stored at -20 ºC for 3 h and subsequently at -80 ºC indefinitely.

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Resistance and survival of selected strains under gastrointestinal conditions

Resistance to acid pH

Inoculum preparation: A further selection was made of the 27 colonies obtained in the isolation process; 16 were chosen for having well-defined coccobacilli and bacilli morphology. Of these sixteen, twelve were isolates from oral mucosa, two from milk and two from colostrum. All selected colonies were reactivated by raising storage temperature to -20 ºC and then to room temperature. Each colony was then transferred into tubes containing 5 ml MRS broth and incubated at 37 ºC under anaerobic conditions for 24 h. A 1 ml sample of each bacterial suspension (106 Log10 CFU/ml) was added to tubes containing 9 ml MRS broth and incubated another 18 h. These final bacterial suspensions were centrifuged at 2,056 xg for 10 min, and the cellular packages resuspended in 10 ml sterilized (110 °C for 15 min) skim milk (Alpura® 2000®) for the resistance test at pH 4.5 and 4.0. The milk functioned as a protective medium and a vehicle for probiotic microorganisms(15), following the protocol described by Fernández de Palencia et al(16). Resistance to acid pH conditions was assessed by reducing the pH to which the bacterial cells were exposed. Reduction of pH was done with controlled HCl aliquots. When PH stabilized at 4.5 and 4.0, samples were incubated at 37 °C for 10 min. Subsequently, 1 ml of each suspension was taken to make serial dilutions. From each dilution, 100 µl was taken and sown in MRS agar to estimate bacterial cell viability. The colonies evaluated at pH 4.5 and 4.0 were sown at 10-6 and 10-7 in a milk suspension.

Resistance to bile salts exposure in microtitre plates

The selected colonies were exposed to bile salts (BS) in microtitre plates (BD PrimariaTM) with 3.5 ml wells. One plate was used per concentration. Before beginning the test, two flasks were prepared containing 100 ml MRS broth: one with 0.3 g bovine BS and the other with 72

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1.5 g bovine BS (Oxgall DifcoTM)(17,18). Two negative controls were run: MRS with BS and without bacteria, and MRS without BS and with bacteria. The BS resistance test was run in triplicate and each colony occupied six plate wells. In addition, 2 ml BS solution (MRS with BS and without bacteria) and 20 μl (1:10 v/v) of bacterial suspension were incubated for 18 h. One hour after inoculation and before the plates were incubated, the optical density (OD) of each suspension was measured at 600 nm using a spectrophotometer (GENESYS 10 UV/Thermo Spectronic). The OD reading was taken again once the plates had been incubated under anaerobic conditions at 37 ºC for 24 h.

Biochemical identification and collection of strains with probiotic potential

Colonies with LAB characteristics were identified using the APICHL system (BioMerieux SA, France). In this procedure the colonies were reactivated in 5 ml MRS broth under anaerobic conditions at 37 ºC for 18 H, adding 50CH diluent (supplied with the gallery: API50CH) following manufacturer instructions (see Figure 1 for summary of procedure). The prepared suspension was added to 50 microtubes in the gallery, and the domes of these microtubes filled with sterile mineral oil to generate anaerobic conditions. The inoculated galleries (one per colony) were kept at 37 ºC for 48 h to establish each colony’s biochemical profile. Results interpretation was done based on color change in the API50CHL medium of each microtube: blue is negative, and yellow and black indicate positive values (plate safety sheet). Results were analyzed with the Apiweb® computer system.

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Figure 1: Probiotic bacteria isolation and selection procedure

Phase 2

Phase 1 ISOLATION

Samples Oral mucosa (lactating calves)

Milk and Colostrum (Holstein cows)

Phase 3

SELECTION

Morphological Identification

Biochemical test

-Colony appearance

-Catalase

GASTROINTESTINAL CONDITIONS RESISTANCE

Resistance to acidic conditions

Resistance to bile salts

-Indol -Gram stain Process

Broth MRS preenrichment for 18 h

-Mobility

Agar MRS enrichment for 48 h

-Cell morphology

-Gelatinase

-Spore stain

-Nitrate reduction

Milk inoculation with lactic acid strains

0.3 y 1.5 g bile salts/100mL of MRS (reactive)

Inoculated milk

20 µL inoculated in 2 mL reactive

Adjust of pH 4.0 and 4.5, incubated for 10 min

Anaerobic and aerobic incubation at 37°C

Viable cell count in agar MRS

Optical density measurement (O.D.600nm) 1 h and 24 h

Resistance evaluation by O.D. differences at 1 h and 24 h.

Statistical Analyses

When analyzed with Kolmogorov–Smirnov test the data exhibited a normal distribution, and a Levene test showed variance homogeneity. Means were compared with an ANOVA and a Tukey test; significance level was 0.05%. All analyses were run with the SPSS ver. 15 statistics package(19).

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Results and discussion

Colony isolation and growth

The colonies cultured in the anaerobic environment exhibited better growth than those cultured under aerobic conditions. Based on morphology, the selected colonies were Gram positive coccobacilli and bacilli, with no spores, catalase negative, no motility, no indole or gelatinase production and nitrate reduction negative. The colonies from the oral mucosa samples had an average size of 2 to 4 mm in diameter with homogeneous morphological characteristics; circular shape, convex elevation, complete edge, smooth surface and white color without pigments. Of the milk samples only 20 % supported bacterial colony growth, which had an average size of 2.5 mm diameter. Those colonies isolated from the colostrum were beige in color and varied in size from 1 to 5 mm diameter. Probiotic bacteria have generally been isolated from the oral, vaginal, and intestinal mucosa of healthy calves and from milk samples(11,20). Lactobacilli colonies isolated from the oral mucosa and milk have the capacity to adapt and survive(13). This is due to the presence of the hemin group, which allows them to activate the respiratory chain with oxygen as the electron recipient(21). The different LAB genera share morphological, metabolic and physiological characteristics such as shape, elevation, edge, color and biochemical reactions(13). For the purpose of probiotic strain selection, their cell morphology and biochemical tests have been reported as basic(5,22), although it is recommended that selection be complemented with molecular studies(23).

API biochemical strain identification

Colony identification based on carbohydrate fermentation profile (API50CHL-BioMerieux) produced a 96 to 99 % effectiveness interval (Table 1). Identified colonies from the oral

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mucosa included six Lactobacillus, five Leuconostoc and one Pediococcus, while those from the colostrum included Leuconostoc and Lactobacillus.

Strain viability based on resistance to acid pH

Analysis of colony population resistance to different pH levels (Table 1), found growth at the control pH (6.5) to average 9.07 log10 CFU/ml. At pH 4.0 growth decreased (P<0.001) to 5.09 log10 CFU/ml. The two colonies from the milk samples did not grow at pH 4 and were not included in the final strains. Resistance to acid pH is relevant because to reach the action site and remain viable probiotic bacteria must withstand acid pH and the presence of BS in the duodenum(24). Several authors have developed methodologies to evaluate probiotic strain resistance under gastrointestinal conditions(7,25). The present results coincide with a study of L. plantarum and L. acidophilus in which these strains grew and remained viable at pH 5.0, but became inactive at pH 4.0 and 3.0(16). Strain sensitivity may be related to the acid tolerant response or acquired resistance. For example, in a study comparing a control of L. casei cells grown at pH 6.0 to acid adapted cells at pH 4.5 for 10 and 20 min, viability decreased up to 4.0 log10 CFU/ml at 10 min adaptation, and from 0.7 to 2.4 log10 CFU/ml at 20 min(26). Cell adaptation to an acid environment caused changes in membrane lipid composition, with a dramatic increase in saturated and unsaturated fatty acids, as well as malolactic fermentation and intracellular histidine accumulation. The ability of probiotic bacteria to survive the stomachâ&#x20AC;&#x2122;s acid environment varies by strain(27,28,29), which would explain the differences in resistance between LAB strains observed here at pH 4.0. Lactobacilli commonly grow better at pH 4.0 than at pH 3.0(30), and at pH 3.0 only four of 200 known LAB strains survive(31).

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Table 1: Colony counts in de Man-Rogosa-Sharpe (MRS) agar immediately after exposure to acid pH, and biochemical strain identifications Strain count

T1 pH 6.5

T2 pH 4.5

T3 pH 4.0

Biochemical strain identifications*

9.40

9.21

5.74

Mucosa 1 2 3 4 5 6 7 8 9 10 11 12

8.77 9.46 9.02 9.06 8.28 8.78 8.71 9.36 9.39 9.37 9.36 8.82

8.40 8.43 9.36 7.23 7.67 8.47 8.49 8.39 9.11 8.68 8.84 8.48

5.08 5.49 5.09 4.83 5.06 4.01 6.43 6.47 5.44 NG NG 3.33

Leuconostoc mesenteroides Leuconostoc mesenteroides Pediococcus pentosaceus Lactobacillus plantarum Lactobacillus plantarum Lactobacillus salivarius Leuconostoc mesenteroides Lactobacillus crispatus Leuconostoc mesenteroides Lactobacillus brevis Lactobacillus brevis Leuconostoc mesenteroides

9.02 9.15

8.14 8.31

NG NG

Lactobacillus brevis Lactobacillus brevis

15 16

9.32 9.32

9.14 8.95

5.34 4.52

Lactococcus lactis Leuconostoc mesenteroides

Mean

9.07±0.33a

8.50±0.54b

5.09±0.89c

Milk 13 14 Colostrum

* Identification done with API system (API 50CHL). Treatment ~ corresponds to positive control strain L. casei. Data are the mean of three replicates and correspond to log10 CFU/ml. NG: No growth. a,b Different superscript letters in the mean value ± standard deviation indicate significant difference. (P<0.03).

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Viability under bile salts exposure

When exposed to high BS concentrations, the LAB tested in the present study continued to grow at concentrations as high as 1.5 g. Lactic acid bacteria resistance to and growth under exposure to BS has been tested at concentrations from 0.1 to 4.0 %(32,33); this is an important parameter for microorganisms in commercial products(34,35), but one rarely tested. In another study(36), L. plantarum resistance was exposed to four concentrations of porcine BS (0.01, 0.05, 0.10 and 0.15 g), and strain growth monitored for 24 h via OD measurements. The highest growth rate was observed at the lowest BS concentration, and, at the final density and 0.10 g BS, this strainâ&#x20AC;&#x2122;s growth rate was three times lower than in the control. This is higher growth inhibition at lower BS concentrations than observed in the present study: final colony OD was only 2.5 times lower at 0.3 g BS than in the control treatment. There are reports of resistance to BS at concentrations from 0.3 to 1% BS in LAB (Streptococcus thermophilus, Lactobacillus delbrueckii subsp. bulgaricus and Lactococcus lactis) and probiotic bacteria (L. acidophilus, L. casei, L. rhamnosus and Bifidobacterium)(37,38). In these studies, S. thermophilus was the most sensitive LAB strain (growth inhibition at 0.5 g BS), L. lactis was the most resistant LAB (growth inhibition at 1 g BS), and all the probiotic strains exhibited resistance to 1.5 g BS. Resistance to BS exposure may differ between Lactobacillus species based on their ability to colonize and rapidly stabilize, as has been tested in the intestine of heifers(7). For example, in an in vivo study in which L. acidophilus was administered to heifers, the total lactobacilli count in the jejunum increased from 13 to 39 %, but strains of L. plantarum and Lactococcus acidilactici exhibited better growth at pH 4.0 and 0.3 g BS(5). In the present results, the LAB were more tolerant of BS exposure than of acid pH levels (4.0). However, their relatively good resistance to prolonged exposure to acid pH and very good resistance to high BS concentrations are effective indicators of their survival and colonization capacity during intestinal transit(28,39). Resistance to BS was also quantified by comparing strain average OD at two BS concentrations (0.3 and 1.5 g) (Table 2). Average OD in all the evaluated strains increased 3.1 times (P<0.05) after 24 h incubation at 0.3 g SB, compared to the initial reading, but when exposed to 1.5 g BS for 24 h, it increased 2.7 times. Optical density (OD) dropped significantly (P<0.023) as BS concentration increased, but it still increased (P<0.0001) from 1 to 24 h.

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Table 2: Average optic density (OD) of growth in lactic bacteria strains at two bile salts (BS, %) concentrations at 1 and 24 hoursâ&#x20AC;&#x2122; incubation

I OD P>F

Treatment 0.3% BS 1.5% BS 1h 24h 1h 24h 0.33 1.02 0.31 0.84 0.008 0.008

Main Effects MSE

0.3% BS 1.5% BS

0.03

0.68

0.57

MSE

24h

MSE

0.02

0.32

0.93 0.0001

0.02

0.023

MSE = Mean standard error.

Evaluations of the benefits of probiotic bacteria in heifers have been contradictory, perhaps due to a lack of diversity in probiotics for specific geographical regions and sale of unviable strains. This makes it difficult to find experimental sequences utilizing the same strain(40). The marketing of probiotic products for heifers in Latin America is limited and dubious. Most suppliers offer only L. acidophilus strain KA1-A 8 (3 trillion CFU/dose) and L. casei (3 billion CFU/dose), without specifying their use in heifers. Others promote products containing Lactobacillus rhamnosus and Bifidobacterium lactis (1 x 1011 CFU/ dose or 50 units for direct application in 1,000 L milk). But they do not specify strain origin, leaving open the possibility that they have been isolated from other animal species or food, making them suboptimum options for use in heifers. For example, when human probiotic strains are administered to livestock the microorganisms cannot resist gastrointestinal conditions or colonize the intestine due to interspecies differences in physiology and food(41,42). This is why the strains isolated in the present study were taken from the species in which they are intended for use and in the region they are to be applied; their probiotic potential can therefore be stated to be for Holstein cattle in the study area. Currently, the most widely used probiotic bacteria genera in livestock are Lactobacillus, Enterococcus, Bifidobacterium, Lactococcus and Leuconostoc(43); Lactobacillus plantarum, L. acidophilus, L. casei, L. salivarius and Lactococcus lactis(5,44,45); and L. fermentum VC3B-08, W. hellinica V1V-30 and L. farciminis B4F-06(20).

Conclusions and implications

Sixteen lactic acid bacteria colonies were selected from the oral mucosa, milk and colostrum of Holstein cattle. Lactobacillus brevis isolated from samples of the oral mucosa and milk did not grow in acid pH (4.0). Based on their relative resistance to acid pH and good

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resistance to bile salts, five strains were selected: Leuconostoc mesenteroides, Pediococcus pentosaceus, Lactobacillus plantarum, Lactobacillus crispatus and Lactococcus lactis. These strains have broad probiotic potential in heifers and require further direct in vivo evaluation in the gastrointestinal tract.

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Shu Q, Gill HS. Immune protection mediated by the probiotic Lactobacillus rhamnosus HN001 (DR20TM) against Escherichia coli O157:H7 infection in mice. FEMS Inmunol Med Microbiol 2002;(34):59–64.

Frizzo LS, Zbrun MV, Soto LP, Signorini ML. Effects of probiotics on growth performance in young calves: A meta-analysis of randomized controlled trials. Anim Feed Sci Technol 2011;(169):147–156.

Rosmini MR, Sequeira GJ, Guerrero I, Marti LE, Dalla R, Frizzo L, Bonazza JC. Producción de prebióticos para animales de abasto: Importancia del uso de la microbiota intestinal indígena. Rev Mex Ing Quim 2004;(3):181-191.

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He ZX, Ferlisi B, Eckert E, Brown HE, Aguilar A, Steele MA. Supplementing a yeast probiotic to pre-weaning Holstein calves: feed intake, growth and fecal biomarkers of gut health. Anim Feed Sci Technol 2017;(226):81-87.

Wannaprasat W, Koowatananukul C, Ekkapobyotin C, Chuanchuen R. Quality analysis of commercial probiotic products for food animals. Southeast Asian J Trop Med Public Health 2009;(40):1103–1112.

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10. NOM-109-SSA1-1994: Proyecto de Norma Oficial Mexicana, Bienes y Servicios. Procedimiento para la toma, manejo y transporte de muestras de alimentos para su análisis microbiológico. 1994. Diario Oficial de la Federación. 1994. 11. Coeuret V, Dubernet S, Bernardeau M, Gueguen M, Vemoux JP. Isolation, characterisation and identification of lactobacilli focusing mainly on cheeses and other dairy products. Dairy Sci Technol Le Lait 2003;(83):269-306. 12. Pérez MJ, Vázquez JR, Rodríguez MC, Miranda RE, Romo AL, Nader GE. Procedimientos de laboratorio para bacteriología y micología veterinarias. Universidad Nacional Autónoma de México, México, DF. 1987. 13. Kandler O, Weiss N. nonsporing Gram positive rods. Bergey´s Manual of systematic bacteriology.10th ed (ed. Sneath, Mair, Sharp and Holt), Baltimore, USA: The Williams and Wilkins Co; 1992. 14. Haro M, Ruiz V, Guerra F. Manual para la identificación de microorganismos de interés veterinario. México: Trillas; 2012. 15. Bove P, Gallone A, Russo P, Capozzi V, Albenzio M, Spano G, Fiocco D. Probiotic features of Lactobacillus plantarum mutant strains. Appl Microbiol Biotechnol 2012;(96):431-441. 16. Fernández de Palencia P, López P, Corbí AL, Peláez C, Requena T. Probiotic strains: survival under simulated gastrointestinal conditions, in vitro adhesion to Caco-2 cells and effect on cytokine secretion. Eur Food Res Technol 2008;(227):1475–1484. 17. Pereira DI, McCartney AL, Gibson GR. An in vitro study of the probiotic potential of a bile-salt-hydrolyzing Lactobacillus fermentum strain, and determination of Its cholesterol-lowering properties. Appl Environ Microbiol 2003;(8):4743-4752. 18. Tinrat D, Saraya S, Chomnawang MT. Isolation and characterization of Lactobacillus salivarius MTC 1026 as a potential probiotic. J Gen Appl Microbiol 2011;(57):365-378. 19. SPSS® Version 15 software (SPSS Inc., Chicago, IL). Copyright © 2006 de SPSS Inc. 20. Sandes S, Alvim L, Silva B, Acurcio L, Santos C, Campos M, Santos C, Nicoli J, Neumann E, Nunes A. Selection of new lactic acid bacteria strains bearing probiotic features from mucosal microbiota of healthy calves: Looking for immunobiotics through in vitro and in vivo approaches for immunoprophylaxis applications. Microbiol Res 2017;(200):1-13. 21. Ekinci F, Gurel M. Effect of using propionic acid bacteria as an adjunt culture in yogurt production. J Dairy Sci 2007;(91):892-899.

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22. Jaramillo GD, Meléndez AP, Sánchez MO. Evaluación de la producción de bacteriocinas a partir de Lactobacillus y Bifidobacterias. Rev Venez Cienc Tecnol Aliment 2010;(1):193-209. 23. Marroki A, Zúñiga M, Kihal M, Pérez- Martínez G. Characterization of lactobacillus from algerian goat’s milk based on phenotypic, 16sr DNA sequencing and their technological properties. Brazilian J Microbiol 2011;(42):158-171. 24. Salminen S, Von Wright A, Morelli L, Marteau P, Brassart D, de Vos WM, et al. Demonstration of safety of probiotics-a review. Int J Food Microbiol 1998;(44):93-106. 25. Dunne C, O´Mahony L, Murphy L. In vitro selection criteria for probiotic bacteria of human origin: correlation with in vivo findings. Am J Clin Nutr 2001;(73):386-392S. 26. Broadbent JR, Larsen RL, Deibel V, Steele JL. Physiological and transcriptional response of Lactobacillus casei ATCC 334 to acid stress. J Bacteriol 2010;(192):24452458. 27. Charteris WP, Kelly PM, Morelli L, Collins JK. Development and application of an in vivo methodology to determine the transit tolerance of potentially probiotic Lactobacillus and Bifidobacterium species in the upper human gastrointestinal tract. J Appl Microbiol 1998;(84):759–76. 28. Chou LS, Weimer B. Isolation and characterization of acid- and bile-tolerant isolates from strains of Lactobacillus acidophilus. J Dairy Sci 1999;(82):23–31. 29. Xanthopoulos V, Litopoulou-Tzanetaki E, Tzanetakis N. Characterization of Lactobacillus isolates from infant faeces as dietary adjuncts. Food Microbiol 2000;(17):205–215. 30. Jin LZ, Ho YW, Abdullah N, Jalaludin S. Acid and bile tolerance of Lactobacillus isolated from chicken intestine. Lett Appl Microbiol 1998;(27):183-185. 31. Prasad J, Gill H, Smart J, Gopal PK. Selection and characterization of Lactobacillus and Bifidobacterium strains for use as probiotics. Int Dairy J 1998;(8):993–1002. 32. Gómez-Zavaglia A, Kociubinski G, Perez P, De Antoni G. 1Isolation and characterization of Bifidobacterium strains for probiotic formulation. J Food Prot 1998;(61):865-873. 33. Kociubinski G, Pérez P., De Antoni G. Screening of bile resistance and bile precipitation in lactic acid bacteria and bifidobacteria. J Food Pro 1999;(62):905-912. 34. Carr F, Chill D, Maida N. The lactic acid bacteria: A literature survey. Crit Rev Microbiol 2002;(28):281-370. 82

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35. Foditsch C, Pereira RVV, Ganda EK, Gómez MS, Marques EC, Santin T, Bicalho RC. Oral Administration of Faecalibacterium prausnitzii decreased the incidence of severe diarrhea and related mortality rate and increased weight gain in preweaned dairy heifers. PLOS ONE 2015;(10):e0145485. 36. Bron PA, Grangette C, Mercenier A, de Vos WM, Kleerebesem M. Identification of Lactobacillus plantarum genes that are induced in the gastrointestinal tract of mice. J Bacteriol 2014;(186):5721-5729. 37. Naidu AS, Biblack WR, Clemens RA. Probiotic spectra of lactic acid bacteria. Critical Rev Food Sci Nutrition 1999;(38):13-126. 38. Lee YK, Nomoto K, Salminen S, Gorbach S. Handbook of probiotics. Lee YK editior. New York, USA: John Wiley & Sons. Inc; 1999. 39. Haller D, Colbus H, Ganzle MG, Scherenbacher P, Bode C, Hammes WP. Metabolic and functional properties of lactic acid bacteria in the gastro-intestinal ecosystem: a comparative in vitro study between bacteria of intestinal and fermented food origin. Syst Appl Microbiol 2001;(24):218–226. 40. Maragkoudakis PA, Zoumpopoulou G, Miaris C, Kalantzopoulos G, Pot B, Tsakalidou E. Probiotic potential of Lactobacillus strains isolated from dairy products. Int Dairy J 2006;(16):189–199. 41. Ewaschuk JB, Naylor JM, Chirino-Trejo M, Zello GA. Lactobacillus rhamnosus strain GG is a potential probiotic for calves. Can J Vet Res 2004;(68):249–253. 42. Ewaschuk JB, Zello GA, Naylor JM. Lactobacillus GG does not affect D-lactic acidosis in diarrheic calves, in a clinical setting. J Vet Int Med 2006;(20):614–619. 43. Gaggia F, Mattarelli P, Biavati B. Probiotics and prebiotics in animal feeding for safe food production. Int J Food Microbiol 2010;(141):S15–S28. 44. Cebeci A, Gürakan C. Properties of potential probiotic Lactobacillus plantarum strains. Food Microbiol 2003;(20):511–518. 45. Vinderola CG, Reinheimer JA. Lactic acid starter and probiotic bacteria: a comparative in vitro study of probiotic characteristics and biological barrier resistance. Food Res Int 2003;(36):895–904.

http://dx.doi.org/ 10.22319/rmcp.v10i1.4661 Article

Effect of an intraruminal monensin bolus on blood β-hydroxybutyrate, peripartum diseases, milk yield and solids in Holstein cows

Pedro Melendeza* Alejandra Arévalosb Mario Duchensb Pablo Pinedoc

University of Georgia, College of Veterinary Medicine. Tifton, GA 31793, EE.UU.

Universidad de Chile, Colegio de Ciencias Veterinarias. Santiago, Chile.

Colorado State University, Department of Animal Sciences. Fort Collins, CO, EE.UU.

*Corresponding author: pedro.melendez@uga.edu

Abstract: Administration of monensin to dairy cows during the transition period may improve cow health, although this is debated. An evaluation of the effects of an intraruminal controlledreleased bolus of monensin on health and milk production in transition Holstein cows was done in a Chilean dairy farm. Seventy-seven (77) cows at 21 d before expected parturition were randomly assigned to either a treatment (n= 37) or a control (n= 40) group. The treatment group received a controlled-release oral bolus that delivered sodium monensin at a rate of 335 mg/d for about 95 d. For the first 10 d postpartum cows were clinically examined daily. From 21 d prepartum to 21 d postpartum, data were collected, considering the presence of fever (t°≥ 39.5 °C), postpartum diseases, weekly blood β-hydroxybutyrate (BHB) concentrations, and body condition score. Comparisons of milk production, milk solids (protein and fat percentage) and somatic cell counts (SCC) during the first 100 d of lactation were conducted. Blood BHB concentrations (mmol/L) were similar between groups (P>0.05). No differences were observed on the incidences of ketosis, fever, puerperal

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metritis, or retained fetal membranes. Endometritis tended to be less frequent in the treatment group than the control group (P=0.08). Monensin did not significantly improve milk yield, fat content, or SCC content. However, cows treated with monensin produced milk with higher protein content during the first week postpartum than the control group (P<0.05). Treated cows also exhibited better improvement on body condition score (P<0.05) between dry-off and parturition and minor losses on body condition score (P<0.05) between parturition and 21 d postpartum than control group. Key words: Monensin, Intraruminal bolus, Diseases, Postpartum, Dairy cow.

Received: 11/10/2017 Accepted: 16/02/2018

Introduction

Transition period for dairy cattle is defined as the final 21 d of gestation to 21 d postpartum. During this period, stress and metabolic changes make cows more susceptible to disease(1-3). Most (75 %) diseases in dairy cattle occur within the first month of lactation and 50 % of metabolic and infectious diseases arise during the transition period(4). There is also a decrease in dry matter intake (DMI) and an increase in energy demands due to fetal growth and increased postpartum milk yield(1). Consequently, dairy cows experience a typical negative energy balance (NEB), which is mostly characterized by mobilization of fat from the adipose tissue. Mobilized fat is transported through the plasma as non-esterified fatty acids (NEFA) to the liver following several metabolic pathways. When glucose levels are normal, NEFA are re-esterified to triglycerides and transported to the blood in the form of very low density lipoproteins(5). If glucose levels are low, NEFA enter the mitochondria and oxidize to acetylCoA to continue in the Krebs cycle or form ketone bodies. Oxaloacetate is required to enter the Krebs cycle, which originates mainly from glucose. Since the adaptive response to NEB is poor and glucose is directed to the mammary gland for lactose synthesis, formation of ketone bodies increases, resulting in clinical or subclinical ketosis(5). Subclinical ketosis is characterized by circulating Î˛-hydroxybutyrate (BHB) levels â&#x2030;Ľ 1.2 mmol/L in the absence of clinical signs(6-8). Ketosis can be diagnosed by quantifying ketone bodies in urine (acetoacetate), milk (BHB), serum (BHB), plasma (BHB), and blood (BHB)(9). Cows that 85

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develop ketosis produce less milk and are at higher risk of experiencing other postpartum diseases, which can lead to reduced fertility(10,11), and subsequent significant losses for the dairy industry(7,12). Disease predisposition is higher during the transition period in dairy cows, highlighting the importance of prevention strategies, including adequate nutritional management. The use of additives such as monensin, an ionophore which alters ruminal fermentation in favor of propionic acid production (the principal gluconeogenic precursor in ruminants) might contribute to lowering the incidence of ketosis and related disorders(13,14). As a result, milk production, and fertility may improve(2,15). The present study was designed to address the hypothesis that cows treated with an intraruminal monensin bolus will have lower blood BHB concentrations, lower postpartum disease incidence and higher milk production than cows without monensin. The objective was to evaluate the effect of an intraruminal controlled-release sodium monensin capsule (300 mg monensin per day for 95 d) on postpartum BHB concentrations, peripartum disease incidence, milk production and solids in Holstein cows from a Chilean commercial dairy farm. Variables included in the study were the environment and climate (Mediterranean), type of forage and quality (hay, alfalfa silage and corn silage) and concentrate quality (based on corn grain, soybean meal, canola meal, wheat middlings, cotton seed, and byproducts), etc.

Material and Methods

Dairy and animals

The study was conducted in a commercial dairy farm from central Chile (33.8째 S, 71.3째 W). Average annual rain fall is 235 mm, annual mean minimum temperature is 2 째C and maximum is 30 째C(16). The experimental animals were 400 Holstein lactating cows housed in a free-stall system bedded with sand. Milking was done three times a day, and average mature equivalent milk production was 12,800 kg (305 d, 2X). Between 45 and 60 d before expected parturition (BEP), cows were dried, housed in a dry-lot and fed typical diets for dry cows. Four weeks BEP, cows were moved to a prepartum lot and fed an anionic diet 86

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supplemented with a glucose precursor (propylene glycol; 200 g/cow/d). The supplement was not fed during the postpartum period. Cows delivered in a maternity pen. After parturition cows were moved to a postpartum group until 21 d in lactation. Diets were formulated to meet or exceed nutritional requirements according to the Cornell Net Carbohydrate and Protein System(17), using a commercial software (NDS, RUM & N Sas, Reggio Emilia, Italy).

Experimental design

Considering a difference in blood BHB concentration of 0.2 mmol/L between a treatment group (1.0 mmol/L) and a control group (1.2 mmol/L; cutoff value for subclinical ketosis), with a SD= 0.22, 95% confidence interval and 80% power(6), a sample size of 30 cows per group was calculated. The experiment was initiated with 40 animals per group to compensate for any involuntary elimination and ensure the minimum number of animals based on the sample size calculation. Animals were randomly assigned to each group 28 d BEP. In the treatment group each animal was orally administered a controlled-release sodium monensin bolus that releases a daily dose of ~ 335 mg sodium monensin over a 95-d period (RumensinÂŽ capsule, Elanco, Greenfield, IN, USA). Each bolus displayed a tracking number which was matched with the cowâ&#x20AC;&#x2122;s identification number to allow identification if the bolus were regurgitated. Prepartum treatment and control cows were housed and handled indistinguishable in the same corral, receiving the same diet (Table 1 and 2). Therefore, they were exposed to the same environmental and management conditions. Both prepartum and postpartum lots were inspected daily to identify any regurgitated bolus. If one was found, its condition was assessed and, if not damaged, it was re-administered. Damaged boluses were replaced with a new bolus.

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Table 1: Composition (kg/day, dry matter base) of pre- and postpartum diets fed to cows in the monensin treatment and control groups Ingredients Alfalfa hay Corn silage Wheat straw Corn grain Soybean meal Canola meal Wheat middlings Bypass fat Wet Brewers Calcium carbonate Anionic salt Minerals Vitamins Mycotoxin binding agent Gluconeogenic precursor1 Yeasts Total dry matter 1

Prepartum

Postpartum

0.90 5.04 1.8 0.44 0.45 0.25 0.88 2.45 0.049 0.87 0.12 0.032 0.05 0.02 0.01 13.22

2.65 6.24 3.98 2.5 0.29 2.03 0.09 1.6 0.09 0.1 0.015 0.05 0.01 19.64

Precursor based on 50% propylene glycol.

Table 2: Nutritional composition of pre- and postpartum diets fed to cows in the monensin treatment and control groups Nutrients

Prepartum

Postpartum

48.5 15.2 26.6 9.49 27.4 47.1 32.3 25.1 16.6 4.59 7.99

49.5 15.9 27.3 9.08 18.3 35.0 21.6 37.2 23.5 5.01 6.96

Dry matter, %1 Crude protein, % DM1 Soluble protein, % CP1 Degradable protein, % DM2 ADF, % DM1, a aNDFom, % DM1, b peNDF, % MS 2, c NFC, % DM1, d Starch, % DM1 EE, % DM1 Ash, % DM1

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Ca, % DM1 P, % DM1 Mg, % DM1 Na, % DM1 K, % DM1 S, % DM1 Cl, % DM1 NELac, Mcal/kg DM2 DACD, mEq/kg DM3

0.89 0.41 0.40 0.23 1.02 0.21 1.23 1.19 -90

0.85 0.41 0.31 0.32 1.13 0.21 0.30 1.60 +210

Laboratory analysis. Calculated from formulas after laboratory analysis. 3 Dietary anionic-cationic difference formula: (Na + + K+) – (Cl- + S-). a Acid detergent fiber. b Ash-free, amylase-treated neutral detergent fiber. c Physically effective neutral detergent fiber. d Non-fibrous carbohydrates. 2

Blood samples Blood samples were collected at 7, 14, 21 and 28 d postpartum to assess plasma BHB concentrations with a portable hands held meter (FreeStyle Optium®, Abbott Diabetes Care Inc., Alameda, CA). Test sensitivity was 94.8% (CI95%: 92.6-97.0) and specificity was 97.5% (CI95%: 96.9-98.1)(9). Subclinical ketosis was defined as a BHB concentration ≥ 1.2 mmol/L(6-8).

Body condition, postpartum diseases and milk production

Body condition score (BCS) was assessed by the same person at assignment, at parturition and 28 d postpartum. A five-point scale with 0.25 unit increments based on a standard methodology was used(18).

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The initial step in identifying postpartum diseases was rectal temperature using a digital thermometer at 3, 5 and 7 d postpartum. Within 24 h postpartum, retained fetal membranes (RMF) was diagnosed, which were defined as membranes present in the vulva, vagina or in utero detected by vaginal examination 24 h postpartum(19). Within the first two weeks of lactation, daily rectal palpation was done to identify any foul-smelling puerperal discharge or metritis, defined as uterine inflammation with abnormal genital discharges, with or without systemic signs, occurring within the first 14 d in lactation(20). Possible mastitis was evaluated in the milking parlor by visual milk inspection; clinical mastitis was defined as visually abnormal milk (e.g. coagulated, aqueous, fibrin residues and/or pus) in one or more quarters. Mammary secretions may or may not be accompanied by signs of udder inflammation (heat, swelling or redness)(19). Examinations for endometritis were done 25 to 38 d postpartum using a vaginoscope. Any purulent or mucopurulent discharge during this period of time was defined as endometritis(20). Milk production was measured weekly through a Chilean Dairy Herd Official test up to 90 d of lactation, using proportional meters (Waikato Milking Systems LP, Verona, WI 53593, USA). Milk fat and protein percentages, and somatic cell count (SCC) were measured weekly during the first 3 wk of lactation, using a commercial laboratory (COOPRINSEM, Osorno, Chile).

Statistical analysis

Statistical data analysis was conducted using the SAS 9.4 software(21). Postpartum disease incidence was compared by logistic regression considering treatment effect as the main variable, and adjusting for lactation number and BCS at parturition. Adjusted odd ratio (AOR) and 95% confidence intervals (CI 95%) were calculated. The concentrations of BHB, fat and protein percentages and SCC were analyzed by ANOVA repeated measures considering as explanatory variables the effect of treatment, day of sample, lactation number (2, â&#x2030;Ľ 3), BCS at parturition and their interactions. Fat and protein percentages were transformed to the arc sine of the square root, with the formula of Blis(22). The SCC was transformed to a linear score with the formula log2(SCC/100)+3, following Dabdoub and Shook(23). Mixed models were built considering the best covariance structure based on the goodness-of-fit test(24). Body condition score was assessed based on changes in body condition score from prepartum to delivery to 21 days postpartum. This variable was 90

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analyzed using a multivariate ANOVA (P â&#x2030;¤ 0.05). Tendency was considered when P values were between 0.1 and 0.05.

Results

The final analysis included 40 cows in the control group and 37 in the treatment group. Three cows were excluded from the treatment group: one died of enterotoxemia shortly after parturition, and two aborted a few days after monensin bolus administration. Average BHB blood concentrations (Âą standard mean error) (mmol/L) did not differ between the two groups over time (P>0.05) (Table 3); in other words, the time-group interaction had no significant effect and both curves were parallel. The largest difference (though not significant; P>0.05) in BHB occurred at day 7 postpartum when concentrations in the control group averaged 0.7 mmol/L and those in the treatment group 0.57 mmol/L.

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Table 3: Results of analysis of variance for repeated measurements and least means squares for BHB (mmol/L) in the control and treatment groups during the first four weeks postpartum Effect DF num1 DF den2 F P Treatment 1 74 0.14 0.70 Week 3 225 1.30 0.27 Treatment by week 3 225 1.20 0.31 Lactation 1 74 1.74 0.19 Blood BHB Concentrations (mmol/L) Week 1 2 3 4

Control 0.695 0.605 0.595 0.658

SEM3 0.062 0.062 0.062 0.062

Monensin 0.573 0.597 0.608 0.716

P > 0.05 > 0.05 > 0.05 > 0.05

1 2

Numerator degrees of freedom. Denominator degrees of freedom. 3 Standard error of mean.

Table 4: Changes in body condition score between prepartum and parturition, and parturition and postpartum in treatment and control groups Group Monensin Control Group Monensin Control

Difference in BCS Calving -prepartum 0.17 0.01 Difference in BCS Postpartum - calving -0.13 -0.31

SEM1

0.04 0.04

0.015

SEM

0.04 0.04

0.008

BC = body condition; SEM= standard error of mean.

At assignment, BCS did not differ between groups (3.28 for control group, 3.21 for treatment group; P>0.05) (Table 4). Body condition score was different at parturition, with treatment group exhibiting a higher BCS (3.21) than the control group (3.12). The difference was more noticeable at 28 d postpartum (3.14 for treatment vs 2.78 for control).

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Only a tendency (P=0.08) was observed for disease incidence. A lower rate of endometritis in treated cows (14 %) than control cows (30 %) was reported. Ketosis incidence was 15 vs 27%, RFM was 23 vs 16 %, metritis was 45 vs 30 %, and fever was 25 vs 16 %, for treated and control group, respectively. All these differences were not significant (P>0.05). Milk production over time did not differ between the two groups (P>0.05) (Figure 1). At 7 days postpartum (wk 1) production was 37.4 kg in the control group and 36.0 kg in the treatment group (P>0.05), a difference that remained unchanged throughout the 10-wk study period. Interaction group by week was clearly not significant, implying that both curves were parallel. For milk solids, only the percentage of protein in wk 1 differed between the groups, being higher in the treatment group (3.47 %) than in the control group (3.16 %) (Table 5, Figure 2). However, total kilograms of protein per week did not differ between the groups at any time. The same was true for milk fat percentage and total kilograms (P>0.05) (Table 5, Figure 3); although in Week 1 postpartum milk fat content was 4.10 % in the treatment group and 3.71 % in the control group. Finally, the linear SCC scores did not differ between groups in Weeks 1, 2, and 3 (P>0.05); linear scores were 2 to 2.5 for both groups (200 to 300,000 cells per ml, approximately), except in wk 2 (1.57 for treatment group and 2.05 for the control group; P>0.05) (Figure 4).

Figure 1: Average weekly milk production in treatment and control groups The interaction group by time was not significant (P>0.05).

Milk Production (kg/d)

55 50 45 40 35

Treatment

Control

25 20 1

Weeks Postpartum

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Table 5: Milk fat and protein percentages in the treatment and control groups during the first four weeks postpartum % Fat Week 1

Control

Monensin

SEM

3.88

4.26

0.61

> 0.05

3.36

3.19

0.59

> 0.05

4.43

4.26

0.60

> 0.05

3.40

3.45

0.61

> 0.05

% Protein Week 1

Control

Monensin

SEM

3.19

3.51

0.06

0.002

3.12

2.99

0.06

> 0.05

3.06

3.00

0.06

> 0.05

3.16

3.11

0.06

> 0.05

SEM= standard error of mean.

Figure 2: Milk protein percentage during first four weeks postpartum in treatment and control groups 3.8 3.6 3.4

Protein (%)

3.2 3

P=0.002

2.8 2.6 2.4

Treatment

Control

2.2 2 1

Week postpartum

Significant differences (Pâ&#x2030;¤0.05) in week 1.

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Figure 3: Milk fat percentage during first four weeks postpartum in treatment and control groups 4.5

Fat (%)

3.5

2.5

Treatment

Control

2 1

Week Postpartum Interaction group by week not significant (P>0.05).

Figure 4: Somatic cell count linear score during first three weeks postpartum in treatment and control groups 3 2.5

SCC LS

1.5 1 Treatment

Control

0.5 0 1

2 Week Postpartum Interaction group by week not significant (P>0.05). SCC LS = Somatic cell count linear score

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Discussion

Use of sodium monensin in dairy cows is illegal in many countries, but is permitted in the US, Chile and Argentina. One of the strengths of the present study is that the cows in the treatment and control groups were housed in the same lot, and were handled in the same way throughout the study period; consequently, the effect of corral and/or management practices on the study variables were identical, decreasing variability of statistical models. However, one of the shortcomings of this study was that some postpartum variables could only be assessed weekly and only during the first 30 days in lactation. Although most metabolic changes occur during early postpartum, there are undoubtedly longer term effects that can influence milk production, solids content, and fertility variables beyond the first month of lactation. The present study was conducted in a commercial dairy where animals are moved to different production groups after 30 d in lactation. This made study variables unfeasibly to evaluate for a longer period of time. Despite these minor limitations significant differences were identified in variables such as milk protein percentage, diseases such as endometritis, and changes in BCS. The present results indicate some benefits for the application of a controlled-release monensin bolus in Holstein cows during the transition period under the farm management conditions. At fourth week of lactation, BCS was significantly lower in the control group cows than in the treatment group cows. This may indicate that treatment with monensin aided cows to experience a reduced amount of postpartum BCS losses. Similar results have been reported in other studies evaluating the effects of monensin use on BCS. Indeed, monensin supplementation in cows led to less loss of BCS during early lactation in comparison to a control group, and helped to maintain or increase BCS from the assignment of animals (prepartum) to parturition(25,26). Lower BCS losses could be the result of increased energy and protein availability caused by the effect of monensin on ruminal fermentation. This mechanism could be partially explained by an increase in the molar proportion of propionic acid with a simultaneous decrease in the molar proportion of acetate and butyrate in the rumen(27). The increase in ruminal propionate could be accompanied by a reduction in the amount of methane produced in the rumen and an increase in blood glucose concentrations(14,28), either for milk synthesis or fat deposition(2,5). It is also known that monensin decreases L-lactate concentrations(28,29), and affects nitrogen metabolism by decreasing ruminal nitrogen ammonia (N-NH3) production(28), consequently raising duodenal flow of amino acids. However, BHB blood concentrations in the present study did not differ between the control and treatment groups, contrasting with several worldwide studies 96

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indicating that monensin exhibits a marked anti-ketogenic effect(26,30-32). Among these studies is the classic meta-analysis, summarizing 59 studies from around the world encompassing a total of 4,000 dairy cows(14). This meta-analysis showed that sodium monensin in dairy cows lowered BHB concentrations by 13 %, especially during the first month of lactation. This also occurred in grazing cows. Nonetheless, in the same meta-analysis two studies reported that monensin-treated cows had higher BHB concentrations than those in the control cows. A partial explanation for the lack of difference in BHB levels observed in the present results may be the prepartum diet supplementation with gluconeogenic precursors in the form of propylene glycol. A high proportion of propylene glycol escapes ruminal degradation and is absorbed in the small intestine, while the rest is metabolized to propionate(33,34). In the liver propylene glycol is converted into glucose, mainly through the lactaldehyde pathway and subsequent oxidation to lactate(35). Unfortunately, it was not possible to infer a positive or negative potential interaction between propylene glycol and monensin in the current experimental scenarios. No differences were observed between groups in terms of peripartum disease incidence. This differs from previous studies(13,36), which stated that monensin indirectly improves immune function by improving the energy status. Indeed, the use of a controlled slow-release bolus containing monensin was also reported to improve BCS from dry-off to calving, compared to a control group. In addition, losses of BCS between parturition and postpartum were lower in the treated than the control group, resulting in fewer diseases(36). However, most of the diseases in the present trial are within normal limits reported by previous studies (19). The exceptions were metritis and endometritis; the control group had a higher incidence (> 30 %) than the treatment group, which tended to develop fewer uterine infections. The ANOVA mixed models for repeated measurements is a very powerful statistical tool to compare the parallelism of curves of continuous variables over time because it analyzes a correlation matrix between each measurement over time. In this analysis each mean in a given time covaries by the mean of the previous measurement, generating a covariance structure of high statistical power(24). No differences in milk production were observed between the two groups. This is consistent with other studies indicating that monensin does not affect milk production(13,37). Moreover, most studies have shown no effect of pre- or postpartum propylene glycol administration on milk production levels in dairy cows (38,39). It is quite possible that the effects of prepartum propylene glycol administration on milk production and blood BHB concentration masked any positive effect of monensin that could have on these variables. When monensin and propylene glycol are administered in conjunction they can have a positive or negative interaction on the glucose and energy metabolic pathways in dairy cows. This suggests that some metabolic pathways can be saturated when a large amount of propionate is available to the liver, which marginally affects glucose synthesis. Both the control and treatment groups may therefore have produced sufficient glucose to 97

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meet the requirements for milk production and maintain low ketone body concentrations. The excess of potential glucose synthesized by the treatment group (monensin and propylene glycol) might have helped to decrease the negative energy balance and reduce the postpartum losses of BCS. Unfortunately, no studies have yet proven the hypothesis of a possible interaction between monensin and propylene glycol in transition dairy cows. One study did compare dairy cows fed propylene glycol and cows fed monensin to a control group. They found that propylene glycol group exhibited higher glucose and lower BHB concentrations than the monensin group, with not differences in milk production(40). These findings constitute partial support for the present results. Future research needs to be addressed to test the implications of both compounds in dairy cows to identify any potential beneficial or antagonistic interaction effect between monensin and propylene glycol. Milk protein exhibited a higher percentage at day 7 postpartum in the treatment group, although overall there were no differences in the total kilograms of milk protein between the treatment and control groups. This contrasts with a previous report stating that monensin increased total protein production (kg) but decreased its percentage in milk(14). Treatment with monensin did not, however, affect milk fat percentage, again contrasting with a previous study indicating that monensin lowers milk fat percentage, and acetate and butyrate production in the rumen, leading to an overall reduction in lipogenic precursors for fatty acids synthesis in the mammary gland(14). The metabolic dynamics of the dairy cow in the transition period, especially during early postpartum, is complex and multifactorial. It is known that insulin plays a fundamental role during these periods, and that cows experience a state of insulin-resistance towards the end of gestation and in early lactation as a metabolic strategy to spare glucose for the fetus and mammary gland in early postpartum(41). Future studies are encouraged to investigate glucose and insulin concentrations to attempt to elucidate the impact of insulin on cow metabolic status during early postpartum period when glucose precursor are administered. No differences in SCC were observed between the control (57,000 cells/ml) and treatment (51,000 cells/ml) groups. These values are well below the recommended SCC (200,000 cells/ml) for an acceptable milk quality. These SCC are also in agreement with the low incidence of clinical mastitis observed in the present study. The reduction in BCS losses observed in early lactation might be the consequences of feeding good quality diets and adequate nutritional management, as well as proper handling and better cow-comfort in the pre- and postpartum period. These conditions could have lowered energy requirements, resulting in less mobilization of body reserves. This in turn would maintain low BHB concentrations, leading the animals to a better health and milk production in both groups. The present results suggest that the administration of monensin provides benefits in well-managed dairy cattle receiving properly feed management and handled under 98

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adequate cow-comfort conditions. Low incidence of diseases on the studied dairy farm is most likely the result of good management practices such as early disease diagnosis and opportune treatment, especially in early postpartum cows.

Conclusions and implications

Use of a controlled-release monensin bolus in dairy cows improved postpartum BCS dynamics, with a tendency of lower uterine infections and a slight improvement in milk protein content. Under the studied conditions monensin caused no differences in milk production and blood BHB concentration between both groups.

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Drackley JK, Overton TR, Douglas GN. Adaptations of glucose and long-chain fatty acid metabolism in liver of dairy cows during the periparturient period. J Dairy Sci 2001;84(E. Suppl):E100-E112.

Melendez P, Risco CA. Management of transition cows to optimize reproductive efficiency in dairy herds. Vet Clin North Am Food Anim Prac 2005;21:485-501.

Grummer RR. Impact of changes in organic nutrient metabolism on feeding the transition dairy cows. J Anim Sci 1995;73:2820-2833.

Leblanc S. Monitoring metabolic health of dairy cattle in the transition period. J Reprod Dev 2010;56 (Suppl):S29â&#x20AC;&#x201C;S35.

Herdt TH. Ruminant adaptation to negative energy balance. Influences on the etiology of ketosis and fatty liver. Vet Clin North Am Food Anim Prac 2000;16:215-230.

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McArt JAA, Nydam DV, Overton MW. Hyperketonemia in early lactation dairy cattle: A deterministic estimate of component and total cost per case. J Dairy Sci 2015;98:2043–2054.

Duffield TF, Lissemore KD, McBride BW, Leslie KE. Impact of hyperketonemia in early lactation dairy cows on health and production. J Dairy Sci 2009;92:571–580.

Oetzel G R. Monitoring and testing dairy herds for metabolic disease. Vet Clin North Am Food Anim Pract 2004;20:651–674.

Tatone EH, Gordon JL, Hubbs J, LeBlanc SJ, DeVries TJ, Duffield TF. A systematic review and meta-analysis of the diagnostic accuracy of point-of-care tests for the detection of hyperketonemia in dairy cows. Prev Vet Med 2016;130:18–32.

10. Suthar VS, Canelas-Raposo J, Deniz A, Heuwieser W. Prevalence of subclinical ketosis and relationships with postpartum diseases in European dairy cows. J Dairy Sci 2013;96:2925-2938. 11. Rutherford AJ, Oikonomou G, Smith RF. The effect of subclinical ketosis on activity at estrus and reproductive performance in dairy cattle. J Dairy Sci 2016;99:4808-4815. 12. Liang D, Arnold LM, Stowe CJ, Harmon RJ, Bewley JM. Estimating US dairy clinical disease costs with a stochastic simulation model. J Dairy Sci 2017;100:1472-1486. 13. Melendez P, Goff JP, Risco CA, Archbald LF, Littell R, Donovan GA. Incidence of subclinical ketosis in cows supplemented with a monensin controlled-release capsule in Holstein cattle Florida, USA. Prev Vet Med 2005;73:33–42. 14. Duffield T, Rabiee A, Lean I. A meta-analysis of the impact of monensin in lactating dairy cattle. Part 1. Metabolic effects. J Dairy Sci 2008;91:1334-1346. 15. Drackley JK, Cardoso FC. Prepartum and postpartum nutritional management to optimize fertility in high-yielding dairy cows in confined TMR systems. Animal 2014;8,s1:5-14. 16. Chilean Meteorological Service. 2017. http://www.meteochile.gob.cl/PortalDMCweb/index.xhtml. Accessed Jan 31, 2017.

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17. Van Amburgh ME, Collao-Saenz EA, Higgs RJ, Ross DA, Recktenwald EB, Raffrenato E, et al. The Cornell Net Carbohydrate and Protein System: Updates to the model and evaluation of version 6.5. J Dairy Sci 2015;98:6361-6380. 18. Ferguson JM, Galligan DT, Thomsen N. Principal descriptors of body condition score in Holstein cows. J Dairy Sci 1994;77:2695-2703. 19. Kelton D, Lissemore K, Martin R. Recommendations for recording and calculating the incidence of selected clinical diseases of dairy cattle. J Dairy Sci 1998;81:2502â&#x20AC;&#x201C;2509. 20. Sheldon IM, Lewis GS, Leblanc S, Gilbert RO. Defining postpartum uterine disease in cattle. Theriogenology 2006;65:1516-1530. 21. SAS INSTITUTE. 2013. SAS/STAT Software: Change and enhancements through release 9.4 for Windows. SAS Institute Inc., Cary, NC. 22. Blis C. The transformation of percentages for use in the analysis of variance. Ohio J Sci 1938;38:9-12. 23. Dabdoub S, Shook G. Phenotypic relations among milk yield, somatic cell count and clinical mastitis. J Dairy Sci 1984;67:163-164. 24. Littell RC, Henry PR, Ammerman CB. Statistical analysis of repeated measures data using SAS procedures. J Anim Sci 1998;76:1216-1231. 25. Wagner JR, Green HB, Symanowski JT, Wilkinson JID, Davis JS, Himstedt MR, et al. Effect of monensin on feed intake, body weight, and body condition in dairy cows. J Dairy Sci 1999;82(Suppl 1):75. 26. Drong C, Meyer U, von Soosten D, Frahm J, Rehage J, Breves G, Danicke S. Effect of monensin and essential oils on performance and energy metabolism of transition dairy cows. J Anim Physiol Anim Nutr 2016;100:537-551. 27. Richardson LF, Raun AP, Potter EL, Cooley CO, Rathmacher RP. Effect of monensin on rumen fermentation in vitro and in vivo. J Anim Sci 1976;43:657-664. 28. Nagaraja TG, Newbold CJ, Van Nevel CJ, Demeyer DI. 1997. Manipulation of ruminal fermentation. In: Hobson PN, Stewart CS editors. The rumen microbial ecosystem. Second edition. Blackie Academic & Professional, England; 1997:523-632.

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29. Callaway TR, Martin SA. Effects of cellobiose and monensin on in vitro fermentation of organic acids by mixed ruminal bacteria. J Dairy Sci 1997;80:1126-1135. 30. Green BL, McBride BW, Sandals D, Leslie KE, Bagg R, Dick P. The impact of a monensin controlled-released capsule on subclinical ketosis in the transition dairy cows. J Dairy Sci 1999;82:333-342. 31. Duffield TF, Sandals D, Leslie KE, Lissemore K, McBride BW, Lumsden JH, Dick P, Bagg R. Efficacy of monensin for the prevention of subclinical ketosis in lactating dairy cows. J Dairy Sci 1998;81:2866-2873. 32. Compton CW, Young L, McDougall S. Efficacy of controlled-release capsules containing monensin for the prevention of subclinical ketosis in pasture-fed dairy cows. NZ Vet J 2015;63:249-253. 33. Grummer RR, Winkler JC, Bertics SJ, Studer VA. Effect of propylene glycol dosage during feed restriction on metabolites in blood of prepartum Holstein heifers. J Dairy Sci 1994;77:3618-3623. 34. Christensen JO, Grummer RR, Rasmussen FE. Bertics SJ. Effect of method of delivery of propylene glycol on plasma metabolites of feed-restricted cattle. J Dairy Sci 1997;80:563-568. 35. Kristensen NB, Raun BML. Ruminal and intermediary metabolism of propylene glycol in lactating Holstein cows. J Dairy Sci 2007;90:4707-4717. 36. Melendez P, Goff JP, Risco CA, Archbald LF, Littell R, Donovan GA. Pre-partum monensin supplementation improves body reserves at calving and milk yield in Holstein cows dried-off with low body condition score. Res Vet Sci 2007;82:349-357. 37. Zahra LC, Duffrield TF, Leslie KE, Overton TR, Putnam D, Leblanc SJ. Effects of rumen-protected choline and monensin on milk production and metabolism of periparturient dairy cows. J Dairy Sci 2006;89:4808-4818. 38. Fisher LJ, Erfle JD, Lodge GA, Sauer FD. Effects of propylene glycol or glycerol supplementation of the diet of dairy cows on feed intake, milk yield and composition, and incidence of ketosis. Canadian J Anim Sci 1973;53:289â&#x20AC;&#x201C;296. 39. Formigoni A, Cornil MC, Prandi A, Mordenti A, Rossi A, Portetelle D, Renaville R. Effect of propylene glycol supplementation around parturition on milk yield, 102

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reproduction performance and some hormonal and metabolic characteristics in dairy cows. J Dairy Res 1996;63:11-24. 40. Juchem SO, Santos FA, Imaizumi H, Pires AV, Barnabe EC. Production and blood parameters of Holstein cows treated prepartum with sodium monensin or propylene glicol. J Dairy Sci 2004;87:680-689. 41. De Koster JD, Opsomer G. Insulin resistance in dairy cows. Vet Clin North Am Food Anim Prac 2013;29:299-

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http://dx.doi.org/10.22319/rmcp.v10i1.4739 Article

Consumer evaluation and sensory analysis of Queso Bola de Ocosingo (Mexico) Mónica Agudelo-Lópeza Alfredo Cesín-Vargasb* Angélica Espinoza-Ortegac Benito Ramírez-Valverded a

Universidad Autónoma Chapingo- CIESTAAM, Km. 38.5. Carretera México- Texcoco. CP 56230. Estado de México, México. b

Universidad Nacional Autónoma de México-UAER, Coordinación de Humanidades, Av. Lázaro Cárdenas s/n esquina Felicitas del Río, Jiquilpan, CP 59510. Michoacán, México. c

Universidad Autónoma del Estado de México- ICAR, Toluca, Estado de México. México.

Colegio de Postgraduados Campus-Puebla. Puebla, México.

Corresponding author: alfredo.cesin@gmail.com.

Abstract: Information on consumer acceptance of and preference for a product are vital to developing marketing strategies. An analysis was done of consumer acceptance of and preference for Queso Bola de Ocosingo, an artisanal cheese, aged for one of three periods: fresh, 21 d and 45 d. Sensory testing panels were organized at three food-related scenarios: a gourmet foods event; a rural culture fair; and a culinary exhibition. A total of ninety (90) panelists participated. Parametric and nonparametric statistical tests were applied to the data. Comparisons of panelist responses considering the scenarios and panelist socioeconomic characteristics found that panelists reporting lower income and educational levels more highly valued visual characteristics and preferred fresher cheeses. Panelists reporting higher income and educational levels appreciated cheese aroma and taste attributes influenced by aging period. Queso Bola de Ocosingo has production and cultural characteristics in common with other artisanal cheeses produced in Mexico, and promoting its consumption can contribute to preserving the country’s culinary heritage.

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Key words: Acceptance, Differentiated foods, Gastronomic fairs, Untrained panelists, Preference.

Received: 04/01/2018 Accepted: 21/02/2018

Introduction

Over the last few decades increasing emphasis has been placed on preservation and promotion of the production and consumption of local products. This partially responds to consumer fears of excessively industrialized food production and lack of knowledge on the origin of food; these have driven consumers to concentrate on external food product attributes such as price, physical appearance, labels and seals(1,2). Several authors have mentioned the importance of restoring confidence in food through a return to local food sourcing and production, thus protecting cultural diversity(3,4). A new segment of consumers has emerged that is concerned with the way food is produced and which has the ability to manage its own food resources. These consumers can potentially contribute to recovering the traditional meanings behind the producer-consumer relationship. For example, they have played a role in the reactivation of local markets, food fairs and other types of gastronomic events as scenarios for product evaluation(1,4-6). Research on changes in consumer preferences has been done largely in Europe(7-10). However, consumers are also changing in Latin America where their characteristics and the main reasons for their preferences remain unknown. This is mostly due to the fact that studies to date in developing countries have mainly considered the effects of the entrance of regional agriculture into the world market, and its implications in traditional forms of production and changes within local populations, especially in terms of diet(1). A need exists to study consumer tastes and preferences for local products such as Mexican artisanal cheeses. Forty different cheeses have been described in Mexico. Many of these are made in poorer regions following traditional artisanal techniques and are marketed mainly in local markets, thus fulfilling an important role in regional economic development(11). Queso Bola (ball-shaped cheese; QBO) is a type made by ten artisanal producers in the city of Ocosingo, in the state of Chiapas, in southern Mexico. Its center is a ball of acid cheese made with double cream raw cowâ&#x20AC;&#x2122;s milk, and this is wrapped with a double lining of cheese made from skim milk. The traditional process begins when the fresh raw milk is received. Cream is added to soften 105

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the cheeseâ&#x20AC;&#x2122;s internal texture, and it is then curdled and the whey removed. It forms a paste which is placed in blanket and hung to age for at least 21 days before being wrapped with skim cheese. The blanket is changed periodically to prevent product contamination. Once aged, balls cheese are shaped and wrapped with two layers of a stringy skim cheese. This protects the internal aged cheese from contamination, allowing its marketing at room temperature(11,12). Competition with different types of industrially-produced cheeses that cost less, as well as the reputation and high demand for QBO, have caused negative changes in the QBO production process. These include shortening of curd acidification time and increasing inventory rotation, both of which reduce expenses and increase profits. The local market has responded by offering three types of QBO, a fresh type, one aged the traditional 21 days and another aged 45 d. However no differentiation is made between these types in terms of labelling (especially between the fresh and 21-d aged cheeses) or price. This compromises the gastronomic heritage of this traditional product because the fresh type is essentially a different product in which the curd is not allowed to acidify for the time required in traditional processes. Properly aging QBO requires experience and knowledge, and is vital to ensuring cheese quality. Because this cheese is made with raw milk, aging is also important to lower risk to consumer health. Studies have shown the QBO aged for 21 d to have an acceptable microbiological profile(12,13), but fresh QBO has not been studied. Evaluations are needed of consumer acceptance of fresh and aged QBO, followed by microbiological analyses to determine how safe they are for consumers. This could help to preserve this artisanal cheese and ensure consumers receive healthy food. The present study objective was to evaluate consumer acceptance of and preference for three types of QBO (fresh, aged 21 d and aged 45 d), and analyze the implications of these preferences.

Material and methods Panelist selection and evaluation scenarios

Panelists were untrained consumers, who are suitable for spontaneous, fast responses unconditioned by previous training(14-16). Tests were done in three scenarios, each an event which attracts different kinds of attendees. The Gourmet Show (GS) is held every year at the World Trade Center in Mexico City and is aimed at bringing together the suppliers of quality cooking products with potential consumers. The National Rural Culture Fair (FCR) is held annually at the Autonomous University Chapingo and brings together local producers from all over Mexico. Local handcraft and food products are on exhibit and for sale, and there is a food court for the sale of 106

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prepared food from all the participating states. The annual Gastronomic Exhibition (MG) of the Institute of Agricultural and Rural Sciences (ICAR) of the Autonomous University of the State of Mexico commemorates The International Day of Food. Attendees are largely university students, teachers and administrative personnel. Scenario choice was done for convenience, given the ease of access to apply sensory tests. Recommended panel size for this kind of sensory test is 50 to 500 panelists. These are usually recruited because they are product users or are familiar with the products to be evaluated(15,17). A total of ninety (90) panelists were interviewed among the three scenarios: 34.4 % in the GS; 30 % in the FCR; and 35.6 % in the MG. Although most had no prior knowledge of QBO, they were chosen under the assumption that attendees at food events are more likely to be open to trying handmade local products. This was also an advantage because QBO is not widely known nationwide so the spontaneous responses of the untrained panelists were more probable to approximate those of the general population(15).

Cheese samples

In an effort to avoid process-related biases, the QBO samples used in the evaluations were taken from cheeses prepared in the same factory. Three QBO types were tested: 1) fresh cheese, curd acidified for three days before wrapping, 17- to 19-day total production time (hereinafter â&#x20AC;&#x153;fresh cheeseâ&#x20AC;?); 2) aged cheese, 21-d curd acidification prior to wrapping, 35- to 37-day total production time (hereinafter 21-d cheese); and 3) aged cheese, 45-d curd acidification before wrapping, 59- to 61-d total production time (hereinafter 45-d cheese). Tests were done by placing randomly-coded QBO samples on a plate (to prevent any preconceptions based on ageing time), along with water, bread and fruit (green apples) to clean the panelistsÂ´ taste buds prior to evaluating the samples, and between samples.

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Tests

Acceptance and preference tests were applied. The first measures perception of sensory characteristics using a scale while the second merely requires selection of the most pleasing sample(15). After evaluating the samples panelists were asked for information on their place of origin, gender, age and income to facilitate statistical analyses. Acceptance was evaluated considering ten attributes: external and internal appearance; external and internal color; texture in hand; smell; texture in mouth; taste; aftertaste; and price. Each attribute was graded on a five-point scale (1: Do not like; 2: Like somewhat; 3: Indifferent; 4: Like; and 5: Like very much); this was accompanied by a visual scale to expedite the evaluation process and avoid any discrimination against panelists lacking formal education(18). Preference was determined by panelists indicating their order of preference of the evaluated samples. After both tests were done panelists were informed of the characteristics of each cheese type and how it is made and asked about their disposition to buy each type and to pay a different price for their preferred cheese (range was Âą 60 % of base price per 300 g piece).

Statistical analysis

Validation of question reliability was done with the Cronbach alpha coefficient, considering the thirty attributes included in the three evaluations. The resulting value (0.935) indicated the questionnaire to be reliable for gathering data on cheese characteristics. This analysis was done with the SPSS ver. 16 statistical package. Data were analyzed using various statistical techniques, all applied with the Infostat statistical package(19,20). Comparison of attributes between cheeses was analyzed with the Friedman test since each panelist in all three scenarios tested three samples and evaluated each attribute, meaning they are related samples. Results presentation was facilitated by classifying attributes as visual (external and internal appearance, external and internal color) or other (texture in hand, smell, texture in the mouth, taste and aftertaste). Perception of price was presented separately because it is not a sensory attribute, but is still fundamental to generating a complete product evaluation(21,22). A KruskalWallis test was applied to compare differences between the three scenarios in terms of cheese attributes. Parametric and non-parametric statistical tests, based on variable measurement scale, were used to identify cheese preferences. Quantitative variables were compared using an analysis of variance (ANOVA), with a Tukey test to identify differences between means, and a chi-square test for differences between nominal values. Finally, a Kruskal-Wallis test was applied to identify any differences between scenarios in willingness to pay a price other than the base price. 108

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Results and discussion

Panelist socioeconomic profile

Most attendees at the GS were from Mexico City and had the highest education and income levels of the three scenarios. Those at the FCR were from different parts of Mexico and had the lowest average education level. At the MG, almost all attendees were students from the State of Mexico, and this group had the lowest average age (Table 1).

Table 1: Consumer profile characteristics by evaluation scenario Variable/ Scenario

FCR

Place of origin (%): Mexico City 48.4 26 State of Mexico 38.7 33.3 Other states 12.9 40.7 Age, years 32.5±11.1 (ab) 34.4±17.2 (b) Gender (%): Male 51.6 51.9 Female 48.4 48.1 Education level, 17.3±3.4 (b) 12.4±2.8 (a) years Occupation (%): Professional 30 7.4 Independent 20 25.9 Worker Employee 16.7 25.9 Student 33.3 40.7 Monthly income*

1,077±995 (b)

442±347 (a)

MG 3.1 81.3 15.6 26.6±6.3 (a)

Statistic

Χ2= 26.722

<.0001

F= 3.43 Χ2= 0.525

<.037 .776

F= 27.169

<.001

Χ2= 36.865

<.001

Χ2= 8.98

<.001

43.7 56.3 16.2±2.5 (b) 9.4 0 0 90.6 415±243 (a)

GS = Gourmet Show; FCR = Rural Culture Fair; MG = Gastronomic Exhibition; a,b Different letters in the same row indicate significant difference (P<0.05); *US dollars at MXP 18.492/USD 1. Source: Banco de México (http://www.banxico.org.mx/dyn/portal-mercado-cambiario/index.html). Consulted 18 July 2016.

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Attribute perception by cheese type and evaluation scenario

Overall consumer perception by cheese type did not differ between types (Table 2). Because QBO is a sui generis product among Mexican artisanal cheeses(11), it was attractive to the panelists, which influenced their positive evaluation of its attributes.

Table 2: Attribute perception by cheese type Average* Attributes Visual Other Perception of price

Fresh cheese

21-d cheese

45-d cheese

3.95 3.53 3.29

4.01 3.48 3.41

3.92 3.43 3.44

0.39 1.14 1.35

0.6789 0.3208 0.2619

Ordinal type measurement scale; average used to illustrate tendency of attribute measurement. T 2= Friedman test.

Visual attributes received better overall evaluations, probably reflecting the fact that the panelists placed more importance on the most easily perceived characteristics. This could be an effect of the global food supply model which is based on symbols and signals to more easily bridge the gap between producer and consumer(1,23). Otherwise, this absence of differences between samples may also be attributed to QBO being an unconventional and striking cheese (only 15.6% of panelists had prior knowledge of it), which would coincide with the largely positive evaluation of all attributes. Since the participants had no previous experience as food evaluation panelists, they failed to detect sensory differences between samples. Similar results have been reported in a study in which goat cheeses aged for different periods were sensory evaluated, and in which consumers who were unfamiliar with cheeses of intense aroma and flavor could not easily recognize sensory differences between samples(24). Comparison of evaluations by scenario and cheese type identified differences between the different cheese samples for visual attributes. However, for other attributes and perception of price only the 45-d cheese differed from the other types (Table 3).

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Table 3: Comparison of sensory attributes by scenarios and cheese type Average* Attributes GS

FCR

Fresh cheese Visual

3.86 (a)

3.68 (a)

4.27 (b)

8.98

0.0105

Other

3.48

3.56

3.55

0.09

0.9547

Perception of price

3.13

3.15

3.56

2.37

0.279

4.28 (b) 3.48 3.63

6.77 1.07 5.03

0.0315 0.5824 0.0652

4.11 (b) 3.27 (a) 3.38 (ab)

6.07 11.25 10.15

0.0457 0.0035 0.0046

Visual Other Perception of price

3.99 (ab) 3.63 3.58

Visual Other Perception of price

4.04 (ab) 3.93 (b) 3.97 (b)

21-d cheese 3.72 (a) 3.32 2.96 45-d cheese 3.64 (a) 3.04 (a) 2.93 (a)

Ordinal type measurement scale; average used to illustrate tendency of attribute measurement. H= Kruskal Wallis test; ab Different letters indicate statistical difference (P<0.05).

Among the scenarios, FCR attendees gave the lowest evaluations to all three cheeses, much like MG attendees, who found visual attributes to be more important for all cheese types. At the GS, however, attendees gave better evaluations to the other attributes and perception of price for the 45-d cheese. The GS panelists also exhibited more consistent evaluations, with higher ratings as cheese age increased. Trends were not as clear in the MG and FCR scenarios because the most positive ratings were generally given the fresh cheese with ratings decreasing with cheese age. These differences in cheese attribute perception based on cheese age may be explained by variations in panelist characteristics and the possibility that some panelists may have had more regular access to this type of product. Panelists in the FCR were the most diverse and had the lowest education level while the MG panelists were mostly students and the youngest group on average. Both these groups had lower income than the GS panelists (Table 1). That panelists from lower-income levels may place greater value on the characteristics of fresher cheeses is plausible since fresh cheeses are common in Mexico and are generally cheaper(25,26). Even though the MG panelists were all studying degrees involving evaluation of local products (e.g. tourism, gastronomy), they still placed more importance on visual attributes. Perhaps this was because they were younger and may not have had the experience necessary to distinguish and evaluate products based on intrinsic properties. Panelists at the GS, in contrast, had higher education and income levels, better fitting the profile of consumers who search for and value unique, quality foods. Consumers of this type typically 111

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appreciate â&#x20AC;&#x153;fine foodsâ&#x20AC;? and seek sensory experiences not offered by mass-produced foods (although these can be made with high quality raw materials). Often they purchase their food at markets selling only specialty or artisanal products. It is this greater contact with differentiated products that most probably allows these consumers to evaluate products based on attributes beyond the visual. Two types of consumers can apparently be identified among the panelists. The first make choices based on intrinsic attributes associated with a certain degree of knowledge of and experience with a product or similar products; this type is best represented by the GS panelists. The second type largely consider visual aspects, including product appearance, as a kind of codification for making purchase decisions; the MG and FCR panelists best represent this type(6,22). Perception of price differed notably for the 45-d cheese (Table 3). Taking into account that all three cheese types were assigned the same price, the GS panelists gave a lower valuation to the price of the fresh cheese and a higher one to the 45-d cheese. The latter provided them with a richer sensory experience and they therefore felt it had better value for price than the other types. Among the FCR and MG panelists, the opposite was true in that they gave better valuations to the price of the fresh and 21-d cheeses than to the 45-d cheese. They are presumably not accustomed to products with strong aromas and flavors, meaning the 45-day cheese seemed them expensive.

Comparison of preference results by scenario

An important component of the present study was to evaluate if the perception of attribute results support panelist preference. The preference results suggest the existence of specific consumers for each cheese type. Preferences differed between scenarios (Ď&#x2021;2=8.121; P=0.087), particularly between the GS and FCR panels (Figure 1). The former clearly preferred the 45-day cheese while the latter preferred the fresh cheese; the MG panel exhibited no clear preference.

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Figure 1: Overall preference by scenario

Fresh

21-d

45-d

52% 44%

34%

38%

36% 30%

28%

26%

34% 28%

13%

Overall preference

FCR

GS= Gourmet Show; FCR= National Rural Culture Fair; MG= Gastronomic Exhibition .

Consumer preference can also be explained by considering demographic characteristics, consumer accessibility to and frequency of contact with differentiated products, and the influence of the evaluation scenarios on panelist’s individual experiences(2). The preference for a particular cheese was linked with education and income levels (Table 4).

Table 4: Consumer profile characteristics by preferred cheese type Variable/Preferred cheese type Place of origin (%): Mexico City State of Mexico Other states Age, years Gender (%): Male Female Education, years

Fresh cheese

21-day cheese

45-day cheese

24 22.6 29.4 44 51.6 58.8 32 25.8 11.8 31.12±10.9 27.97±12.3 33.62±13.1 48 52 14.67±3.7 (a)

45.2 54.8 14.71±3.2 (ab) 113

52.9 47.1 16.82±3.3 (b)

Statistic

Χ2=3.866

0.424

F=1.723 Χ2=0.404

0.185 0.834

F=4.059

0.021

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Occupation (%): Professional Independent worker

16 16

6.5 16

24.2 12.1

Employee Student

20 48

9.7 67.7

12.1 51.5

Monthly income*

463±255 (a) 467±471 (a) 945±948 (b)

Χ2=5.769

0.451

F=4.617

0.013

*US dollars at MXP 18.492/USD 1. Source: Banco de México (http://www.banxico.org.mx/dyn/portalmercado-cambiario/index.html). Consulted 18 July 2016.

A preference for 45-d cheese clearly coincided with higher education and income levels. The preference per scenario results also support the acceptance tests results, suggesting the existence of two consumer types: one of lower education and income level which accepts and prefers the fresh cheese, these panelists were in a scenario in which gastronomy was presented as an aspect associated with general culture (i.e. FCR); and another of higher education and income levels which accepts and prefers more mature cheeses, these were panelists in a gourmet food event who likely had more specialized sensibilities (i.e. mainly GS panelists). In the MG scenario the preference results did not tend towards a particular type, suggesting that panelists were a mixture of consumer types. Food choices are also influenced by consumer experience(22). Considering this the panelists that preferred the fresh cheeses are probably consumers who prefer milder cheeses because they are commonly found in the markets were they shop(24). Due to the nature of the FCR, the attendees were probably consumers who share characteristics similar to average Mexican consumers; that is, they are more inclined to consume fresh cheese due to its lower price and greater availability(26). The preferences of the GS panelists highlight that consumption of aged cheeses is more likely limited to those regions of the country where they are produced, making them a traditional food stuff, and to gourmet markets in large urban areas where specialized fairs play a key role in product exposure. The evaluation scenarios themselves, as an element in the social context that produces individual expectations and experiences, may have influenced the results. They can contribute previous codification that provides indirect information on the expected quality of the products on offer in a specific scenario(2,27). This may explain why consumers at the GS placed more value on intrinsic attributes and preferred the most aged cheese; they are at an event centered on differentiated gastronomy and they hope to find products offering rich sensory experiences. The FCR, in contrast, is a more general and diverse event including cultural events such as a book fair, food exhibition and handcrafts, and attracted consumers that preferred fresh cheeses. Acceptance of the three cheese types at the MG did not differ, perhaps because the students at the event studied degrees such as tourism and gastronomy, and are thus sensitized to local products, but lacked the knowledge and experience needed to perceive the differences between the cheese samples. 114

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The attribute perception and cheese preference results reflect important aspects of QBO and its potential consumers. These can be analyzed to identify areas of opportunity and improve QBO marketing strategies; for instance, considering cheese maturation days, regional origin and promoting local products at food-agriculture fairs and gastronomic events (28). Panelists from an apparently higher socioeconomic class preferred the 45-day cheese, highlighting the potential for marketing to this consumer sector within the region where QBO is produced; for instance, the tourist destination of San CristĂłbal de las Casas is relatively near Ocosingo(28). The other two groups tended to appreciate QBO for its visual attributes and freshness, and were apparently from lower socioeconomic classes, much like the greater part of Mexicoâ&#x20AC;&#x2122;s population. This consumer sector can be offered a fresher cheese that also happens to be cheaper, an appealing quality according to the perception of price results.

Purchase intention and willingness to pay a different price for the preferred cheese type Before information on QBO was provided the panelists they gave the lowest ranking to perception of price (Table 3). Providing product information can transform consumer perception, a tendency reflected in willingness to purchase the product and to pay a preferential value(21,29). This was observed in all three scenarios; panelists were more willing to buy their preferred cheese type after they had received information on how it is produced (93.5 % in the GS; 87 % in the MG and 74 % in the FCR). Of note is that the GS panelists were willing to pay more than the market price of QBO, those at the MG were willing to pay near the market price and those at the FCR less than the market price. The differences between the willingness of the different groups to pay for their preferred cheese was significant for the fresh and 21-d cheeses and highly significant for the 45-d cheese (Table 5).

Table 5: Comparison between scenarios for willingness to pay for preferred cheese type Willingness to pay Fresh cheese 21-d cheese 45-d cheese

Average (proportion over base price)* GS 0.15 0.12 0.18 b

FCR -0.05 -0.08 -0.15 a

MG -0.01 0.00 -0.04 a

4.77 0.0840 4.76 0.0833 11.91 0.0022

Ordinal type measurement scale; average used to illustrate tendency of attribute measurement. GS = Gourmet Show, FCR = National Rural Culture Fair, MG = Culinary Exhibition; H = Kruskal-Wallis test; ab Different letters indicate difference (P<0.05). 115

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Willingness to pay a higher price was at least partially associated with panelist purchasing power (Table 5), but could also be attributed to educational level and access to differentiated quality products. Only the GS panelists were willing to pay additional value for any of the three tested cheese types, particularly for the 45-d cheese (18 % additional, on average). In the other two scenarios, in which the lowest income levels were recorded (Table 1), panelists did express willingness to pay for this same cheese type, but at a price below the base price. Although price and income level clearly influenced purchase decision in the present study, other factors intrinsic to the product may have a greater influence on purchase decision, but this implies that the consumer has the possibility of acquiring knowledge on the product. Flavor is reported to be the most important attribute when determining product quality and willingness to buy a local food as long as the consumer can live the sensory experience. However, when sensory information is not available on a product other factors such as price, brand, packaging and the property of being artisanal or local come into play(2,30,31). Once panelists had chosen their preferred cheese and expressed their intent to purchase, they were asked about their principal reasons for buying it. Flavor was the main reason for 55.4 % of the panelists, the properties of its being unique and artisanal for 20.7 %, appearance, curiosity and its being a local product for 24 %, and price for just 6.5 %. Overall, for the panelists participating in the sensory evaluation, taste was more important than price, although the prospect of paying added value was conditioned by socioeconomic variables and individual experiences.

Conclusions and implications

Knowledge of consumer tastes and preferences provided by studies like the present allow traditional food producers to access more profitable specialty food markets, and contribute to maintaining traditions. In this case the QBO aged over 21-d was perceived to be richer than fresher types and was highly valued in a gourmet foods market sector. The fresher types also have a market since the largest proportion of panelists preferred them. This variety of artisanal cheese is made with raw milk, meaning that, even though there are consumers who prefer the different types, each type needs to be tested to ensure it meets microbiological quality standards and poses no consumer health risk. The QBO cheese aged 21 d requires longer curd acidification periods, therefore attains lower pH levels and poses a minimal threat to consumer health. The microbiological quality of the fresh cheese is yet unknown and may represent a risk to consumers. This is cause for concern since any pathology linked to consumption of fresh QBO of poor microbiological quality could negatively affect the reputation of the 21-d and 45-d cheeses, which are richer and most likely safe. 116

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Currently a proportionally larger amount of fresh QBO is marketed highlighting the need to conduct research on the minimum curd acidification time required to guarantee the safety of this cheese type.

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http://dx.doi.org/10.22319/rmcp.v10i1.4547 Review

Factors affecting the ruminal microbial composition and methods to determine microbial protein yield. Review

Ezequias Castillo-Lopeza* María G. Domínguez-Ordóñezb

Facultad de Estudios Superiores Cuautitlán, Medicina Veterinaria y Zootecnia, Universidad Nacional Autónoma de México, Cuautitlán, Estado de México. b

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

*Corresponding author: ezequias@huskers.unl.edu

Abstract: Microbial protein synthesized in the rumen is a major contributor of metabolizable protein. Thus, accurate estimation of microbial protein is essential in ruminant nutrition. The objective of this review is to describe the microbial composition, major factors affecting its yield and methods to estimate microbial protein flow to the intestine. The use of novel molecular techniques to elucidate the ruminal microbiome and improve methods for estimating microbial protein are discussed. Bacteria, protozoa, fungi and archaea compose the ruminal microbiome. Main factors affecting microbial protein synthesis are availability of carbohydrates, ruminally degradable protein, dietary fat, and ruminal pH. Major microbial markers used to estimate microbial protein synthesis are total purines, diaminopimelic acid and labeled nitrogen; in addition, DNA through real-time PCR is being tested for the estimation of bacterial, protozoal and yeast protein separately. The main difficulty in the estimation of microbial protein flow is obtaining representative microbial pellets from the rumen, which are used as reference to establish the ratio of marker/nitrogen. Detailed phylogenetic analysis using High-throughput DNA sequencing has recently revealed drastic

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taxonomic differences between fluid-associated bacteria and bacteria from whole intestinal digesta contents. For example, ruminal fluid contains less Fibrobacteres and Proteobacteria, but more Firmicutes compared to whole intestinal digesta. This demonstrates the need of developing effective bacterial collection procedures for obtaining representative ruminal microbial reference pellets to prevent bias on the estimation of the contribution of microbial protein to the intestinal supply of metabolizable protein. Key words: Microbial protein, Metabolizable protein, Marker, Rumen, DNA.

Received: 04/07/2017 Accepted: 06/03/2018

Introduction

Metabolizable protein is the true protein absorbed by the intestine supplied by microbial protein, rumen undegradable protein and, to a minor extent, sloughed (endogenous) protein(1); with microbial protein usually representing the largest source of the metabolizable protein supply(2,3). When absorbed, this protein may be utilized for maintenance, growth, reproduction or lactation. Therefore, it is important for nutritionists to understand the nature, factors affecting, and appropriate methods for estimating the flow of microbial protein to the small intestine. The estimation of microbial protein synthesis has been carried out by a variety of methods, including the purine analysis(4); the diaminopimelic acid method(5), and isotope incorporation into the microbial cells(6). Recent advances in molecular techniques have allowed estimation of microbial protein using microbial DNA through real-time PCR(7,8,3), which is particularly important when rations include ingredients containing yeast DNA from Saccharomyces cerevicieae, such as those from the ethanol industry(9) or when researchers need to estimate the contribution of protozoa to total microbial protein(7). Quantification of microbial protein requires the isolation of microbial pellets from the rumen, which are used as reference to establish de ratio microbial marker/nitrogen. However, if the isolated reference pellets are not representative of whole ruminal contents, the estimation will be biased(10). Differences between solid-associated bacteria and liquid-associated bacteria 121

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have been assumed longtime ago(11); however, detailed phylogenetic differences between these fractions have remained largely unknown. The use of cutting-edge technology such as high-throughput microbial DNA sequencing in combination with bioinformatics(12,13) has provided new insights into the ruminal microbiome and have revealed drastic differences between liquid- and solid-associated bacteria(14). Studies have compared the use of conventional microbial markers(4,11,15) or factors affecting microbial growth. In addition, recent reports have evaluated equations to predict postruminal microbial protein flow(16,17,18). However; to the authorsâ&#x20AC;&#x2122; knowledge, there is a lack of studies integrating recent advances and findings from the use of molecular techniques in ruminal microbiology, to improve the understanding on factors affecting and appropriate procedures to quantify microbial protein synthesis and its contribution to metabolizable protein. Therefore, the objective of this review is to describe the microbial composition, major factors affecting its yield and methods to estimate microbial protein flows to the intestine. In addition, the use of high-throughput DNA sequencing to improve our understanding on the microbiome and factors affecting quantification of ruminal microbial protein and its flow to the small intestine is discussed.

Ruminal microorganisms and their importance

The reduced, anaerobic environment in the rumen allows the development of different kinds of microbes composed primarily of bacteria, protozoa, fungi and archaea(19,20).

Bacteria

In 1994(20) around 200 species of bacteria had been cultured. Recent reports using highthroughput DNA sequencing have revealed the presence of 13 major bacterial phyla in the rumen, that include 40 bacterial orders, around 80 bacterial classes, at least 180 bacterial families, around 320 bacterial genera and more than 2,000 bacterial operational taxonomic units(21,14). Bacterial density in the rumen is found in the range of 107 to 1010 cells/mL of ruminal fluid. The most abundant bacterial phyla are Bacteroidetes and Firmicutes, which 122

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account for at least 75 % of total bacterial population. The most abundant ruminal bacterial genus is Prevotella representing approximately 20 % of the bacterial community(14,22,23).

Protozoa

More than 20 species of protozoa had been identified(20), their concentration in the rumen is approximately 106 cells/mL. Although the number of protozoal genera is less than that of bacteria, protozoa are physically more massive than bacteria and they may account for approximately half of the total ruminal microbial biomass(19). Protozoal nitrogen ranges from 4.8 to 12.7 % in the rumen and from 5.9 to 11.9 % in the duodenum(3,7). Novel reports using high-throughput DNA sequencing have showed that predominant protozoal genera are Entodinium, Epidinium, Metadinium, Diploplastron, Polyplastron and Diplodinium(24). Over 90 % of the protozoal population in the rumen belong to the class Litostomatea which include two groups, Haptoria and Trichostomatia. The Trichostomatia subclass contains Entodinium one of the most studied genera, and which accounts around 89 to 91 % of the protozoal population(24).

Fungi

Fungi have been found associated with the more slowly digested fractions of plants, and act as initial colonizers of lignocellulose and increase the bacterial digestion rate of dietary fiber by disrupting lignified plant cell walls(19). They are small flagellated organisms and they were first misclassified as flagellated protozoa. However, later, it was observed that those flagellates had a cell wall that contained chitin and a reproductive life cycle typical of fungi. The flagellates are fungal zoospores that eventually colonized plant surfaces to produce a mycelium. The mycelium gives rise to sporangia that release more zoospores, and the cycle continues. The fungi increase their residence time by attaching to feed particles. For this reason, it has been difficult to estimate their biomass in the ruminal content(20). DNA sequencing has recently revealed the presence of 5 major fungal phyla, which include 55 fungal genera. Predominant genera are Ascomycota (27 %), Basidiomycota (3 %), and Neocallimastigomycota (1 %)(25). 123

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Archaea

The archaeal population includes microorganisms that were thought to be bacteria. However, molecular analysis of their DNA has revealed that they belong to a different domain(26). The density of archaea in the rumen has not precisely been determined. These microorganisms play a special role on feed efficiency given their participation in methane formation, which takes place using carbon dioxide and hydrogen(27). Because methane emitted into the environment contributes to global warming, abatement of the production of this gas in ruminants is one of the main targets of greenhouse gas mitigation practices for the livestock industry(28). Recent findings from high-throughput DNA sequencing has revealed that the most abundant archaeal phylum in the rumen is Euryarchaeota, which accounts for around 99 % of total ruminal archaeal population. Ten archaeal genera have been detected in the rumen, and the most abundant genus is Methanobrevibacter, representing approximately 91 %(26). The importance of microbial protein as a major source of metabolizable protein with regard to the nutritional state of ruminants and has been recognized a longtime ago(19). Ruminal bacteria and protozoa contribute to the majority of the metabolizable protein reaching the duodenum. The microbial protein synthesized in the rumen meets at least 50 % of the amino acid requirements of ruminants in various states of production(1,29,30). Under most dietary conditions, microbial protein accounts for 50 to 85 % of the total amino acid nitrogen entering the small intestine(5). Other studies suggest that microbial protein synthesized in the rumen contributes from 40 to 90 % of the protein reaching the small intestine, despite the fact that up to 50 % of the microbial protein synthesized could be degraded to ammonia nitrogen in the rumen(30). Furthermore, the relative contribution of microbial protein reaching the small intestine depends mainly on the quality and solubility of nitrogen intake(30). This contribution may range from 1,262 to 2,137 g/d in the adult dairy cow, and from 473 to 1,300 g/d in beef cattle; in addition, the concentration of microbial protein in duodenal digesta of sheep has been found to range from 130 to 162 mg/g DM (Table 1).

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Table 1: Comparative data of microbial protein reaching the small intestine measured by different methods Source Glenn et al.(86) Ipharraguerre et al.(89) Cooper et al.(85) Sylvester et al.(83) Schwab et al.(90) Moorby et al.(88) Hristov et al.(84) Leupp et al.(87) Belanche et al.(8) Belanche et al.(8) Castillo-Lopez et al.(5) Castillo-Lopez et al.(5) Castillo-Lopez et al.(3) Castillo-Lopez et al.(3)

Marker used1 PB PB PB rDNA LN Cytosine LN PB PB rDNA DAPA rDNA PB rDNA

Type of animal Holstein steers Dairy cattle Beef cattle Dairy cattle Dairy cattle Dairy cattle Dairy cattle Beef cattle Sheep Sheep Beef cattle Beef cattle Dairy cattle Dairy cattle

Microbial protein reaching the duodenum 1,093 g/d 1,825 g/d 1,300 g/d 1,693 g/d 2,137 g/d 944 g/d 1,906 g/d 545 g/d 162 mg/g DM 130 mg/g DM 473 g/d 561 g/d 1,881 g/d 1,262 g/d

PB= Purine bases; DAPA= Diaminopimelic acid; LN= Labelled nitrogen ( 15N).

Moreover, ruminal microbes are a major source of other nutrients for the ruminant(31). Major chemical components of ruminal microorganisms are nitrogen, carbohydrates, lipids and ash(32) (Table 2). The content of organic matter, nitrogen and amino acids in mixed rumen bacteria increase by decreasing the level of forage in the diet(19). These variations could be due to difference in the species of bacteria resulting from different diets(33). High-throughput DNA sequencing has recently confirmed this suggestion(21). An increase in the organic matter and nitrogen concentrations of the protozoal population observed in response to an increase in the amount of starch in the diet has been observed(19), which may be due to changes in the protozoal community, recently confirmed using molecular methods(34).

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Table 2: Nutrient composition of ruminal microorganisms(30) isolated through centrifugation Centrifugal fraction A1 62 100 91 92 116

Nutrient content (g/kg DM) Moisture Nitrogen Carbohydrate Lipid Ash 1

B2 50 103 93 94 98

SEM3 2.3 1.6 7.1 6.7 4.0

Supernatant centrifuged at 19,000 Ă&#x2014;g for 8 min considered to contain the bulk of microorganisms. 2 Supernatant re-centrifuged at 19,500 Ă&#x2014;g for 15 min considered to harvest virtually all remaining microorganisms. 3 Standard error of the mean.

Factors influencing the synthesis of ruminal microbial protein

Ruminal microbial growth depends on their capability to degrade and ferment feed ingredients. Bacterial cells have diverse transport systems for taking up low-molecular weight and soluble nutrients such as sugars(35). Because feed ingredients are primarily composed of complex polymers such as starch, protein and cellulose, these polymers are first degraded by extracellular enzymes to low molecular weight substances, which are then utilized by bacteria. The amount of in vivo bacterial yield ranges from 1.9 to 3.0 mg per 100 mg of organic matter truly digested(36). Some of the main factors that influence ruminal microbial protein synthesis include availability of dietary carbohydrate, ruminally degradable protein, dietary fat, ruminal pH and feed intake(37). The model used to predict microbial protein (g/d) flow to small intestine is related to total digestible nutrientes, MN= 0.0166TNDkg(38); or MCP= 0.087TDNintake+42.73(18).

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Effect of dietary carbohydrates

Efficient utilization of degraded dietary nutrient requires that the energy from the fermentation of dietary organic matter be supplied at a rate which matches the synthetic abilities of the ruminal microbes. Readily available carbohydrates such as starch are effective for increasing utilization of degraded nutrients and increasing microbial growth(39). In addition, there is an increase in microbial growth in continuous cultures (15.0 to 19.5 g microbial protein/100 g DM digested) in response to increased dietary nonstructural carbohydrate levels (32 to 49 % of DM)(39). Thus, the type of dietary carbohydrates may influence bacterial metabolism. Feedlot cattle fed high-carbohydrate diets are virtually free of protozoa. However, other investigations carried out utilizing wheat(40) and corn- and sorghum-based diets(41) have showed high concentrations of protozoa in the rumen with highgrain diets. The shifts in the bacterial and protozoal population due to dramatic increase in dietary starch(21) is presumably due to the decrease in ruminal pH(38).

Effect of ruminally degradable protein

High producing ruminants are generally unable to meet their requirements for amino acids from rumen microbes alone(42). Therefore, inclusion of ruminally undegraded protein in the diet may increase the total amino acid supply to the small intestine and modify the duodenal amino acid profile. However, feeding low-degradable protein sources may also limit microbial fermentation, resulting in reduced supply of energy and microbial amino acid to the host animal. Ruminal degradation of dietary protein is a time-dependent process, and rate of degradation relative to rate of passage is a critical dynamic property affecting the amount of ruminally undegraded protein escaping the rumen(43). A diet with 5.3 % ruminally degradable protein results in a higher bacterial nitrogen flow (415 g/d as opposed to 365 g/d when 4.8 % ruminally degradable protein is fed)(42). More ruminally available nitrogen likely improves the efficiency of energy utilization stimulating the growth of the bacterial population(43). This indicates that if energy from carbohydrate for microbial growth is not limiting, the resulting peptides and amino acids are used for microbial protein synthesis more efficiently. However, if carbohydrates are limiting, a considerable fraction of the protein is broken down to ammonia, which can be partially wasted through urine. Thus, there should 127

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be coordination between the availability of energy and nitrogen in the rumen(15). More recently, equations have predicted microbial protein production as a linear function of ruminally degradable protein intake in dairy cattle(17). In addition, in feedlot cattle, a minimum of 100 g of soluble nitrogen/kg of organic matter digested in total tract is required to maximize microbial nitrogen flow(44,45).

Effect of dietary fat

Although negative effects of dietary fat has been acknowledge several decades ago, novel advances in molecular methods have revealed that ruminal microorganisms belonging to the genera Fibrobacter, Ruminocuccus, Butyrivibrio and Prevotella can be very sensitive to fat(46,47). It is important to note that unsaturated fatty acids have been shown to be toxic to ruminal bacteria, especially fiber digesting bacteria. This toxicity could be due to an impediment in the nutrient digestion due to fatty acids adhering to the cell wall(46). Thus, it is not surprising that one of the major actions of some ruminal bacterial genera is fatty acid biohydrogenation to minimize the negative impacts of unsaturated fatty acids on microbial growth. Detrimental effects of dietary fat on ruminal protozoa, fungi and archaea have also been reported when feeding linseed or soybean oil(46).

Effect of ruminal pH

The effects of pH on growth of some ruminal bacteria have been recognized(48). Species like Fibrobacter succinogenes and Ruminoccosus albus are very sensitive to acidic ruminal pH(49). This sensitivity can be explained by negative effects of pH on glucose uptake. Other bacterial species such as Prevotella ruminicola and Selenomonas ruminantium are fairly resistant to decline in extracellular pH(50). The type of transport mechanisms used by bacteria influences their sensitivity to pH. For example, transport of arabinose and xylose by Prevotella ruminicola is more sensitive to declines in extracellular pH than is glucose transport(51). Low extracellular pH also decreases the transport of arginine, glutamate, and 128

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leucine in Streptococcus sp.(49). Development of high-throughput DNA sequencing have described the effect of ruminal pH on bacterial taxa of the entire bacterial population. For example, fiber digesting bacteria have been shown to be more sensitive to low ruminal pH compared to starch digesting bacteria(37,21). In addition, researchers have found that mild or severe ruminal acidosis can induce drastic shifts in the bacterial population of the rumen. Rapid proliferation of some bacteria such as Streptoccosus bovis and Lactobacillus sp. has been reported in cattle in situations where the rumen contains high proportions of rapidly fermented carbohydrates and low ruminal pH(52,53). Furthermore, the decrease in ruminal pH due to feeding high-grain diets negatively affects protozoal growth(54); consequently, the model to predict microbial protein includes neutral detergent fiber as an adjustment factor(29).

Effect of feed intake

Decreased feed intake may affect bacterial activity and decrease microbial efficiency due to insuficiency in soluble nitrogen and fermentable organic matter(45). However, if feed intake restriction is not severe, then microbial efficiency is increased (grams microbial nitrogen/kilograms organic matter fermented), but microbial yield (grams of microbial nitrogen reaching duodenum) is decreased as a consequence of less organic matter fermented in rumen. Other studies that have reported a positive relationship between increased feed intake and microbial yield; this is because higher feed intake increases passage rate which prevents protozoa predation(44,53). In addition, the increased quantity of bacterial nitrogen reaching the duodenum with increased feed intake is expected because bacterial nitrogen production is positively correlated with the intake of digestible organic matter(53).

Measurement of microbial protein and its contribution to metabolizable protein

Measurement of intestinal flow of microbial protein requires the isolation of ruminal 129

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microbial pellets, which are then used as reference to establish the ratio of microbial marker/nitrogen. Then, the marker in intestinal digesta is quantified. During the last few decades, several methods have been used to estimate microbial protein synthesis and the proportion that leaves the rumen(4)(Table 1). One of the critical challenges in this process is obtaining a reference microbial pellet representative of both the fluid and particulate phases(10). The nitrogen content of liquid-associated bacteria is 8.5 % and that of the particulate-associated bacteria is 7.0 %(19). Consequently, if only the liquid-associated bacteria are used as reference to establish the ratio of marker/protein, this ratio would lead to underestimated values. Measuring intestinal digesta flow is also needed to estimate microbial protein flow(53,54). One of the most commonly used external digesta markers is chromic oxide (Cr2O3). For this procedure, Cr2O3 is placed in gelatin capsules and dosed into the rumen(55,56) twice daily during 10 d to reach a stable flow of the marker through the gastrointestinal track(5,57,58). Although, it has also became common to incorporate Cr2O3 in the diet at concentrations that range between 0.25 and 0.40 %, on a DM-basis. In addition, indigestible ADF (iADF) is an internal digesta marker routinely used(59,60). With this approach, the concentration of iADF in samples is determined after a 288-h in situ incubation in the rumen. Intestinal digesta flow is then calculated based on the amount of the marker fed (iADF) or dosed (Cr2O3) and the concentration of the respective marker in duodenal samples(61). From these values, the flow of microbial protein; and thus, its contribution to total metabolizable protein is estimated. Other techniques for measuring digesta flow include labeling the particulate and fluid digesta phases with YbCl3 and Cr-EDTA, respectively(6). This review will focus on conventional microbial markers widely used for the estimation of microbial protein, such as total purines(4), diaminopimelic acid(5), and labeled nitrogen(6). In addition, the use of DNA(3) through real-time PCR to measure protein originating from bacterial, protozoa and yeast will be discussed. The ideal microbial marker should not be present in the feed, not be absorbed, be biologically stable, occur in a similar percentage between the various types of microbes, be a constant percentage of the microbial cell in all stages of growth, and all forms should flow at a similar rate(62).

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The use of total purines as a microbial marker

Purine bases (adenine and guanine) are part of nucleic acids of microbial cells(63). Briefly, this procedure combines standard methods for the hydrolysis of nucleotides by perchloric acid. The first step is followed by precipitation of free purines with silver nitrate to separate the purines from interfering compounds. In this method, acid resolubilized purines are quantitated with a spectrophotometer at 260 nm. Then, microbial protein is estimated by the ratio of purines/nitrogen of reference bacterial pellets(64) and the concentration of purines in samples. The use of purines is considered to have some inherent challenges. For example, purines from feed, which escape destruction in the rumen may cause overestimation of microbial protein(63). Sloughed epithelial gut cells may also contribute purines to the digesta, and therefore cause an overestimation. In addition, greater purine concentration in duodenum than in abomasum in lambs has been reported, which was attributed to sloughed cells and bile secretion(8). The correction factor 0.195 Ă&#x2014; BW^0.75 has been utilized to mitigate this overestimation(65). Other major challenges encountered when using total purines as a microbial marker seems to be whether the purines are present in a similar percentage in the different species and in all stages of microbial growth. It has been reported that values for purines in mixed ruminal bacteria vary widely. For example, a study found a mean purine concentration of 7.28 % with values ranging from 2.40 to 13.02 %(53). Variations in purine concentrations of mixed ruminal bacteria grown in continuous culture using several different protein sources have been reported(66). This variation has also been reported among pure cultures(64). Concentrations as a percentage of DM ranges from 0.69 to 5.57 %, with a mean value of 2.98 %. This situation indicates that if the ratio purine/nitrogen is used to estimate microbial protein at the duodenal level, values would be overestimated. Among the biological factors that may be responsible for these variations are the difference in chemical composition among liquid- and particle-associated bacteria and the stage of bacterial growth(19). Therefore, the bacterial isolation procedure should gather a bacterial pellet that represents not only different locations of the rumen, but also liquid- and particle-associated bacteria(67).

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The use of daminopimelic acid as a microbial marker

This method is based on the estimation of the ratio diaminopimelic acid/nitrogen in ruminal bacteria and the amount of the microbial marker in digesta(5). From these values the amount of bacterial nitrogen in intestinal digesta is calculated(68). Briefly, lyophilized samples are hydrolyzed with methasulfonic acid then centrifuged. Then, 20 ÂľL of derivatized sample are injected into the column and subjected to HPLC analysis. During the oxidation process, methionine is converted into methionine-sulfone. In the last step of the process ion-exchange column chromatographic separation is conducted. Diaminopimelic acid is found in the cell membrane of ruminal bacteria and it is absent in feedstuffs commonly fed to ruminants(68). The accuracy of the technique depends on a constant diaminopimelic acid/nitrogen ratio among various microbial species, or the maintenance of a constant ratio of microbial species in the rumen. However, the latter assumption is not consistent with the sequential nature of rumen fermentation. In addition, the diaminopimelic/nitrogen ratio may vary among ruminal bacterial species(39). The different bacteria have different peptidoglycan concentrations in the cell wall, therefore, different diaminopimelic acid concentration. For example, gram-positive bacteria contain 30 to 70% peptidoglycan in the cell wall; the gram-negative bacteria contain only 10 %. Furthermore, if cattle are fed with only forage diets, the gram-negative bacteria will be predominant in the rumen, and if cattle consume more concentrate, the proportion of grampositive bacteria will increase(69,70). Therefore, variations in the relative abundance of grampositive and gram-negative bacteria may affect the estimation of bacterial nitrogen synthesis. For example, if gram-positive bacteria predominate in the rumen, this ratio will be greater, which would lead to an underestimation of bacterial protein synthesis if reference pellets are not representative of whole digesta.

The use of labeled nitrogen as a microbial marker

The synthesis of microbial protein has also been estimated by quantifying 15N incorporation into microbes from (l5NH4)2SO4(15,6). The 15N is infused into the rumen via a ruminal cannula at a constant rate of approximately 1 L per day. This method is based on the incorporation of 132

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labeled nitrogen from ammonia and do not account for microbial protein synthesized directly from amino acids or peptides. Besides being costly, the technique of utilizing nitrogen as a marker is quite complicated and as a result has not been extensively used. One of the advantages of this approach as compared to the purine analysis is the fact that 15N-labeled protein leaving the rumen will only be of microbial origin, whereas a portion of the purines leaving the rumen may be of dietary origin(71). However, the marker/nitrogen ratio has been shown to differ between bacteria associated with fluid and particle phases(30). Thus, establishing this ratio from a representative bacterial pellet has been challenging.

The use of DNA as a microbial marker The real-time PCR is a powerful tool used for quantitative nucleic acid analysis. DNA has been recently tested as a microbial marker through this method. The real-time PCR is a refinement of the original PCR developed in the mid 1980â&#x20AC;&#x2122;s(72,73), which allows rapid detection of microbial DNA, thus indicating the presence of a target microorganism or group of microorganisms. Compared with a conventional PCR method employing two primers, a forward and a reverse, an additional fluorescent probe is required in real-time PCR assays. Therefore, this is highly specific and sensitive because three oligonucleotides complementary to the target DNA marker are employed(74). One advantage of this approach is the ability to quantify microbial protein originating from bacteria, protozoa and yeast, which could not be achieved using the conventional microbial markers. Therefore, the method is based on quantification of a DNA segment specific to these microbial domains(74). One of the first studies that employed DNA through real-time PCR for the estimation of microbial protein was conducted in 2005(75) by using the protozoal 18S gene as a microbial marker. This assay was used to quantify the amount of protozoal biomass in ruminal fluid and digesta from the small intestine. These authors also reported that duodenal digesta subjected to two freeze-thaw cycles decreased recovery by almost half, but one freezing (a standard practice) appeared to increase recovery of microbial DNA. The assay includes procedures for isolating protozoal cells from the rumen for use as a standard to convert 18S gene copies to a biomass basis. The protozoal nitrogen has been determined to be 12.7 % of total rumen microbial nitrogen pool and 11.9 % of the duodenal microbial nitrogen for diets containing high forage(75). Researchers have also reported the use of microbial DNA as a marker to estimate bacterial protein by measuring the 16S gene(5,8), or yeast protein by measuring part of the second chromosome of Saccharomyces cerevisiae(9). One of the advantages of using DNA as a microbial marker is the high specificity for targeting an amplicon that is part of either bacteria, protozoa or yeast excluding any extraneous materials originating from undegraded

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feed, which prevents contamination(8,64). The quantification of yeast protein from the microbial protein pool is particularly important when ruminant rations include feed ingredients containing yeast cells from Saccharomyces cerevisiae, like those from the ethanol industry(76). If the contribution of dietary yeast protein is not quantified separately, then microbial protein originating from bacteria and protozoa would be overestimated. Major components of the real-time PCR assay include 1) A forward primer, which is an oligonucleotide of 20 to 24 base pairs, the 5’ end of this oligonucleotide anneals to the 3’ end of the target DNA marker(73); 2) A reverse primer is also needed, the length of this oligonucleotide should be of 20 to 24 base pairs, the 3’ end of the target microbial DNA marker should be complementary to the 5’ end of this primer(73); 3) A dual labelled Probe is also required(9). The real-time PCR reaction is performed by temperature cycling. High temperature (95 ºC) is applied to separate the strands of the double helical DNA, then temperature is lowered at 60 ºC to let primers anneal to the target DNA marker, and finally the temperature is set around 72 ºC, which is optimum for the polymerase that extends the primers(74). Recent reports, however, indicate that some bacterial(77) and protozoal(7) species may present varying copy numbers of the DNA markers utilized. For example, the phyla Firmicutes and Gammaproteobacteria may contain 5-fold more copies of the 16S gene compared to the rest of bacterial phyla(77), which could introduce bias in the method if bacterial pellets used as reference are not representative of samples being analyzed. In addition, it has been suggested that the lower estimates of microbial protein(3) may be attributed to incomplete recovery of DNA copies from samples(8) or because the universal primers used do not bind to 100% of the microbial 16S and 18S genes, when quantifying bacterial or protozoal protein, respectively.

DNA sequencing improves knowledge on factors affecting measurement of microbial protein flow

The use of high-throughput DNA sequencing

Recent advances in molecular techniques applied to high-throughput DNA sequencing of microbial DNA in combination with bioinformatic analysis of the microbial population 134

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inhabiting the rumen have made significant contributions to our knowledge on the ruminal microbiome(12). This technique has been applied in a variety of research topics related to ruminant nutrition. For example, new insights have been achieved on shifts in the ruminal bacterial population due to change in diet composition(21), change in ruminal pH(37), biohydrogenating bacteria(14,78), the role of bacteria on milk fat composition(79), and archaea involved in methane formation(22,80). In addition, DNA sequencing can improve our understanding on factors affecting the estimation of microbial protein and its flow to the small intestine. More specifically, detailed phylogenetic differences have been revealed between bacterial pellets used as reference and the bacterial population of the intestinal digesta.

Taxonomic differences of bacteria from ruminal fluid and whole intestinal digesta

One of the main challenges in the estimation of microbial protein synthesis and its flow to the small intestine is obtaining a reference bacterial pellet representative of microbial population of whole ruminal contents. Although differences between bacteria from ruminal fluid and bacteria from whole digesta flowing has been longtime assumed(10), it is not until recent years that the use of high-throughput DNA sequencing has enabled researchers to examined the complete taxonomic profile of the reference pellets and whole intestinal digesta(14). Those findings have revealed that taxonomic profile of bacterial pellets isolated from ruminal fluid differs drastically compared to that of bacteria in intestinal digesta when analyzed at the taxonomic levels of phylum, order, family and genus (Tables 3,4). For example, greater proportions of the predominant bacterial phyla Firmicutes, TM7 and Tenericutes have been found in the reference bacterial pellets compared to whole intestinal digesta. In addition, greater proportions of the bacterial orders Bacteroidales and Clostridiales, as well as higher levels of the bacterial family Lachnospiraceae were found in the reference pellets. On the other hand, the reference bacterial pellets contained lower proportions of the phyla Fibrobacteres, Spyrochaetes, Proteobacteria and Lentisphare, and contained lower proportion of the family Ruminoccocaceae and the genus Butyrivibrio. These findings support the notion that the use of solely fluid-associated bacteria as reference pellets would lead to bias in the estimation of microbial protein synthesis, and that there is a need to develop effective detachment procedures to obtain bacterial pellets that are more representative of whole ruminal contents(10) for accurate estimation of the contribution of microbial protein to total metabolizable protein. These findings show that detachment of the 135

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fibrolytic bacteria from the solid fraction of ruminal contents is particularly important for obtaining representative reference microbial pellets.

Table 3: Predominant bacterial phyla and orders found in reference bacterial pellets isolated from ruminal fluid and in whole intestinal digesta of beef steers (%)

Bacterial taxa Phylum, % of total Firmicutes Bacteroidetes Fibrobacteres Chloroflexi TM7 Tenericutes Spyrochaetes Proteobacteria SR1 Planctomyces Lentisphaera Synergistetes Verrucomicrobia WPS2 Other Order, % of total Bacteroidales Clostridiales Coriobacteriales Anaerolineales TM7 Campylobacterales Pirellulales Erysipelotrichaeles Victivallales Sipochaetales Sphaerochaetales Rhizobiales Desulfovibrionales YS2 Rickettsiales Other 1

Origin of bacteria Reference pellets Whole intestinal from ruminal fluid1 digesta

SEM2

P-value

45.95 44.22 0.1 1.69 1.60 1.45 0.92 0.63 0.33 0.26 0.13 0.11 0.12 0.10 2.49

31.32 42.02 10.1 2.00 0.29 1.00 1.78 3.81 0.22 0.11 2.02 0.14 0.52 0.30 14.46

2.675 2.497 0.06 0.303 0.227 0.199 0.138 0.241 0.150 0.042 0.128 0.031 0.056 0.051 0.122

< 0.001 0.53 < 0.01 0.41 < 0.001 0.027 < 0.001 < 0.001 0.58 0.014 < 0.001 0.552 < 0.001 < 0.001 0.001

44.22 34.99 5.32 1.69 1.60 0.32 0.26 0.17 0.12 0.12 0.09 0.04 0.04 0.03 0.02 10.97

41.90 28.31 1.41 2.00 0.30 0.42 0.11 0.07 1.78 0.16 1.79 0.01 0.04 0.57 0.29 20.84

2.498 1.748 0.881 0.303 0.227 0.039 0.042 0.020 0.125 0.021 0.235 0.010 0.018 0.051 0.046 ---

0.51 0.004 < 0.001 0.41 < 0.001 0.067 0.014 < 0.001 < 0.001 0.17 < 0.001 0.084 0.97 < 0.001 < 0.001 ---

Bacteria isolated by differential centrifugation. Adapted from Castillo-Lopez et al.(14). 2 The largest standard of the mean.

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Table 4: Predominant bacterial families and genera found in reference bacterial pellets isolated from ruminal fluid and in whole intestinal digesta of beef steers (%) Bacterial taxa Family, % of total Unclassified bacteroidales Lachnospiraceae Rominococcaceae Prevotellaceae Unclassified clostridiales Paraprevotellaceae F16 Clostridiaceae Anaerolinaceae Coriobacteriaceae Anaeroplasmataceae Veillonellaceae Spirochaetaceae Catabacteriaceae BS11 Genus, % of total Unclassified bacteroidales Unclassified lachnospiraceae Prevotella Unclassified ruminococcaceae Unclassified clostridia Unclassified coriobacteriales Unclassified paraprevotellaceae Ruminococcus Butyrivibrio SHD231 Clostridum Unclassified coriobacteriaceae Coprococcus Succiniclasticum Shuttleworthia Unclassified catabacteriaceae BS11 Pseudobutyrivibrio

Origin of bacteria Reference pellets Whole intestinal from ruminal fluid1 digesta

SEM2

P-value

27.93

17.80

2.442

0.006

17.38 11.48 10.99

9.27 13.66 12.12

0.979 0.895 1.225

< 0.001 0.061 0.52

7.70

2.47

0.857

< 0.001

3.78 2.80 2.11 1.68 1.30 0.98 0.88 0.78 0.72 0.68

4.27 0.47 1.39 2.00 0.05 0.80 1.44 1.48 1.24 0.18

0.857 0.884 0.202 0.303 0.261 0.185 0.191 0.130 0.147 0.293

0.671 0.055 < 0.001 0.418 < 0.001 0.351 0.047 < 0.01 0.011 0.01

27.94

17.81

2.442

0.006

11.73

6.39

0.582

< 0.001

10.94

12.02

1.127

0.53

8.51

9.71

0.770

0.15

7.71

2.47

0.857

< 0.001

4.02

1.36

0.659

< 0.001

3.79

4.27

0.857

0.67

2.84 2.59 1.69 1.48

3.51 0.88 2.00 0.66

0.326 0.203 0.303 0.120

0.162 < 0.001 0.41 < 0.001

1.10

0.05

0.213

< 0.001

0.97 0.81 0.76

0.23 1.41 0.10

0.225 0.189 0.150

0.011 0.032 < 0.001

0.73

1.25

0.147

0.011

0.68 0.64

1.83 0.73

0.293 0.103

0.01 0.553

Bacteria isolated by differential centrifugation. Adapted from Castillo-Lopez et al.(14). 2 The largest standard of the mean. 137

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Implications of taxonomic differences between bacteria from ruminal fluid and whole intestinal digesta on microbial markers

Results obtained from the use of high-throughput DNA sequencing elucidate potential factors that may bias the estimation of microbial protein flow when isolating the representative pellet only from the liquid phase of ruminal contents. For example, studies have suggested that particle-associated bacteria contain lower proportions of purines than liquid-associated bacteria(81). Data on purine content among different bacterial taxa are limited, and because a large proportion of particle associated bacteria are excluded from the reference pellet isolated during differential centrifugation, taxonomic profile divergence between the isolate and intestinal digesta likely represents a source of potential underestimation of intestinal supply of microbial protein. This may partially explain the lower estimates observed compared to predicted values(3). In addition, peptidoglycan concentration varies among bacteria, thus they have different diaminopimelic acid concentrations. Gram-positive bacteria contain more peptidoglycan in the cell wall than gram-negative bacteria(68). Given the greater proportion of Firmicutes (phylum), Clostridiales and Coriobacteriales (orders) and Lachnospiraceae (family), largely represented by gram-positive bacteria, in the reference pellets isolated from ruminal fluid compared to bacteria from whole intestinal digesta, when diaminopimelic acid is used as microbial marker, researchers should be aware of potential underestimation of intestinal microbial protein flow. There is limited information on how the concentration of labeled nitrogen varies among ruminal bacteria. However, reports indicate that the marker/nitrogen ratio differs between fluid- and particle-associated bacteria and that 15N enrichment is higher in liquid-associated bacteria compared to particle-associated bacteria(82). Therefore, results on taxonomic profile between bacteria from ruminal fluid and bacteria from whole intestinal digesta suggest that when the reference microbial pellets are obtained only from ruminal fluid, potential underestimation of intestinal microbial protein flow may occur. Lastly, given the variations in copy numbers of the 16S gene across ruminal bacteria, particularly greater copy numbers in Firmicutes, and because of the greater proportions of Firmicutes in bacteria isolated form ruminal fluid, when DNA is used as microbial marker, underestimated values for bacterial protein would likely be obtained if reference bacterial pellets are not representative of whole digesta flowing to the small intestine.

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Conclusions

The ruminal microbiome plays an essential role in ruminant nutrition; major contributors to microbial protein are bacteria and protozoa. Main dietary and animal related factors that influence microbial protein synthesis in the rumen are the availability of carbohydrates, ruminally degradable protein, dietary fat, feed intake and ruminal pH. All microbial markers have advantages and disadvantages; conventional microbial markers that are commonly utilized to estimate microbial protein synthesis include total purines, diaminopimelic acid and labeled nitrogen. Recently, the use of DNA as a microbial marker through real-time PCR allows detection of bacterial, protozoal and yeast protein separately. Therefore, when researchers are interested in evaluating the contribution of protozoa to the metabolizable protein pool or when evaluating the contribution of dietary yeast, the use of DNA marker with real-time PCR represents an alternative method. However, investigators should be aware of potential biase when using any of these methods. One of the major difficulties in the estimation of microbial protein flow is obtaining a representative microbial pellet from the rumen to establish the ratio of microbial marker/nitrogen. Differences between particulate-associated bacteria and fluid-associated bacteria have been recognized. However, to the authorsâ&#x20AC;&#x2122; knowledge, no studies have compared the taxonomic community composition between fluid associated bacteria and bacteria found in whole intestinal contents and discuss implications on microbial markers as well as potential effects on the estimation of microbial protein flow to the small intestine. Recent advances in high-throughput DNA sequencing in combination with bioinformatics have revealed significant phylogenetic divergence from many bacterial taxa at the phylogenetic levels of phylum, family and genus between the reference microbial pellets isolated solely from ruminal fluid and bacteria found in whole intestinal contents. These findings indicate that further research to develop effective methods for detaching bacteria from feed particles to obtain reference microbial pellets representative of whole ruminal contents is warranted in order to prevent bias when quantifying the microbial protein contribution to the metabolizable protein supply in ruminants.

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http://dx.doi.org/10.22319/rmcp.v10i1.4487 Technical note

Infection dynamics of Cystoisospora suis (Isospora suis) on a pilot swine farm in Carabobo State, Venezuela

Juan Carlos Pinilla Leóna* Natalia Da Silva Borgesb

Universidad de Santander, Facultad de Ciencias Exactas, Naturales y Agropecuarias, Programa de Medicina Veterinaria, Campus de Bucaramanga, Lagos de Cacique, Bucaramanga, Santander, Colombia. b

Universidad Rómulo Gallegos, Facultad de Agronomía, Departamento de Producción Animal, San Juan de Los Morros, Venezuela.

* Corresponding author: j.pinilla@mail.udes.edu.co, jcpinilla@hotmail.com

Abstract: A research was done of the infection dynamics of the protozoan parasite Cystoisospora suis in lactating piglets at an intensive swine pilot farm in Venezuela. Over a 12-mo period (September 2015 to August 2016), 480 fecal samples were collected directly from the rectum in piglets in four age groups: 1-7 d (20 %); 8-14 d (47 %); 15-21 d (23 %); and 22-28 d (10 %). Stool samples were cultured in a 2.5% potassium dichromate solution and later processed by centrifugation-flotation. Cystoisospora suis was present throughout the study period with a 52.08 % overall average prevalence; values were highest in the second week of life. Meteorological variables (temperature, relative humidity and precipitation) had no effect (P>0.05) on variations in C. suis prevalence. Data from an epidemiological questionnaire were analyzed with a Spearman correlation test, identifying an association (P<0.05) between prevalence and the variables of on-site veterinarian, an intense disinfection protocol and use of 5% Baycox. Regional meteorological conditions are optimal for C. suis

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sporulation and year round maintenance of oocysts. This coupled with inconsistent control and hygiene protocols at the studied farm favored parasite survival and proliferation. Key words: Herds, Protozoan, Swine, Venezuela.

Received: 10/05/2017 Accepted: 01/02/2018

The protozoan Cystoisospora suis (Kingdom Chromista, Infraphylum Apicomplexa, Subclass Coccidea, Order Eimerida)(1,2), is one of the most important coccidia affecting swine and the causal agent of porcine neonatal cystoisosporosis(3, 4). Animals infected with C. suis develop yellow-colored diarrhea from the second week of age, which changes from an initially pasty texture to liquid in 2-3 d(3,4). Prevalence varies widely. In German pig farms prevalence was 62.2 % in farms and 53.8 % in litters(5,6), as well as 42.5 % in piglets bred on intensive farms(7). Prevalence in Poland was 27.8 % in litters and 66.7 % on farms(8), but 21.8 % in litters in the Czech Republic(9). In Venezuela, C. suis prevalence was 21.8 % in piglets and 26 % in pigs (0 to 13 wk of age)(10), but on farms in the state of Carabobo it reached 75 %(11). Age can also effect prevalence, with higher levels in litters at two weeks of age in one study(12), but higher prevalence in litters at three and four weeks of age in another study(13). Some authors have reported that season had no effect on C. suis prevalence in piglets(5,14). In contrast, prevalence of C. suis-related diarrhea on pig farms in Germany was reported to increase in summer (66.3 %) and autumn (61 %)(6). Season affects C. suis incidence since sporulation is favored in hot environments (32 to 35 Â°C), which also coincides with conditions inside swine farrowing units(13). In Venezuela C. suis incidence in piglets varies notably between different months(15), probably because parasite survival in farrowing crates is highest during months of higher temperature and humidity. Propagation of C. suis within litters, and by association diarrhea frequency, can be minimized through sanitary control, hygiene measures and proper cleaning of farrowing units(16). Overall, the association between some hygiene and health factors suggests they can minimize C. suis presence in pig farms(17). Carlos Arvelo municipality, in the state of Carabobo, Venezuela, is an important agricultural and livestock region. It accounts for approximately 40 % of all intensive farms in the state, and is a significant pork producer on a national level(18). The present study objective was to evaluate the C. suis infection dynamic over a 12-mo period in piglets grown on a pilot farm.

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The study was conducted at a pilot farm in Guigue Parish, Carlos Arvelo municipality, in the Carabobo state, Venezuela (10°11’35” N; 67°58’48” W). Farm elevation is 500 m asl and annual rainfall is approximately 1,150 mm. Precipitation is highest from June to October, and most intense between August and October. It then declines in November and December until the dry season begins, which lasts until the end of May(19). The farm utilizes an intensive continuous flow system and has a history of neonatal diarrhea. Of the total animal population of approximately 25,000, about 3,000 are producing sows. Animals are crosses of improved breeds. They are fed balanced feed produced at plants near the farm. Average weaning is at 21 d. Piglets are treated with toltrazuril at 2.5 and 5% between 3 and 5 d of age, but interruptions in anticoccidial treatment were observed during the study period. After each weaning, the plastic floor pallets are washed and treated with 5% glutaraldehyde for 2 h. Prior to the study a pilot test was run to measure C. suis prevalence at the farm. Fifteen percent of the litters (50/325) of different ages were sampled following methods described below and prevalence calculated as 80 % (40/50). Based on this figure sample size (n) was calculated using the formula of known prevalence in finite populations(20):

n = N*Zα² (p)(q) /d² (N – 1) + Zα² (p)(q) Where: N = population (litters with diarrhea); Zα2 = 1.962 (95% confidence level); p = expected prevalence (80%, based on pilot study); q = 1 – p; d = maximum admissible error (5%).

During the months of September 2015 to August 2016, 480 fecal samples were collected from lactating piglets, with an average of forty monthly samples taken amongst the four age groups established in the pilot study: Group 1 (1-7 d of age, 20 %); Group 2 (8-14 d, 4 7%); Group 3 (15-21 d, 23 %); and Group 4 (22-28 d, 10 %). Four to five piglets were selected from each litter to create a sample pool. Samples were collected from the selected piglets by introducing a rectal swab into the anus to stimulate defecation, and the feces collected in previously marked test tubes. Collected samples were placed under refrigeration (10 °C) for transport to the Parasitology Research Unit of Romulo Gallegos University in the Guárico state, Venezuela, where they were kept under refrigeration (9 °C) until processing.

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Every time samples were collected a questionnaire was applied to the farm owner to gather data on veterinary care, cleaning and disinfection protocols, and anticoccidial treatments, among other factors. Veterinary care was categorized as absent (1) or present (2). Farrowing crate cleaning protocols were classified into three types: washing with pressurized water (1); washing with pressurized water plus disinfection with 5% glutaraldehyde solution applied with a 20 L agricultural manual sprayer (2); and washing with pressurized water using a hydrojet pump (water at 70 °C and 3,300 lbs/in2) plus disinfection with a 5% glutaraldehyde solution (3). Preventive application of oral anticoccidials was classified as not applied (1); 2 ml/piglet 2.5% Baycox (2); and 1 ml/piglet 5% Baycox (3). Meteorological data (temperature, relative humidity and precipitation) were taken from annual records for the El Pao Meteorological Station (Latitude 10.16°, Longitude: -67.93°, Altitude 430 m asl), Valencia, state of Carabobo, Venezuela(19). All fecal samples (pooled by litter) were cultured at room temperature in Petri capsules using 20 ml 2.5% potassium dichromate solution for 24 h(21). A centrifugation-flotation technique and McMaster was then used with a saturated NaCl solution enriched with sucrose solution (1 L saturated NaCl solution + 500 g sugar) at room temperature and 1.28 specific gravity(22). In samples where fat made C. suis oocyst observation difficult a sedimentation technique was applied using PBS-ether(23). Oocysts were viewed with an optical light microscope at 10x and 40x magnification. Results were analyzed using descriptive statistics and a Chi-Square test to identify statistical differences. The Pearson correlation coefficient was applied to identify associations between prevalence and meteorological data. All calculations were run with the Statistix statistical program(24). Overall, Cystoisospora suis infection prevalence in lactating piglets during the study period was 52.08 % (250/480) (Figure 1). Associations (Chi-Square-Pearson test; χ2:81.36; P<0.05) were found between C. suis prevalence sampling month, implying a seasonal effect on this protozoan’s presence. Prevalence levels during the study period coincide with the high levels in lactating piglets reported elsewhere(5, 6, 7), but differ from other reports of lower prevalence levels(8-11). Differences between studies are probably due to differing management practices and sanitation conditions, which influence C. suis survival and proliferation mechanisms.

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Figure 1: Cystoisospora suis prevalence dynamic in lactating piglets of different ages during the study period 90

Prevalence (%)

80 70 60

71.4 61.5

69.5 59.3

52.6

50 40 22.2

20 10 0

P<0.05; Ď&#x2021;2: 81.36

During the first six months of the study prevalence values were above the annual average (52.08 %). Beginning in March levels dropped as low as 22.2 %, rose in April to 48 %, and then remained constant at 20 % for the remaining four months. Prevalence was probably higher in the months when climate conditions favored oocyst sporulation. This contrasts with lack of a seasonal effect reported elsewhere(5,14), although seasonal differences in prevalence have been reported, particularly in months with high temperatures(6, 13, 15). Prevalence data by age group showed Group 2 (8 to 14 d) to have had the highest prevalence values during the study period (Figure 2); in this group values were highest in October (55 %) and lowest in March (9.1 %). Group 4 (> 22 d) had the lowest overall C. suis prevalence. Groups 1 and 3 exhibited variable prevalence values throughout the study period. Of note is that groups 3 and 4 exhibited no oocyst excretion during the final four months of the study.

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Prevalence (%)

Figure 2: Cystoisospora suis prevalence by litter age group.

55 50 45 40 35 30 25 20 15 10 5 0

< 7 days

8-14 days

15-21 days

> 21 days

The present results coincide with previous reports of higher prevalence values in the first 2 wk of life possibly due to lack of an adequate prophylaxis and control program and consequent higher infection pressure at this age(9,12). However, there are also reports of higher prevalence rates in litters at 3 and 4 wk of age(5,7,14). Since piglets are born with an immature immune system, colostral transfer of antibodies and immune cells appears to be an essential factor in controlling infections in lactating piglets. However, the role of specific antibodies against C. suis which may be transferred from sows to piglets, and any possible correlations between antibody levels and cystoisosporosis is not yet understood(25). Antibodies have been detected in the colostrum and milk of sows experimentally infected with C. suis before parturition, with a protective effect highly correlated to antibody titers during the first two weeks of life(26); this would explain the low C. suis prevalence observed in the present study in piglets less than a week old. Average annual temperature during the study period was 26.3 Â°C, with the lowest readings (20.2 Â°C) in December and the highest (34.2 Â°C) in April (Figure 3). Annual average relative humidity (RH) was 68.2 %, with the lowest RH (55.8%) in March and the highest in September (78.5 %) and October (80.9%). Rainfall over the study period averaged 552 mm, with the lowest levels in November and December, and the highest from January to July. Prevalence decreased in the months with lower RH, and the temperature curve was inversely proportional to prevalence values. This would suggest that higher precipitation and RH favor 154

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higher C. suis prevalence. However, the results do not reflect this since prevalence was highest in the months with the lowest precipitation (September to December), meaning that factors other than climate may be involved in the C. suis lifecycle. Climate in Venezuela is not extremely variable but there are marked seasonal fluctuations that affect parasite dynamics. Despite these variations, meteorological conditions are generally optimal for C. suis sporulation and year round maintenance of viable oocysts. This allows the species to survive until the arrival of new swine hosts who help it to multiply and perpetuate its lifecycle within the farm, especially when biosafety mechanisms are inadequate.

80 75 70 65 60 55 50 45 40 35 30 25 20 15

78.5

77.1 69.4 65.9

65.9 61.5

68.5

61 54 49

Humidity (%)

Prevalence (%)

27.4 27.2 27 26.8 26.6 26.4 26.2 26 25.8 25.6 25.4 25.2 25

Temperature (Â°C)

Percentage (%)

Figure 3: Meteorological variables and Cystoisospora suis prevalence during study period.

Temperature (Â°C)

Source: El Pao-Valencia Meteorological Station (804720) SVVA. Latitude: 10.16. Longitude: - 67.93. Altitude: 430 m.

The Pearson correlation coefficients (r) between meteorological variables and prevalence and infection level data during the study period found no associations (P>0.05) (Table 1). Apparently the studied environmental factors had no effect on prevalence and infection at the studied pilot farm.

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Table 1: Pearson correlations between Cystoisospora suis prevalence and infection level, and the studied meteorological parameters (temperature, humidity and precipitation).

Prevalence Infection level

Temperature

Humidity

Precipitation

- 0.4 - 0.34

0.34 0.5

- 0.5 - 0.1

(P>0.05).

Questionnaire data (veterinary care, washing and disinfecting protocols, and anticoccidial treatment) was analyzed by a Spearman correlation test. A negative correlation was identified (rho= -0.9; P<0.05) between C. suis prevalence and disinfection protocols (Table 2), indicating that prevalence decreased to the extent that Protocol 3 (washing + hydrojet pump + disinfection) was applied. The correlation between prevalence and use of 5% Baycox was also negative (rho= -0.65; P<0.05), suggesting that prevalence decreased when this drug was used. A third negative correlation was found between veterinary care and prevalence (rho= 0.7; P<0.05), meaning that presence of a veterinarian on site may have lowered prevalence. The variables of Protocol 3 (washing + hydrojet pump + disinfection) applied in farrowing units with plastic pallets, presence of a veterinarian on site, and treatment with 5% Baycox were associated amongst themselves and with farms negative for C. suis(17). An on-site veterinarian ensures that effective health programs are implemented on large farms, thus controlling the spread of infectious diseases in a herd. Glutaraldehydeâ&#x20AC;&#x2122;s mechanism of action on evolutionary forms of C. suis has not been reported in the literature, but its proper application as part of well-designed sanitation programs can considerably reduce the amount of coccidia on a farm(16). Use of pressurized hot water to clean plastic flooring and subsequent soaking in disinfectant solutions may also considerably reduce the presence of sporulated oocysts, so that new litters can arrive in a clean environment, without viable oocysts in the farrowing area. Cystoisosporosis control and prevention programs on Venezuelan swine farms could benefit from implementation of good hygiene standards combined with sanitation and disinfection protocols including washing of farrowing areas followed by rinsing with hot water under pressure and disinfection of plastic pallets with glutaraldehyde. This would minimize the possibility of parasite proliferation and spread within farrowing areas, consequently reducing the frequency of C. suis-related diarrhea.

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Table 2: Questionnaire results and monthly prevalence Month

On-site Veterinarian

Protocols

Anticoccidial

Prevalence (%)

Sep-15

61.5

Oct-15

80.0

Nov-15

71.4

Dec-15

59.3

Jan-16

69.5

Feb-16

52.6

Mar-16

22.2

Apr-16

48.0

May-16

20.0

Jun-16

20.0

Jul-16

20.0

Aug-16

20.0

-0.7 P<0.05

-0.9 P<0.05

-0.65 P<0.05

Rho

P<0.05 (Statistically significant association). On-site Veterinarian: (1) absent; (2) present. Protocols: (1) washing; (2) washing + disinfection; (3) washing + hydrojet + disinfection. Anticoccidial: (1) not used; (2) 2.5% Baycox; (3) 5% Baycox.

In the present results, C. suis was present year round in Carlos Arvelo municipality, Venezuela, indicating that regional climate conditions are optimum for sporulation and maintaining oocysts viable in pigs and farm installations. Controlling this protozoan can be accomplished by applying adequate sanitation protocols.

Acknowledgements

The authors thank the Veterinary Medicine Program of the Faculty of Exact, Natural and Agricultural Sciences of the Universidad de Santander for collaborating with and supporting this research.

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Lindsay D, Dubey J. Coccidia and other protozoa. In: Straw B, et al editors. Diseases of swine. 9th ed. Iowa, USA: Iowa State University Press; 2005:861-873.

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Otten A, Takla M, Daugschies A, Rommel M. The epizootiology and pathogenic significance of infections with Isospora suis in ten piglet production operations in Nordrhein-Westfalen. Berl Munch Tierarztl Wochenschr 1996;109(6-7):220-223.

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13. Martineau GP, Castillo J. Epidemiological, clinical and controls investigations on field porcine coccidiosis: clinical, epidemiological and parasitological paradigms. Parasitol Res 2000;86:834-837. 14. Driesen SJ, Carland PG, Fahy VA. Studies on preweaning piglet diarrhea. Aust Vet J 1993;70(7):259-262. 15. Pinilla JC, Coronado A. Prevalencia de Isospora suis en lechones criados en granjas de la región Centro – Occidental de Venezuela. Zoot Trop 2008;26(1):47-53. 16. Sotiraki S, Roepstorff A, Nielsen J, Maddox – Hyttel C, Enoe C, Boes J, Murrell K, Thamsborg S. Population dynamics and intra-litter transmissions patterns of Isospora suis in suckling piglets under on- farms conditions. Parasitol 2008;135(3):395-405. 17. Pinilla JC. Estudio epidemiológico de Isospora suis en granjas porcinas intensivas ubicadas en la región central de Venezuela [tesis doctoral]. Maracay, Venezuela: Universidad Central de Venezuela; 2010. 18. Feporcina. Comportamiento del sector porcino venezolano en el año 2010. Revista de Información Divulgativa 2010;1:10-12. 19. Estación Meteorológica El Pao – Valencia. Anuario de la estación meteorológica El Pao Valencia (804720) SVVA. Latitud: 10.16. Longitud: - 67.93. Altitud: 430 m. 2015. 20. Fernández P. Metodología de la investigación: determinación del tamaño muestral. Manual de epidemiología clínica y bioestadística. Madrid, España 1996;3:138-141. 21. Hendrix CM. Diagnóstico parasitológico veterinario. 2a ed. Madrid, España: Editorial Harcourt Brace; 1999. 22. Henriksen SA, Christensen JP. Demonstration of Isospora suis oocysts in faecal samples. Vet Rec 1992;131:443-444. 23. Ortega-Mora L, Troncoso J, Rojo-Vázquez F, Gómez-Bautista M. Evaluation of an improved method to purify Cryptosporidium parvum oocysts. Res Rev Parasitol 1992;52(3-4):127-130. 24. Statistix 8. Analytical Software for Windows. Version 8.0. USA. 2008. 25. Schwarz L, Worliczek H, Winkler M, Joachim A. Superinfection of sows with Cystoisospora suis ante partum leads to a milder course of cystoisosporosis in suckling piglets. Vet Parasitol 2014;204:158-168.

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26. Shrestha A, Freundenschuss B, Jansen R, Hinney B, Ruttkowski B, Joachim A. Experimentally confirmed toltrazuril resistance in a field isolate of Cystoisospora suis. Parasites & Vectors 2017;10:317.

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http://dx.doi.org/10.22319/rmcp.v10i1.4540 Technical note

Design of an electrochemical prototype to determine relative NaCl content and its application in fresh cheeses

Rubén Cázares-Gallegosa Juan Antonio Vidales-Contrerasa Alejandro Isabel Luna-Maldonadoa Michael E. Humeb Ramón Silva-Vázquezc Armando Quintero-Ramosd Gerardo Méndez-Zamoraa*

Universidad Autónoma de Nuevo León. Facultad de Agronomía. Francisco Villa s/n, Ex Hacienda El Canada, 66050. Escobedo, Nuevo León, México. b

Food and Feed Safety Research Unit, Southern Plains Agricultural Research Center, USDA, TX, USA. c

Instituto Tecnológico de Parral, Chihuahua, México.

Universidad Autónoma de Chihuahua. Facultad de Ciencias Químicas. Chih, México.

*Corresponding author. mezage@hotmail.com

Abstract: An electrochemical prototype (ECP) was developmed and evaluated to determine NaCl electrical variables [volt (V), ampere (A), resistance (R) and power (P)] and its use in fresh cheeses. The ECP circuit consisted of two electrodes, an aluminum (anode) and a copper (cathode). The experimental parameters established in the ECP were distance between electrodes and the presence of a resistor. Seven treatment solutions were examined at 0, 2, 4,

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6, 8, 10 and 12 g of NaCl/100 mL of water. Cheeses evaluated were a commercial cheese (Control) and a commercial light cheese. Treatment influenced (P<0.05) the electrical variables in NaCl solutions and cheeses. Regression analysis showed that the best fit was a quadratic model for the ECP. Prototype results showed that at higher NaCl concentrations, voltage and resistance decreased, while amperage and power increased. Key words: Adulteration, Cheese, Electrical potential, NaCl content, Quality assurance.

Received: 26/06/2017 Accepted: 08/02/2018

Today, inappropriate eating habits have serious impacts on human health. Food intake with high levels of simple sugars, fats and mineral components such as NaCl present problems associated with obesity, hypertension, and chronic degenerative diseases. In the dairy industry, milk adulteration presents significant problems such as economic loss, deterioration of product quality, and threats to consumer health(1). Therefore, the dairy industry employs several often expensive and time consuming chemical and physical tests to determine fat and total solids content(1). Thus, technological alternatives based on electrical circuits have been used to assess the quality of milk(2,3), conductance effects of milk components(4), the presence of adulterants(1), and to evaluate fat content(5). Electrical circuit technology also has been applied to cheese to study dielectric properties for thermodynamic analysis of salt(6), and fractal and dynamic analysis of water(7). Electrical conduction properties of a material represent its ability to interact in an electric current(4,8). Electrical properties of meat, milk, fruits and derivatives are dependent on the chemical composition, measurement parameters of the current, and the experimental conditions(1). Foods containing positively or negatively charged electrolytes, charged molecules, or charged macromolecules are capable of transmitting an electric current(9). In the case of foods, it is necessary to have mobile â&#x20AC;&#x153;carriersâ&#x20AC;? for the cations and anions, being influenced by salinity, formulation, aggregation state, molar mass, link type, charge and the number of charged carriers(9,10). According to Figura and Teixeira(9), an electric current (I) will flow through a food sample containing ions as part of an electrical circuit. The strength of the electric current will be determined by the electrical resistance [R; 1 volt (V) * ampere (A-1) = 1 Ohm (â&#x201E;Ś)] of the food sample, where R limits the flow of electric current through the sample. Therefore, a linear relationship exists between voltage [V represented as U], current, A, and electrical 162

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resistance, R, within an electrical circuit, which is known as Ohm's Law [I = (1/R)*U; o I = G * U]. In order to be independent of sample and circuit geometry in performing certain types of calculations, it is necessary to introduce material properties, specific electrical resistivity (ρ; in Ω*m), and specific conductivity (κ; in S*m-1); where κ depends only phase state, moisture content, and chemical composition, and not sample size, expressed as R = ρ * (Ɩ/A) or κ = 1/ρ, where Ɩ is length in m, and A is current area in m2(9,11). Milk is an electrolyte characterized by ionic conductivity due to its high water content and minerals content(5), as determined by: 1) Current measurements including voltage, frequency, pulse shape and type of electric current (direct, variable, alternating); 2) Chemical composition of fresh material [water content and ion (Ca, Na, K, Mg, Cl) concentrations and components of dry matter such as fats, proteins and sugars]; 3) The experimental conditions, especially temperature. Meanwhile, cheese is a colloidal system consisting of protein, fat and an aqueous phase in electrical balance where salt is a common component used in the dairy industry to preserve cheese quality(6). In this study, an electrochemical prototype (ECP) was developed and evaluated to measure NaCl concentration as alternative to evaluate the NaCl fastly. The ECP consists of an experimental galvanic cell to generate electricity through a spontaneous redox reaction(12), and includes two electrodes and an ionic conductor, which may be a liquid or a solid(13). The objective of this study was to develop and evaluate the ECP consisting of a copper cathode and an aluminum anode, and an ionic conductor (NaCl solutions and fresh commercial cheeses) to measure voltage, electric current, resistance and power as reflections of NaCl content. The research was conducted at the Laboratory of Environmental Remediation and Soils Analysis, Water and Plant of the Facultad de Agronomía, Universidad Autónoma de Nuevo León, General Escobedo City, Nuevo León, México. General Escobedo is located at 26°49' N, -100°19' W and altitude of 500 m(14). The ECP system consisted of two electrodes, an aluminum anode and a copper cathode, with electrode dimensions of 4.5 cm long x 4.5 cm high x 0.15 cm wide. A multimeter (Model 2700/Switch System Keithley, Ohio, USA) was used to measure variables V and A throughout the experiment. A resistor (Ф; 100 Ω tolerance ± 5%) was used to complete the electrical circuit (Figure 1a’).

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Figure 1: Circuit design of the electrochemical prototype (a’), and circuits to determinate Volt (a, b), Ampere (c) and distance (d) between electrodes (4.0 and 0.5 cm)

(d)

(a’)

Experimental conditions for evaluation of the ECP were separation distance (δ) between the electrodes (0.5 and 4.0 cm) and resistor presence (with or without the resistor), during measurement of electrical variables. Variation of distance and presence of the resistor in the circuit were used to define how ECP measurements varied under these conditions in order to obtain the optimum configuration of ECP design. The experiment consisted of seven treatment solutions (Ƭi), based on NaCl concentrations of 0, 2, 4, 6, 8, 10, 12 g of NaCl/100 mL of water. Deionized water (CTR Scientific, Monterrey, N.L., México) at room temperature (24 °C) was used to prepare the solutions. The electrodes were inserted 2.0 cm into each solution, separating them by distances of 0.5 and 4.0 cm (Figure 1d), and with the presence or absence of the resistor (Figure 1a-b) in the circuit (δ with Ф and δ without Ф; Figure 1a-d). These conditions were established to measure variable V. To determine amperage (Figure 1c), it was necessary to place a resistor in the electrical circuit. Variables V and A were used to estimate the R, based on Ohm's Law(15). Power (P) in watts was determined with the following equation: P = V I(15). The experiment was replicated twice, and measurements were performed in duplicate. The ECP was evaluated in 400 g each of two fresh commercial cheeses: a standard (Control) cheese and a light cheese (Light) low in calcium, sodium and fat (Table 1). The cheeses dimensions were 12 cm in diameter and 4 cm high. The electrical variables V, A, R and P in cheese were determined according to conditions determined in the ECP evaluation (Figure 1). Electrodes were introduced 1.5 cm into cheeses, and electrodes were placed at distances of 0.5 and 4.0 cm. Varying the distance between electrodes was done in order to validate the optimum distance between electrodes and whether a resistor in the circuit was required when amperage was measured, and to determine the optimum conditions for measuring the electrical variables and their variation in cheese. The measurements were conducted in two replicates per type of cheese and each variable was measured in triplicate. A 10-g sample of each cheese in triplicate was homogenized in 90 mL of distilled water, and pH was determined with a potentiometer (Mettler Toledo, Probiotek; Columbus, OH, USA).

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Table 1: Nutritional composition of the cheeses Composition (g/20 g of cheese)* Control Light 0.60 0.50 3.40 4.00 5.20 2.80 Â§ 0.11 0.11 0.08 10.57 12.62

Trait Carbohydrate Protein Fat Calcium Sodium Moisture and other components *

Data taken from the commercial product package. Â§ = not present

The statistical evaluation of the ECP was carried through of an analysis of variance (ANOVA) with the GLM procedure of SAS(16), using the statistical model: yijk = Âľ + ĆŹi + Î´j + Đ¤k + (ĆŹÎ´)ij + (ĆŹĐ¤)ik + (Î´Đ¤)jk + (ĆŹÎ´Đ¤)ijk + Ô?ijk; Where: yijk = evaluated variables V, A, R and P; Îź = general mean; ĆŹi = fixed effect of the ith treatment (NaCl solutions and cheeses); Î´j = fixed effect of the jth distance between the electrodes; Đ¤k = fixed effect of the kth condition of the resistor; (ĆŹÎ´)ij = fixed effect of the interaction between treatment and distance; (ĆŹĐ¤)ik = fixed effect of the interaction between treatment and the resistor; (Î´Đ¤)jk = fixed effect of the interaction between distance and the resistor; (ĆŹÎ´Đ¤)ijk = fixed effect of the triple interaction between treatment, distance and the resistor; Ô?ijk = random error normally distributed with zero mean and variance Ď&#x192;2 [Ô?ijk ~ N (0, Ď&#x192;2)]. The pH analysis of cheese involved a simple ANOVA. The effect of the independent variable NaCl on dependent variables V, A, R and P was analyzed with ANOVA, linear regression analysis and the REG procedure of SAS(16), and the following second order quadratic statistical model(17): yi = Î˛0 + Î˛1X1 + Î˛11đ?&#x2018;&#x2039;12 + Ć?i; Where: yi = dependent variable y influenced by X (NaCl);

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Î˛0 = intercept to the origin when X = 0; Î˛1 = linear regression coefficient, which represents the change of y when X (NaCl) increases one unit; X1 = values of the ith solution of independent variable X1 (NaCl); Î˛11 = regression coefficients of second order and represent the change in y when X1 increases by an increment of one unit quadratically; đ?&#x2018;żđ?&#x;?đ?&#x;? = value of the ith quadratic solution of independent variable đ?&#x2018;&#x2039;12 (NaCl2); Ć?i = random error of the ith observation by effect of independent variable (X1) on y. A Tukey means comparison was performed by setting a 0.05 confidence level. Table 2 presents the statistical effect (P-value) of factors evaluated in the ECP on the variables measured in saline solutions. Distance (Î´j) and its interaction with NaCl treatment [(ĆŹÎ´)ij] were not statistically significant (P>0.05) for the electrical variables evaluated (yijk). However, the NaCl concentration (ĆŹi) did influence (P<0.05) the variables measured in the solutions. These results indicate that a distance of 0.5 or 4.0 cm can be used in the ECP design to measure the electrical variables in these solutions without changing the variable values. Amperage was measured only with presence of the resistor in the circuit, therefore, statistical P-value was not calculated for resistor (Đ¤k) interaction with NaCl [(ĆŹĐ¤)ik], distance [(Î´Đ¤)jk] and triple interaction [(ĆŹÎ´Đ¤)ijk] between treatment, distance, and resistor.

Table 2: Effects of model parameters on variables evaluated in NaCl solutions by the electrochemical prototype Model parameters* Model ĆŹi Î´j Đ¤k (ĆŹÎ´)ij (ĆŹĐ¤)ik (Î´Đ¤)jk (ĆŹÎ´Đ¤)ijk Âľ Âą Ô?ijk

Volt 0.3902 0.0076 0.3768 0.1794 0.9202 0.8566 0.9527 0.9971 0.564 Âą 0.007

P-value Resistance 0.0007 < 0.0001 0.3705 Â§ 0.7314 0.6128 2.615 Âą 0.097 220.333 Âą 7.562 Ampere 0.0007 < 0.0001 0.8698

Power 0.0003 < 0.0001 0.7297 0.4448 1464.686 Âą 37.189

ĆŹi = i-th treatment (NaCl); Î´j = j-th distance; Đ¤k = j-th resistor condition; (ĆŹÎ´)ij = interaction between treatment and distance; (ĆŹĐ¤)ik = interaction between treatment and resistor; (Î´Đ¤)jk = interaction between distance and resistor; (ĆŹÎ´Đ¤)ijk = triple interaction between treatment, distance and resistor; Îź Âą Ô?ijk = mean Âą standard error. n = 42. Â§ = not detected. *

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The electrical conductivity measured in NaCl concentrations (Ƭi) by the ECP is presented in the Table 3. Concentrations 2, 4 and 6 g of NaCl/100 mL of water gave the highest voltage values, while the control at 0 g of NaCl/100 mL of water gave the lowest value (P<0.05). The higher NaCl concentrations, including 6 g of NaCl/100 mL of water, showed high ampere and power, but lower values for resistance. Muske et al(18) evaluated electrical variables in lemon juice while varying NaCl concentrations. The conclusions from that study were that the presence of weak acids directly influenced electron transfer and mainly affected the magnesium anode, while the addition of NaCl blocked interaction of the acid on the electrode surface, and resulted in the decrease in electric potential.

Table 3: Electrical conductivity measured in solutions of various NaCl concentrations by the electrochemical prototype NaCl* (Ƭi) 0 2 4 6 8 10 12 SE

Volt 0.539b 0.576a 0.576a 0.580a 0.566ab 0.553ab 0.556ab 0.007

Ampere §

2.055b 2.240b 2.715a 2.663a 2.960a 3.058a 0.088

Variables¶ Resistance 277.810a 253.215ab 212.785bc 211.610c 186.723c 179.858c 9.110

Power 1,168.018b 1,267.343b 1,553.998a 1,499.765a 1,626.340a 1,672.655a 45.778

NaCl in g/100 mL of water. Means (n = 42) with the same superscript are not significantly different. SE = standard error. § = not detected.

Regression analysis of the ECP validation (Table 4) showed significant effect (P<0.05) for a linear behavior, and indicated that the best fit for the electrical variables was a quadratic model. In the case of V, the ECP detected a decrease of -0003 V and R a reduction of-19 Ω for each increase in the NaCl concentration. In contrast, in A and P were detected more than 0.17 and 107 for each unit increase in sodium concentrations, respectively. The quadratic parameter (β11) was found appropriate for detection of decreases in the V, A and P parameters and an increase in R with the NaCl variation.

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Table 4: Regression (β) and determination (R2) coefficients in validation of the electrochemical prototype Dependent variable Volt Ampere Resistance Power *

Regression coefficients* β0 0.563 1.712 314.511 959.196

β1 -0.003 0.173 -19.289 107.242

β11 - 0.0004 - 0.0051 0.6733 - 4.0418

R2 Linear 0.2127 0.7854 0.7756 0.7384

Quadratic 0.2664 0.8024 0.8064 0.7785

P-value 0.0387 < 0.0001 < 0.0001 < 0.0001

β0 = intercept when X = 0; β1 = change in y when X (NaCl) increases one unit; β11 = represent the change in y when X1 increases one unit quadratically; R2 = determination coefficient.

The significance level (P-values) of statistical parameters and means of cheese variables are present in Table 5. The type of cheese (Ƭi) statistically affected V, A, P and pH (P<0.05), while distance (δj) affected V (P<0.05). The interaction between cheese and distance [(Ƭδ)ij] did not influence the variables. In other parameters involving resistance, P-values were not presented for interactions, because the resistor was included in the circuit to measure amperage only. In mean comparisons, control cheese showed the highest values for V, A and P but lower values for R and pH with respect to light cheese. Voltage at the 4-cm distance was the highest compared to V at 0.5 cm. These results may be related to the composition of control cheese, because it had a higher lipid content, and, consequently, a greater presence of fatty acids available in the system, influencing oxidation at the anode. For example, some acids such as CH3COOH are weak electrolytes, and are not completely ionized, being a reversible reaction that gives H+ ions in the medium, and with the presence of metals such as Zn, Mg and Fe conduct electricity(12). Moreover, dissolved hydrogen (H+) in solution is reduced in the absence of copper by the effect of electrode oxidation to H2(19), affecting the electrical variables measured in cheeses. Sadat et al(1) indicated that dielectric properties of foods depend of their chemical compositions. The reactions determined in the current study could explain the high values found in the control cheese, with higher fat content, Ca and Na with respect to the light cheese. Hence, this prototype can be used to evaluate the fat and Na content in cheeses to evaluate its quality and levels of this variables respect to Mexican official standars.

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Table 5: Effects of model parameters on variables evaluated in cheeses with the electrochemical prototype Model parameters*

Volt

Model Ƭi δj Фk (Ƭδ)ij (ƬФ)ik (δФ)jk (ƬδФ)ijk

0.0008 0.0004 0.0118 0.0639 0.3775 0.2091 0.9773 0.3930

Control Light

0.528a 0.512b

0.5 3.0 Resistor (Фk) (Ƭδ)ij (ƬФ)ik (δФ)jk (ƬδФ)ijk SE

0.515b 0.526a 0.520 0.520 0.003

Ampere

Resistence

P-value 0.2118 0.2821 0.0421 0.0867 0.5687 0.4656 0.9026 0.5623 Commercial cheeses (Ƭi; µ)¶ 1.082a 507.307b 0.982b 536.689a Distance (δj; cm) 1.021 525.609 1.044 513.388 1.032 519.498 1.032 522.590 0.024 9.378

Power

0.1505 0.0312 0.4322 0.8712 -

< 0.0001 -

568.701a 505.675b

6.530b 6.755ª

527.127 547.250 537.188 542.330 15.394

0.013

* Ƭ = i-th treatment (cheeses); δ = j-th distance; Ф = j-th resistor condition; (Ƭδ) = interaction between treatment and i j k ij distance; (ƬФ)ik = interaction between treatment and resistor; (δФ)jk = interaction between distance and resistor; (ƬδФ)ijk = triple interaction between treatment, distance and resistor; 2 μ ± Ԑijk = mean ± standard error (SE); n = 12. § = not detected. ¶ Means (n = 12) with the same superscript are not significantly different.

The voltage and resistance are variables that can measure with the electrochemical prototype due that these variables decrease at higher concentrations of NaCl, while amperage and power increased. The distances between the electrodes and presence of the resistor in the circuit had no influence on levels of the electrical variables accessed, but the resistor is necessary to determine of resistance data. The electrochemical prototype perceived differences in the electrical variables (volt, ampere, resistance, and power) of cheeses according to their chemical composition. Therefore, this prototype could be used to evaluate the minerals and quality of the cheeses with the volt, ampere, resistance and power.

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Literature cited: 1.

Sadat A, Mustajab P, Khan IA. Determining the adulteration of natural milk with synthetic milk using ac conductance measurement. J Food Eng 2006;77(3):472-477.

Mabrook MF, Petty MC. Application of electrical admittance measurements to the quality control of milk. Sensor Actuat B-Chem 2002;B84(2-3):136-141.

Mabrook MF, Petty MC. A novel technique for the detection of added water to full fat milk using single frequency admittance measurements. Sensor Actuat B-Chem 2003a;B96(1-2):215-218.

Mabrook MF, Petty MC. Effect of composition on the electrical conductance of milk. J Food Eng 2003b;60(3):321-325.

Żywica R, Banach JK, Kiełczewska K. An attempt of applying the electrical properties for the evaluation of milk fat content of raw milk. J Food Eng 2012;111(2):420-424.

Velázquez-Varela J, Fito PJ, Castro-Giráldez M. Thermodynamic analysis of salting cheese process. J Food Eng 2014;130:36-44.

Maruyama Y, Numamoto Y, Saito H, Kita R, Shinyashiki N, Yagihara S, Fukuzaki M. Complementary analyses of fractal and dynamic water structures in protein-water mixtures and cheeses. Colloid Surface A 2014;440:42-48.

Lin Teng Shee F, Angers P, Bazinet L. Relationship between electrical conductivity and demineralization rate during electroacidification of cheddar cheese whey. J Membrane Sci 2005;262(1-2):100-106.

Figura LO, Teixeira AA. Food physics. Physical properties-measurement and applications. Berlin Heidelberg, Germany: Springer-Verlag; 2007.

10. Lewis MJ. Physical properties of foods and food processing systems. Berlin Heidelberg, Germany: Springer-Verlag; 1990. 11. Gustafson RJ, Morgan MT. Fundamentals of electricity for agriculture. American Society of Agricultural and Biological Engineers. St. Joseph, MI. 2004. 12. Chang R. Chemistry. New York, USA: Mc Graw Hill; 2010. 13. Atkins P, de Paula J. Physical Chemistry. Oxford, New York: W.H. Freeman and Company; 2006.

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14. INEGI. Instituto Nacional de Estadística y Geografía. México en Cifras: Información Nacional por Entidad Federativa y Municipios. http://www.beta.inegi.org.mx/app/areasgeograficas/. Consultado: Feb 12, 2017. 15. Harris DC. Quantitative chemical analysis. Oxford, New York: W.H. Freeman and Company; 2007. 16. SAS. Statistical Analysis System. Version 9.1.3. SAS Institute Inc. Cary, North Carolina, 2006. 17. Montgomery DC. Design and analysis of experiments. Danvers MA: John Wiley & Sons, Inc; 2013. 18. Muske KR, Nigh CW, Weinstein RD. A lemon cell battery for high-power applications. J Chem Educ 2007;84(4):635-638. 19. Kelter PB, Carr JD, Johnson T. The chemical and educational appeal of the orange juice clock. J Chem Educ1996;73(12):1123-1127.

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http://dx.doi.org/10.22319/rmcp.v10i1.4344 Technical note

Hygienic quality of the traditional red chorizo commercialized in the city of Toluca, State of Mexico

Ana Laura Becerril Sáncheza Octavio Dublán Garcíab Aurelio Domínguez-Lópezc Daniel Arizmendi Coteroc Baciliza Quintero-Salazard*

Universidad Autónoma del Estado de México. Programa de Maestría y Doctorado en Ciencias Químicas, Paseo Colón intersección Paseo Tollocan s/n. Col. Residencial Colón, 50120 Toluca, Estado de México, México. b

Universidad Autónoma del Estado de México. Laboratorio de Toxicología Ambiental, Facultad de Química. México. c

Universidad Autónoma del Estado de México. Facultad de Ciencias Agrícolas, México.

Universidad Autónoma del Estado de México. Facultad de Turismo y Gastronomía. México.

*Corresponding author: bquinteros@uaemex.mx

Abstract: The traditional red chorizo that is commercialized in Toluca is a sausage with great fame; however, little is known about its quality. The objective of this study was to determine the hygienic quality of traditional red chorizo in different points of sale. 75 samples of the four main markets of the city of Toluca and 10 specialized butcher shops were analyzed in three periods. The water activity (aw), humidity, pH, acidity and nitrite content were determined based on the Mexican Official Standards. Aerobic mesophilic bacteria (AMB), lactic acid bacteria (LAB), total coliforms and fecal coliforms were counted; the presence of Salmonella spp. and Escherichia coli spp. was detected. The traditional red chorizo did not exhibit

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significant differences (P>0.05) in most of the analyzed physicochemical and microbiological variables. It showed a aw over 0.95; humidity 40 to 50 %; pH below 5 and nitrite content below the maximum limits (156 mg/kg) accepted for sausages according to official standards. The AMB count was between 7.3 to 7.8 Log10 CFU/g and 7.8 to 8.1 Log10 CFU/g for LAB; between 11.1 to 48.6 MPN/g for total coliforms, and between 4.9 to 9.7 MPN/g for fecal coliforms. Salmonella spp. and E. coli exhibited incidence rates in all markets, regardless of their nature, of 11.1 to 60 % and 16.7 to 43.3 %, respectively. The traditional red chorizo of Toluca has distinctive characteristics; yet, it is imperative to implement sanitary management programs during its production, storage and commercialization in order to guarantee a sausage that is not only typical of the region but also innocuous. Key words: Safety, Traditional Mexican sausages, Enterobacteriaceae, Quality.

Received: 14/12/2016 Accepted: 08/02/2018

The increasing worth and demand of traditional foods whose quality and reputation is associated to a territorial origin has prompted studies to characterize (typification) them and assess their quality. The characterization of traditional foods â&#x20AC;&#x201D;especially of artisanal sausagesâ&#x20AC;&#x201D; is a common practice in European countries like France(1), Germany(2), Italy(3), and Spain(4,5). Particularly in Spain, studies on dry fermented sausages like the Pamplona chorizo(4,5) and the Galician onion sausage(6) are prominent. These have determined the color and the texture(4), the volatile compounds(4), and the biochemical changes during the ripening process(6,7), as well as the effect of starter cultures on the volatile compound profile, the microbial count, and the physico-chemical and sensory parameters(8). In the case of Mexico, the techniques for the manufacture of sausages were brought by the Spaniards during the Conquest(9). Later, the local ingenuity, creativity and biodiversity resulted in a great variety of sausages, the most prominent of which is chorizo, a sausage that became popular since the colonial times(10). Chorizo is a cured meat product made from a mixture of minced pork meat and pork fat with added salts such as sodium chloride, nitrites, nitrates, and other permitted food additives(11). Mexican chorizos are characterized for containing mixtures of chili peppers, and they are very important in Mexican gastronomy. Today, varieties of traditional chorizos are produced mainly in states like Hidalgo, Veracruz, Oaxaca, and the state of Mexico. However, despite their gastronomic and economic importance, few studies have been conducted on their physico-chemical(12), sensory(13) and microbiological(14) characteristics.

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In the Valley of Toluca, in the state of Mexico, the small-scale production of red and green chorizos, which are commercialized in the main permanent markets and street markets of the city, is deeply rooted(15). The fame of Toluca as a chorizo-producing city is such that, for many, “Toluca” is synonymous with chorizo(16). However, although the manufacture of these sausages has a great economic importance for the region(15), only preliminary studies on the physico-chemical and morphological quality of traditional green chorizos exist (17), while there are virtually no studies on the general quality —much less on the sanitary quality— of the traditional red chorizo. Based on the above, and led by the awareness of the importance of assessing the microbiological quality of regional foods, the purpose of this study was to determine the sanitary quality of the traditional red chorizo commercialized in the main markets and butcher shops specialized in the sale of pork meat products in the city of Toluca. Samples of traditional red chorizo were obtained from 25 points of sale, 15 of which were established shops in the main permanent markets of the city of Toluca, and 10 were butcher shops specialized in the production and sale of pork meat products. Three samplings were carried out: the first, in October-November, 2015; the second, in January-February, 2016, and the third, in March-April, 2016. Physico-chemical analyses were conducted. Water activity (aw) was determined with the method exposed by Decagon(18). The pH and total titrable acidity were determined with the methods reported by Guerrero et al.(19) The moisture content was estimated through ovendrying(20). The nitrite content was determined using the Griess method(11). Microbial counts were carried out using dilutions to 10-7. Aerial mesophilic bacteria were determined in PCA agar (B. D. Bioxon, Mexico City, Mexico), incubated at 35 ± 1 °C during 48 h(21). The most probable number (MPN) technique was utilized for determining the total and fecal coliforms according to the norm NOM-112-SSA1(22). The presence of Escherichia coli was determined based on those tubes that tested positive for coliforms with the MPN technique on EMB agar plates (B. D. Bioxon, Mexico City, Mexico) at 35 ± 1 °C during 24 h. Gram staining was then applied to suspicious colonies. The IMViC biochemical test (B. D. Dixon, Mexico City, Mexico) was applied to strains with a morphology of Gram-negative bacilli. Salmonella spp. was determined using the methodology exposed in the norm NOM-114-SSA1-1994(23); RVS broth tubes (B. D. Difco, USA) and tetrathionate broth (B. D. Bioxon, Mexico City, Mexico) were utilized as means of enrichment; HE agar (B. D. Difco, USA), SB agar (B.D. Bioxon, Mexico City, Mexico) and SS agar (B. D. Bioxon, Mexico City, Mexico) were utilized as selective means. Suspicious colonies were transferred to TSI biochemical identification media (B. D. Bioxon, Mexico City, Mexico) and LIA (B. D. Bioxon, Mexico City, Mexico). Lactic acid bacteria

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were determined through inoculation using the double layer method(24) in MRS agar at 35 Â°C during 48 h. All the samples were analyzed in triplicate, and the data obtained were subjected to a variance analysis (ANOVA) and to Tukeyâ&#x20AC;&#x2122;s mean comparison test, using the Statgraphics Centurion XVI software, version 16.1.03, Warrenton, Virginia. It is essential to produce foods of good sanitary quality, as the microorganisms present in these may cause not only decay, but also diseases that may put the consumersâ&#x20AC;&#x2122; health at risk(25). A large amount of traditional foods are produced today in Mexico in an artisanal manner; however, they frequently exhibit deficiencies in their quality, especially in their sanitary quality(26). The studies conducted in the Aro cheese that are marked in the municipality of Oaxaca(27), the cheeses of Zacazonapan, in the State of Mexico(28), in chorizos commercialized in Hidalgo(13), and in green chorizo commercialized in Toluca(29). It is important to clarify that the groups of establishments where the samples analyzed in this study were obtained have certain specific characteristics (Table 1). The specialized butcher shops (B) are established shops equipped with refrigerated counters and specific storage areas; similar characteristic may be seen in the shops of market Md; they both cater to a medium-high sector of the population. Instead, the establishments in markets Ma, Mb and Mc are characterized by their limited spaces, without specific areas for production and storage and without proper hygiene; the shops of market Mb target the middle-low sector and wholesale stores. Mexican traditional chorizos have certain unique characteristics; first, they are fresh, not ripe; they are lightly acidified, and they are cooked before they are consumed. Particularly the traditional red chorizos of Toluca are characterized by containing mixes of different chili peppers (Capsicum annum), including puya, guajillo, and ancho, among others; furthermore, depending on the variety, they include dried fruits such as pine nuts (Jatropha curcas), raisins (Vitis vinifera), almonds (Prunus dulcis), and pecans (Carya illinoinensis), among others(30). Other distinctive aspects of the product are its format (i.e. the length and diameter), and the physico-chemical parameters (e.g. aw, pH, acidity) determined in this study.

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Table 1: Characteristics of the groups of establishments where red chorizo is commercialized in the city of Toluca Establishment group Ma (n=15) Mb (n=15) Mc (n=6) Md (n=9) B (n=30)

Degree of technification Artesanal Artesanal Artesanal Artesanal Semi-industrial

Type of storage

Commercial sector

Intemperie Intemperie Intemperie Refrigeration Refrigeration

Middle-low Middle-low Middle-low Middle-high Middle-high

M= markets; B= specialized butcher shops.

In order to understand the presence of indicator microorganisms, first it was necessary to carry out the physico-chemical determinations shown in Table 2. In general, the aw of the chorizo commercialized in the main groups of establishments analyzed herein had a mean value above 0.95, showing a significant difference (P<0.05) between market Ma and the specialized butcher shops (B). These values are consistent because they relate to a fresh sausage; furthermore, they are slightly higher than those reported for the chorizos of the state of Hidalgo (0.93-0.95)(13) and the green chorizo commercialized in Toluca (0.94-0.96)(17). Doubtless, such high aw values were a factor that influenced the development of bacteria, but not of fungi or yeasts. As for the moisture content, the product exhibited percentages ranging between 41.8 and 50.1%; Furthermore, those establishment groups where chorizos are kept in refrigeration (Md and B) exhibited a higher moisture percentage. These values were higher than those reported for chorizos of the state of Hidalgo (36 a 43 %)(13). The high aw values in a food item suggest a larger amount of water available for the development of chemicalenzyme reactions, as well as a greater microbial growth. On the other hand, the moisture content refers to the total water content, without specifying the portion of water that is associated to other molecules.

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Table 2: Physico-chemical parameters of the traditional red chorizo commercialized in different groups of establishments in the city of Toluca Establishment group Ma (n=15) Mb (n=15) Mc (n=6) Md (n=9) B (n=30)

Moisture (%)

0.963±0.003a 0.959±0.003ab 0.969±0.005ab 0.964±0.004ab 0.970±0.002 b

47.056±1.714b 41.803±1.714a 46.515±2.710ab 50.101±2.213b 49.762±1.212b

4.572±0.085a 4.470±0.085a 4.728±0.134ab 4.588±0.110ab 4.785±0.060b

Acidity (% lactic acid) 0.022±0.002a 0.021±0.002a 0.022±0.003ab 0.028±0.002bc 0.030±0.002c

Nitrites (mg/kg) 0.267±0.332a 0.667±0.332ab 2.600±0.525c 0.573±0.428ab 1.145±0.428b

M= markets; B= specialized butcher shops. a,b,c: Different superscripts in the same column indicate significant differences between the establishments (P<0.05).

The pH values were below 4.8, and there was no significant difference (P>0.05) between the chorizos from the various markets. The chorizo samples from specialized butcher shops (B) had significantly higher pH values than those from the markets Ma and Mb. A similar behavior was observed in regard to acidity, where the specialized butcher shops group exhibited significant differences (P<0.05) with respect to markets Ma, Mb and Mc. Studies conducted on Pamplona chorizo and Galician onion sausages have reported pH values of 4.4 and 4.8, respectively(4,6); these values are understandable, given the ripening process, which lasts approximately 50 days. In the case of chorizos sold in Tulancingo, Mexico, pH values of 4.41 to 5.15 have been reported(31), while green chorizos sold in Toluca have exhibited pH values between 4.49 and 5.64(17). The fact that the traditional chorizos commercialized in Mexico, particularly in Toluca, exhibit pH values close to those of the ripened Spanish chorizos may be due to the combined effect of spontaneous fermentation during the airing process, with the consequent development of lactic bacteria and the production of organic acids, and the acidic nature of an important amount of ingredients such as vinegar, red wine, white wine, and dry red chili peppers, e.g. guajillo, puya, ancho, chipotle, and chile de árbol (Capsicum annuum L.) reported in their formulation(14,30). As for nitrites, they are added with antimicrobial and antioxidant purposes, as well as to fix certain organoleptic characteristics of certain meat products and contribute to their development(32). In this study, chorizos of all the analyzed establishment groups exhibited nitrite values below 0.27 mg/kg; this value is far below the maximum limits (156 mg/kg) permitted by the Mexican official norms for sausages(11). These results agree with those documented by traditional producers, who claim that they do not add nitrites to their formulations(30). The marginal presence of nitrites may be ascribed to the biological oxidation of amines, or to the anaerobic reduction of the nitrate naturally present in the vegetables used to produce them, rather than to the intentional addition of nitrites for product conservation purposes. In certain locations, chorizos are usually manufactured without added nitrites, and this is a provision that must be met by such products as the Cantimpalos chorizo, which has a designation of origin(33). 177

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The determination of indicator microorganisms in foods makes it possible to detect poor management practices or contamination; in most cases, a high number of indicator microorganisms may increase the risk of occurrence of pathogenic microorganisms(34). Particularly in the case of the traditional red chorizo commercialized in Toluca, values of 7.39 to 7.85 log10 CFU/g were registered for aerobic mesophilic bacteria (Table 3). No significant differences were found (P>0.05) between the different groups of establishments. The presence of aerobic mesophiles usually indicates the degree of contamination of a sample. However, this does not apply to fermented foods, like the chorizo type analyzed here, since by nature a high bacterial multiplication is desirable for fermentation. The presence of aerobic mesophilic bacteria and lactic acid bacteria in sausages like the traditional Galician chorizo has been observed to increase during the fermentation process, reaching values of up to 8.55 log10 CFU/g and 8.1 log10 CFU/g, respectively, after 30 d of ripening(7).

Table 3: Mean values and standard deviation in the counts of various microbial groups present in the traditional red chorizo commercialized in Toluca Establishment group Ma (n=15) Mb (n=15) Mc (n=6) Md (n=9) B (n=30)

Aerobic mesophilic bacteria (Log10 UFC/g) 7.76±0.48a 7.85±0.56a 7.60±0.44a 7.39±0.49a 7.80±0.49a

Lactic acid bacteria (Log10 UFC/g)

Total coliforms (NMP/g)

Fecal coliforms (NMP/g)

7.90±0.36a 7.87±0.46a 7.84±0.47a 8.07±0.63a 8.01±0.47a

48.56±57.29b 19.61±16.73a 14.33±10.87a 11.07± 8.49a 34.06± 56.30b

7.85±6.11a 9.67±4.67a 5.73±3.44a 4.87±3.38a 7.36±5.59a

M= markets; B= specialized butcher shops. ab

MPN= minimum permitted number. Different superscripts in the same column indicate significant differences between markets (P<0.05).

In the case of fresh sausages, studies conducted on chorizos from the state of Hidalgo, Mexico, have documented a count of aerobic mesophilic bacteria ranging between 7.17 and 8.73 log10 CFU/g)(13), while values above 8.0 log10 CFU/g have been reported in chorizos from Mexico City(35). These differences may be due to the nature of the ingredients and production processes. As for the coliforms (Table 3), their presence indicates the efficiency of the food sanitization and disinfection processes(34). Values for total coliforms ranging between 11.07 and 48.56 MPN/g were found, with significant differences (P<0.05) between the groups of establishments Ma and B with respect to the rest of the establishment groups. Fecal coliforms exhibited values between 4.87 and 48.56 MPN/g, without significant differences (P>0.05),

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regardless of the group of establishments. This may be due, among other reasons, to poor quality of the raw materials utilized, to failures in the cold chain during the manufacture and commercialization process, to a lack of specific storage spaces for the raw materials and/or to the inexistence of a cleaning plan for the packs or containers(31). The Mexican Official Norm for processed meat products (NOM-213-SSA1-2002)(11) does not indicate the maximum permitted number of fecal coliforms allowed in raw products like chorizo ; it only establishes that the limit must be <3 MPN/g for cooked products. However, since chorizo is an essential ingredient in Tolucan gastronomy, it is very important to apply a correct degree of cooking in which the minimum temperature at the thermal core of this meat product is 74 ÂşC, according to the norm NOM-251-SSA1-2009(36). This will allow avoiding the incidence of food-borne infections that may put at risk the health of local consumers and of those tourists who in the course of their visit to the city of Toluca wish to taste this famous sausage, especially when it is added to traditional fast foods, such as tacos, tortas, sopes, and others. The presence of lactic acid bacteria (LAB) is inherent to raw-cured fermented sausages because they are added intentionally during the manufacture process or because they develop during the ripening process. LAB counts in the order of 8.0 a 8-5 log10 CFU/g and 8.6 log10 CFU/g, respectively, have been reported in the traditional chorizos made with pork of the Chato Murciano breed or in ripened Galician chorizos(7,37), depending on the ripening time. In contrast, lower counts, of 7.4 to 9.0 log10 CFU/g, have been reported in the fresh and slightly acidified chorizos of the state of Hidalgo(13). LAB counts between 7.84 and 8.07 log10 CFU/g were found, without significant differences (P>0.05) between the studied establishment groups. The presence of LAB favors spontaneous fermentation during the airing or drying process (1-3 d)(31), and it could be partly responsible for both the acidity and the stability of the product. Salmonella is one of the main pathogenic bacteria, and its simple presence, even in low numbers, entails a significant health hazard(38). According to the norm NOM-213-SSA12002(11), the presence of Salmonella spp. is not allowed in cooked, cured, marinated, brined, or raw meat products like chorizo; it should be â&#x20AC;&#x153;absentâ&#x20AC;? from 25 g of product. Nevertheless, according to the literature(38,39,40), its presence has been reported in samples of fresh chorizos of certain localities of Mexico. This is ascribed, among other causes, to poor hygienic handling of the product, to the lack of an ongoing control of the temperature along the supply chain of the sausages (cold chain) from its production to its distribution, storage, and exhibition at the point of sale, commercialization and consumption. This is a consequence of the lack of investment in adequate equipment and infrastructure. Another aspect that might also compromise the innocuousness of the product and favor the presence of Salmonella in it is the use of natural guts for stuffing(38).

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The presence of Salmonella in the traditional red chorizo analyzed here was positive in the product from markets as well as from certain specialized butcher shops (Table 4). The highest percentage of incidence (60 %) was observed in the market Mb, where 15 samples tested positive. The group of establishments within the market Mb caters to a middle-low sector, and has a great affluence due to its closeness to the Central Bus Station of Toluca. On the other hand, the shops in market Md were the ones with the lowest percentage (11%) of samples that tested positive for Salmonella (9 samples); this market targets a middle-high sector and has security facilities and hygiene. Given the infrastructure of specialized butcher shops, we expected to find in them a lower incidence of Salmonella; however, this was not the case. The presence of Salmonella spp. in this type of establishments may have been due to cross-contamination favored by the handling of other meat products (for example, pork brawn, fresh meat, chili pork meat, among others), which are often commercialized and displayed together with chorizo.

Table 4: Percentage of samples of traditional red chorizo of Toluca that tested positive for Salmonella spp. and Escherichia coli by establishment group Establishment group Ma (n=15) Mb (n=15) Mc (n=6) Md (n=9) B (n=30)

Salmonella spp.

E. coli

20.0 60.0 33.3 11.1 30.0

40.0 40.0 16.7 22.2 43.33

M= markets; B= specialized butcher shops.

Based on the above, the red chorizo commercialized in Toluca may represent a latent risk factor for the health of the consumers; hence the need to implement control and monitoring of the temperatures, as well as an adequate hygienic handling throughout the supply chain, in order to eliminate the possibility of development of pathogenic microorganisms. Furthermore, it is advisable to raise the awareness of the consumers and of those in charge of food and drink establishments regarding the appropriate handling and cooking of the product, and to remind them that the product must be cooked at a temperature above 74 ยบC (at its core), during an adequate number of hours, in order to eliminate the potential risk of food-borne infections due to the development of Salmonella and other pathogenic microorganisms in the product. On the other hand, E. coli is generally a harmless bacterium; however, pathogenic strains can exchange genes and generate disease-causing variations(34). Samples in all the groups of 180

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establishments tested positive for E. coli. The group of establishments with the highest incidence was that of specialized butcher shops (B), with 43.33% (30 positive samples) (Table 4). Oddly enough, the group of establishments with the lowest percentage of positive tests was Mc, which caters to the middle-low sector of the population, and where with 17 % of the samples (6 samples) tested positive. Although the traditional red chorizo commercialized in Toluca is manufactured by different producers from their own recipes, the samples exhibited high similarities in terms of their physico-chemical and even biological characteristics, especially in terms of the number of LAB. The fact of having found samples of traditional red chorizo that tested positive for Salmonella spp. and E. coli represents a call to attention for both producers and vendors, and at the same time suggests the need to implement programs to allow the selection of higher-quality raw materials, the improvement of the hygienic handling of the product, and the maintenance of the cold chain. This may contribute to maintain or improve the reputation and increase the sales of this very traditional and iconic sausage beyond a local level, leading to a better life quality for those who for centuries, from one generation to the next, have preserved the know how in relation to its manufacture.

Acknowledgements

The authors wish to express their gratitude to the National Council for Science and Technology (Consejo Nacional de Ciencia y Tecnología, CONACyT-Mexico) for the postgraduate scholarship granted to Ana Laura Becerril Sánchez, as well as to the Center for Research and Advanced Studies of the Autonomous University of Mexico (Secretaría de Investigación y Estudios Avanzados, SIEA-UAEMéx) for the funding granted through its project, “Determination of the quality characteristics of the red chorizo of Toluca and its perception by consumers and producers”, code No. 3744/2014CID.

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http://dx.doi.org/10.22319/rmcp.v10i1.4350 Technical note

Impact of health monitoring of clenbuterol in Guerrero, Mexico: Results from 2011 to 2015

Luis Alberto Chávez-Almazána* Jesús Antonio Díaz-Ortizb Diana Garibo-Ruizc Mario Alberto Alarcón-Romerob Miguel Angel Mata-Diazb Beatriz Pérez-Cruzb Elizabeth Godoy-Galeanab

Universidad Autónoma de Guerrero. Facultad de Ciencias Químico Biológicas. Guerrero, México. Secretaría de Salud de Guerrero. Laboratorio Estatal de Salud Pública “Dr. Galo Soberón y Parra”. Guerrero, México. b

Centro de Investigación Científica y de Educación Superior de Ensenada, Baja California. México.

*Corresponding author: chavez_79@hotmail.com>

Abstract: The use of clenbuterol in livestock production entails risks to human health that must be characterized and managed by the agricultural and health authorities. This work evaluated the results of the health surveillance program of this compound in bovine meat products that are commercialized in Guerrero, Mexico. A retrospective analysis of the evolution of the illegal use of clenbuterol and of the record of food poisoning with this chemical was carried

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out for the 2011–2015 period. The rate of positive samples decreased gradually to be 6.8 % in 2015 and, in general, was lower in comparison with the immediate antecedents; however, it was always higher than the average rates obtained in the rest of the country (Guerrero= 9.5 %, National= 5.8 %). The health jurisdictions with the greatest presence of the drug were Tierra Caliente and the North, with 12.1 and 16.8 %, respectively, as well as in locations with a large population like Acapulco (9.6 %). Few cases of human poisoning were reported in the first three years of the period (3 in 2011, 5 in 2012, and 4 in 2013) and none in the two subsequent years; however, there is an under-registration issue, which may be due to different individual, regional and institutional factors that are discussed further below. The progress observed in this program should be maintained by strengthening health surveillance with the aim to eradicate this illegal activity in the short term. Key words: Clenbuterol, Food poisoning, Health surveillance.

Received: 14/01/2017 Accepted: 29/11/2017

Clenbuterol is an antagonist compound of the beta adrenergic receptor of the vascular, myometrial, and bronchial smooth muscle, used in veterinary medicine as a bronchodilator and tocolytic drug(1); in certain countries, its administration is authorized as a treatment for respiratory illnesses in humans. Because this compound acts as a distributing agent in animals by eliminating fats and promoting the synthesis of proteins, it causes accelerated growth of the muscle mass, and is therefore utilized, illegally and indiscriminately, to increase meat production in bovine livestock(2-5). The ingestion of foods with clenbuterol residues entails a hazard for consumers, as it can cause serious intoxications associated to such symptoms as palpitations, tachycardia, headache, tremor in the extremities, high blood pressure, anxiety, nervousness, itch, nausea, stomach ache, fever, vomiting, asthenia and muscle weakness, accompanied by alterations of certain hematological (leucocytes) and chemical (electrolytes, glucose) parameters(6-10). In order to protect the population against hazards due to the consumption of foods contaminated with clenbuterol, the Undersecretariat for Food Regulation and Control and Health Promotion, dependent upon the Department of Health of the State of Guerrero, Mexico, has implemented the Food Innocuousness Program (formerly known as Potentially Hazardous Foods Project), since the year 2005, based on the Mexican Official Norm NOM194-SSA1-2004(11), which consists of verification visits to various establishments, such as markets, slaughterhouses and supermarkets, where samples of meat products are collected by the “Dr. Galo Soberón y Parra” Public Health Laboratory of the State of Guerrero (LESP187

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Guerrero) in order to detect clenbuterol, using the Ridascreen Clenbuterol Fast enzyme immunoassay (r-biopharm, Germany)(12). The purpose of this study was to evaluate the results of this program in order to determine its effectiveness in reducing the illegal use of clenbuterol in the production of beef in the state of Guerrero. This is a retrospective, comparative, transversal observational study. The results of the health surveillance program for clenbuterol implemented in Guerrero between the years 2011 and 2015 were analyzed in order to determine the suitability of the sampling scheme and establish whether there was a tendency in the percentages of positive cases through the years, as well as compare the results obtained in the state with the situation across the country. The use of clenbuterol was analyzed at the regional and municipal level, and the number of food intoxications derived from this illegal practice was reported. Two hundred fifty (250) g samples of liver and muscles (and, occasionally, eyeball and urine samples) of bovine cattle were collected and screened for clenbuterol. The samples were stored in polyethylene bags and plastic jars with a screw cap (for urine samples); they were perfectly identified and transported to LESP-Guerrero at a temperature of 2 to 8º C. The samples were prepared as follows: A) Liver and muscle. 5 g of the previously ground sample were placed in a 50 ml (CorningTM, USA) centrifuge tube. 25 ml of HCl 0.05 M were then added, and the tube was mechanically shaken during 20 min. It was subsequently centrifuged at 4,000 xg for 15 min at a temperature of 10 to 15 ºC, after which 18 ml of supernatant were transferred to another tube, to which 2 ml of NaOH 0.5 M were added and mixed during 10 min. Finally, 4 ml of a phosphate buffer (KH2PO4 0.5 M pH 3) were added, and the mixture was homogenized and left to stand for another 90 min at 2-8 ºC. The mix was then centrifuged, and 10 ml of supernatant were drawn and passed through a C18 type solid-phase extraction column (RBiopharm, Germany). B) Eyeball. The pieces were frozen at -20 ºC during 24 h in order to lyse the tissue. They were subsequently dissected, and the extracted fluid was diluted in distilled water at a ratio of 1:2 and centrifuged at 2 000 xg during 5 min. 20 µl of the supernatant were drawn for the immunoassay. C) Urine. These samples were analyzed directly without any previous extraction treatment, and they were centrifuged at 2 000 xg during 5 min only when they exhibited turbidity. The adequate volume for the analysis was 30 to 50 ml. The solid phase extraction was carried out by conditioning the C18 column with 3 ml of methanol, and 2 ml of a rinse buffer (KH2PO4 0.05 M pH 3); the supernatant was applied, and 3 ml of rinse buffer were added. The column was dried and slowly eluted with 1 ml of HPLC-degree methanol (Honeywell Burdick and Jackson, USA). The extract was concentrated at 50 to 60 ºC under a stream of air; the dry residue was reconstituted with 400 µl of HPLC-degree water (Sigma Aldrich, Switzerland). 188

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The extracts were analyzed by means of a competitive enzyme immunoassay (Ridascreen Clembuterol Fast, R-Biopharm, Germany)(12) with a reading on a UV-Vis iMark spectrophotometer (Bio-Rad Laboratories Inc, USA) at 450 nm; the clenbuterol concentration was expressed in ng/kg or ppb (parts per billion). According to the norm NOM194-SSA1-2004(11), those samples with concentrations above 2 000 ng/kg were considered to be contaminated, detected or positive. Samples with lower results were interpreted as “not detected”. As for the analytical quality of the method, the acceptance criteria described in the reagent’s insert were met(12). Likewise, in each run, the commercial controls and samples with known concentrations were analyzed, and the expected values were always obtained. Notably, this Laboratory has been enabled by the Federal Commission of Protection against Health Risks (Comisión Federal para la Protección contra Riesgos Sanitarios, COFEPRIS), as the third laboratory authorized to conduct analyses for health regulation and control, as it fulfills the technical and quality management requirements established in the norm NMXEC-17025-IMNC-2006(13). The results of the program were statistically analyzed by means of a correlation study (Pearson’s r coefficient) between the number of collected specimens and such variables as the population and the dressed beef output of the visited municipalities. The percentage of contaminated samples was subsequently calculated according to the Health Jurisdiction (HJ)> of the studied provenance and year; graphs were developed on which the annual percentages of contaminated samples in Guerrero were related to the nationwide percentages, as well as with the number of persons intoxicated during the studied period. The results calculated for the HJs and the municipalities were depicted in thematic maps. These analyses and graphs were developed using the SPSS version 21 (IBM Corporation, USA) and ArcGIS version 9.3 (ESRI, USA) software. According to the analysis of the results, the sample collection was not uniform as to the quantity, as in 2011 more meat products were analyzed than in any other year (n= 172), while the number of analyzed meat products diminished substantially, to 91 in 2012, and 105 in 2013. This variable showed a recovery in 2014 and a progression in 2015 (Table 1). This behavior may be due to the fact that the budget allotted to the operation of the health surveillance program is different every year, and the activities to which it is destined involve expenses; this affects the planning of the inspection visits to supermarkets, slaughterhouses and meat retail shops directly. Furthermore, the presence of samples contaminated with clenbuterol leads to the redesigning of strategies with the aim to obtain better results in inhibiting this illegal activity in livestock production. This entails emphasizing surveillance, particularly in those localities where there have been positive cases, and relegating to a second place those where this problem has not been observed. The application of this riskbased approach renders the program effective and reduces the use of financial and human resources.

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Table 1: Contaminated / collected samples and percentage of contaminated samples by year (annual %) and health jurisdiction (HJ) Tierra Caliente North Center Mountain Costa Grande Costa Chica Acapulco Annual, %

2011

2012

2013

2014

2015

Total

HJ (%)

4/25 4/22 2/36 0/9 4/28 0/17 8/35 12.8 n=172

0/9 2/12 1/8 2/4 1/16 0/12 1/30 7.7 n=91

6/26 0/10 0/19 0/11 0/11 0/8 0/18 5.7 n=105

2/24 6/19 0/21 0/11 0/13 5/20 2/21 11.6 n=129

1/23 4/30 4/32 1/7 0/24 0/24 1/21 6.8 n=161

13/107 16/95 7/116 3/42 5/92 5/81 12/125 9.3 n=658

12.1 16.8 6.0 7.1 5.4 6.2 9.6

In terms of the sample types, there was a certain equality in the amount collected from the liver (n= 329) and the muscles (n= 310) (Table 2). The Work Instruction(14) of the Sanitary Commission of COFEPRIS establishes that, in the course of inspection visits to slaughterhouses, butcher shops and supermarkets, the meat products must be collected by triplicate: a sample for analysis at the State Laboratory, a second sample to be kept by the Undersecretariat for Health Regulation, and a third one, for the owner of the regulated establishment â&#x20AC;&#x201D;in case they should express any inconformity regarding the resultâ&#x20AC;&#x201D;, to be subjected to analysis at some other authorized laboratory in the country (so that a final dictum may be issued by the corresponding health authority).

Table 2: Percentage of samples in which the presence of clenbuterol was detected, by simple type and corresponding year Year 2011 2012 2013 2014 2015

Type of sample Liver Muscle Liver Muscle Liver Muscle Eyeball Liver Muscle Liver Muscle Urine

Result Not detected 89 61 53 31 37 56 6 53 61 67 74 9

190

Detected 15 7 7 0 1 4 1 4 11 3 5 3

Total

104 68 60 31 38 60 7 57 72 70 79 12

16.9 11.5 13.2 0 2.7 7.1 16.7 7.6 18.0 4.5 6.8 33.3

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The collection was similar in all regions except for the Mountain, where only 42 samples were gathered (Table 1). The difficult access to the localities may be an important factor limiting the operation of the program in this area of the state, all the more because the samples must be transported and preserved at a temperature of 2 to 8 ยบC, and since the transportation times to the laboratory are usually long, the cold chain may be broken at some point, damaging the quality of the sample; this is another factor that may influence the small number of samples collected in this region. A total of 39 (48.1 %) out of the 81 municipalities that make up the state were visited, with a focus on those with the largest population and greatest touristic, economic and political importance: Acapulco (n= 119), Chilpancingo (n= 73), Iguala (n= 39), Tlapa (n= 31), Ciudad Altamirano (n= 34), and Zihuatanejo (n= 29) (Figure 1). An analysis of the correlation between the number of inhabitants of the visited municipalities and the amount of meat products collected in these yielded a high correlation between the two variables (r= 0.912, P<0.001); this is logical, as health surveillance must be increased in direct proportion with the growing number of consumers, for purposes of prevention and hazard control. There is no relationship between the levels of dressed beef production in the municipalities and the samples obtained in them (r= -0.045); i.e. the sample collection was not influenced by the high output of certain municipalities. Based on this, it is recommended broadening the coverage of the sampling in the municipalities and regions in order to increase the likelihood of detecting positive cases and, thus, have elements for making decisions that may contribute to attain better results in health surveillance for clenbuterol.

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Figure 1: Meat product collection in the municipalities of Guerrero

The percentage of positive samples, i.e. the relationship between the amount of meat products contaminated with clenbuterol and the total number of meat products collected exhibited a downward tendency through the years (Table 1). This reduction was gradual, except for the year 2014, when there was a slight increase (11.6 %). Eventually, this percentage diminished to approximately half of the initial one (2011= 12.8 % vs 2015= 6.8 %). This indicates an important success of the surveillance program for clenbuterol in terms of health risk reduction for beef consumers in the state of Guerrero. The global percentage (9.3 %) was lower than that obtained by Chรกvez et al (15) in a similar study conducted during the years 2005-2010, in which the average annual percentage was 13.1 %, with almost 24 % of the samples contaminated with this chemical in 2005. However, these figures always were above the national average (Guerrero mean= 9.5 %, national mean= 5.8 %; P= 0.1) (Figure 2). In some cases, like that of the year 2011, the percentage of positive samples in Guerrero was twice the percentage of the rest of the country (12.8 vs 5.1 %, respectively); therefore, the goal should be to reverse this behavior in the short or medium term in order to reduce the contamination levels to those of the rest of the country.

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Figure 2: Comparison between the percentages of positive samples in Guerrero and at a national level during 2011-2014

The eyeball and urine were not the samples of choice in the sampling scheme of the program. However, as shown in Table 1 clenbuterol was more successfully detected in these biological samples, as only seven eyeball specimens were required to find residues of the drug in one; likewise, the compound of interest was found in up to three of the nine urine samples tested. This is due to the pharmacokinetics of the molecule, since high concentrations—and therefore a high permanence— of clenbuterol have been reported in the retina after the chemical has been administered therapeutically(16). Likewise, this agent is excreted slowly through the urine, where it may be found up to the ten days after the exposure(17,18), whereas in the blood it can only be detected within five days after the intake(19). Despite the evidence presented in this and other studies(16,20), collection of eyeball samples has not been the procedure of choice because the condition of obtaining three specimens from the same animal as indicated in the Work Instruction of COFEPRIS(14) cannot be met (for logical reasons). Furthermore, urine samples are obtained only in special operations of the health authority of the slaughterhouses, and this activity is not very frequent, as it carried out only when a public complaint has been filed or when there is a history of introduction of contaminated meat into these establishments. In the regional analysis, the main HJs that contributed higher percentages of positive samples were the North and Tierra Caliente —with 16.8 and 12.1 %, respectively—, where the presence of this chemical was constant in almost all the studied years. In Acapulco, despite the intense surveillance (more samples were collected there than in any other HJ), positive cases also occurred repeatedly, with 9.6 %, although to a lesser extent than in the other two jurisdictions. In the remaining HJs, the situation was more controlled, and positive cases occurred only sporadically. Clenbuterol was detected in 22 municipalities, notably in those

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with a larger population, like Acapulco, Chilpancingo, Iguala, Ciudad Altamirano, and Tlapa, where the largest number of contaminated samples were found (Figure 3).

Figure 3: Presence of clenbuterol in the municipalities of Guerrero

There are some records of intoxication in humans due to consumption of meat products contaminated with clenbuterol: three cases occurred in 2011, five in 2012, and four in 2013; no other cases were registered in the remaining years (Figure 4). Six of these cases were detected in Acapulco, three in Iguala, two in Chilpancingo, and one in Chilapa, which are the municipalities that exhibited the largest number of positive samples, with the exception of Chilapa, where only one case, directly related to an intoxication, occurred in 2012. As with many health issues in Mexico and other countries, food intoxications with clenbuterol are underreported, possibly due to a lack of information at the first level of healthcare for recognizing the symptoms that may imply the need for a deeper study of the cases in order to attain an adequate diagnosis(21); furthermore, people do not seek treatment at the healthcare centers because they lack economic resources or because of a shortage of institutional medical services. Therefore, it estimates that the real number of cases is larger.

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Figure 4: Percentage of contaminated samples (bars) and cases of intoxication (dotted line) in each studied year

Because this chemical contaminant is still present in foods, it is important to maintain and strengthen monitoring by increasing the number of inspection visits to establishments, as well as to follow up on the cases of contaminated samples through the traceability chain, in order to locate the livestock producers and make them aware of the negative impact of these inadequate livestock production practices on human health. Finally, intersectoral coordination is required to fight this problem; every institution must design, within the scope of its authority and responsibilities, an integral scheme to promote good production practices from the initial stages, preventing livestock breeders from seeking a better output through the use of substances that are dangerous for the consumers. Likewise, when there is sufficient evidence of the illegal use of clenbuterol, acts of authority must be executed to the ultimate consequences in compliance with the laws in force, based on the fact that this activity poses a threat to public health and must therefore be penalized without reserve or exceptions. In the light of these results, and in comparison with the previous years, it is only fair to mention the work carried out by the Department of Health of Guerrero in relation to this phenomenon, whereby the number of positive cases and, therefore, of food intoxications, has been substantially reduced. Nevertheless, the surveillance program must be kept in operation with the aim to eradicate the illegal use of clenbuterol in order to protect the population from the related health hazards.

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Acknowledgements

The authors wish to express their gratitude to the Undersecretariat for Food Regulation and Control and Health Promotion for the operation of the health surveillance program for clenbuterol in Guerrero; to their colleagues Roberto Huante and Diego Morán for their technical assistance, and to Dr. Hugo Saldarriaga for the revision of the manuscript and for his valuable contributions.

Literature cited: 1.

Sillence MN, Mathews ML, Badran TW, Pegg GG. Effects of clenbuterol on growth in underfed cattle. Austr J Agric Res 2000;51:401-406.

Sakai N, Sakai M, Mohamad-Haron DE, Yoneda M, Ali-Mohd M. Beta-agonist residues in cattle, chicken and swine livers at the wet market and the environmental impacts of wastewater from livestock farms in Selangor State, Malaysia. Chemosphere 2016;165:183-190.

Kearns CF, McKeever KH, Malinowski K, Struck MB, Abe T. Chronic administration of therapeutic levels of clenbuterol acts as a repartitioning agent. J Appl Physiol 2001;91:2064-2070.

Peters AR. b-agonists as repartitioning agents: a review. Vet Rec 1989;124:417-420.

Mitchell GA, Dunnavan G. Illegal use of β-adrenergic agonists in the United States. J Anim Sci 1998;76:208-211.

Brett J, Dawson AH, Brown JA. Clenbuterol toxicity: a NSW poisons information centre experience. Med J Aust 2014;200(4):219-221.

Hoey AJ, Matthews ML, Badran TW, Peg GG, Sillence MN. Cardiovascular effects of clenbuterol are β2-adrenoreceptor-mediated in steers. J Anim Sci 1995;73:1754-1765.

Brambilla G, Cenci T, Franconi F, Galarini R, Macri A, Rondoni F, Strozzi M, Loizzo A. Clinical and pharmacological profile in a clenbuterol epidemic poisoning of contaminated beef meat in Italy. Toxicol Lett 2000;114(1-3):47-53.

FAO/WHO Expert Committee on Food Additives. Residues of some veterinary drugs in animals and foods. Monographs prepared by the Fourth Meeting of the Joint FAO/WHO Expert Committee on Food Additives. Geneva. 1992. 196

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10. Hoffman RJ, Hoffman RS, Freyberg CL, Poppenga RH, Nelson LS. Clenbuterol ingestion causing prolonged tachycardia, hypokalemia, and hypophosphatemia with confirmation by quantitative levels. Clin Toxicol 2001;39(4):339-344. 11. Diario Oficial de la Federación. NOM-194-SSA1-2004, Productos y Servicios. Especificaciones sanitarias en los establecimientos dedicados al sacrificio y faenado de animales para abasto, almacenamiento, transporte y expendio. Especificaciones sanitarias de productos. http://www.salud.gob. mx/unidades/cdi/nom/194ssa104.html. Consultado 25 Mar, 2016. 12. R-Biopharm AG. Enzyme immunoassay for the quantitative analysis of Clenbuterol and other β-agonists. http://www.r-biopharm.com/products/food-feedanalysis/residues/hormones-and-anabolics/clenbuterol/item/ridascreen -clenbuterolfast. Accessed Apr 27, 2015. 13. Instituto Mexicano de Normalización y Certificación. NMX-EC-17025-IMNC-2006 Requisitos generales para la competencia de los laboratorios de ensayo y de calibración. México. 2006. 14. Comisión Federal para la Protección contra Riesgos Sanitarios. Comisión de Operación Sanitaria. Instrucción de trabajo para la vigilancia sanitaria del clembuterol en productos cárnicos. México, DF. Secretaría de Salud. 2008. 15. Chávez LA, Diaz JA, Pérez B, Alarcón MA. Tendencia de 2005 a 2010 de los niveles de clembuterol en muestras de bovinos en Guerrero, México. Rev Mex Cienc Pecu 2012;3(4):449-458. 16. Smith DJ, Paulson GD. Distribution, elimination, and residues of [14C] clenbuterol HCl in Holstein calves. J Anim Sci 1997;75(2):454-461. 17. Harkins JD, Woods WE, Lehner AF, Fisher M, Tobin T. Clenbuterol in the horse: urinary concentrations determined by ELISA and GC/MS after clinical doses. J Vet Pharma Therapeutics 2001;24:7-14. 18. Dave M, Sauer MJ, Fallon RJ. Clenbuterol plasma pharmacokinetics in cattle. Analyst 1998;123:2697-2699. 19. Yang YG, Song LX, Jiang N, Xu XT, Di XH, Zhang M. Pharmacokinetics of ambroxol and clenbuterol tablets in healthy Chinese volunteers. Int J Clin Exp Med 2015;8(10):18744-18750. 20. Li L, Tang C, Zhao Q, Zhang K. The potential of various living tissues for monitoring clenbuterol abuse in food-producing Chinese Simmental beef cattle. J Anal Toxicol 2016;40(1):72-77. 197

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21. Wu ML, Deng JF, Chen Y, Chu WL, Hung DZ, Yang CC. Late diagnosis of an outbreak of leanness-enhancing agent-related food poisoning. Am J Emerg Med 2013;31(10):1501-1503.

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http://dx.doi.org/10.22319/rmcp.v10i1.4387 Technical note

Populations and food stores of honey bee (Apis mellifera) colonies from three regions of Mexico’s semiarid high plateau

Carlos Aurelio Medina-Floresa* Ernesto Guzmán-Novoab Jairo Iván Aguilera Sotoa Marco Antonio López Carlosa Sergio Ernesto Medina-Cuéllarc

Universidad Autónoma de Zacatecas. Unidad Académica de Medicina Veterinaria y Zootecnia, Carretera Panamericana Zacatecas-Fresnillo km 31.5, El Cordovel, Enrique Estrada. CP. 98500, Zacatecas, México. b

University of Guelph. School of Environmental Sciences. Guelph, ON, N1G 2W1, Canada.

Universidad de Guanajuato. Campus Irapuato-Salamanca, Departamento de Arte y Empresa, Salamanca, Guanajuato, México.

*Corresponding author: carlosmedina@uaz.edu.mx

Abstract: The aim of this study was to determine the number of adult bees, brood areas, honey and pollen from 150 honey bee (Apis mellifera) colonies in spring and fall in the temperate semidry, temperate sub-humid and semi-warm semi-dry regions of Zacatecas, Mexico. The colonies in the semi-warm semi-dry region had significantly more bees and brood in the fall than those in the other regions (P=0.001). In the spring, colony populations in the temperate semi-dry and semi-warm semi-dry regions were similar and significantly greater than those in the temperate sub-humid region (P<0.01). There was significantly less honey and more

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pollen stored in the fall, in hives of the semi-warm semi-dry region than in hives of the other regions (P=0.001). In the spring, the area of stored pollen in colonies of the temperate semidry region was significantly greater than that of colonies from the other regions (P<0.0001). The population of adult bees and brood areas of colonies in the fall correlated positively with bee population, brood and honey areas in the spring (P<0.001). In the fall, the semi-warm semi-dry region had better conditions for developing and reproducing colonies than the other regions. However, the population sizes of the colonies studied (21,000 to 35,000 bees/hive) are not considered optimal (>50,000), and thus, it is suggested that previous to blossom seasons, strategies aimed at increasing bee population and food stores, that contribute to winter colony survival and to improve their productivity, are implemented. Key words: Apis mellifera, Bee population, Brood areas, Honey, Pollen, Climatic regions.

Received: 25/02/2017 Accepted: 11/02/2018

The state of Zacatecas occupies the tenth place as honey producer in Mexico, and the first in the northern region of the country, with an annual yield of 1,603 t(1). Honey production and the survival of honey bee (Apis mellifera) colonies depend on the effect and interaction of various factors, namely the population size of the colonies, the industriousness of the bees and the environment(2). However, for the state of Zacatecas, and generally for the semiarid high plateau of Mexico, the environmental conditions demand efficient management processes to contribute to the optimal exploitation of floral resources. Regarding the above stated, the growth of honey bee colonies under natural conditions is related to the availability of pollen and nectar in the field. The entry of nectar and pollen into the hive stimulates the egg laying rate of the queen, which results in an increase of the colonyâ&#x20AC;&#x2122;s population(3). Honey production in honey bee colonies is associated to a rapid exploitation of the blossom season by the bees; therefore, the blooming period must coincide with the existence of an abundant bee population in the hive for the attainment of a higher honey yield. The colony must produce an abundant amount of brood before the blossom season, so that the maximum population may coincide with the nectar flow(2). In addition to honey production, population and nutritional parameters are important indicators of the survival of honey bee colonies during the winter(4), which has both economic and ecological implications.

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Because of the above, it is of interest for researchers and beekeepers to know the size of the population and food reserves of honey bee colonies at different times of the year and in different climatic regions. This knowledge may allow producers to implement management strategies during the pre-harvest season that may contribute to increase honey yields as well as to reduce the rate of colony losses during critical seasons (e.g. winter), and the execution of these management strategies will depend on the natural development of bee populations in each region. The objective of this study was to determine the population size and food stores of honey bee colonies during the two main blossom seasons in the three climatic regions of more apicultural importance for the state of Zacatecas. To achieve this goal, the population size and food stores in 20 % of the commercial bee colonies located in 25 apiaries of three climatic regions of the state of Zacatecas were assessed. These evaluations were carried out on two occasions: during mid-autumn, 2010 (n= 150 colonies), and during mid-spring, 2011 (n= 150 colonies). Ninety (90) % of the colonies sampled in the fall were also sampled in the spring; the remaining 10 % were different, as 15 were lost during the winter. The colonies studied were selected at random from each sampled apiary, as long as they were visually perceived as clinically healthy. The colonies belonged to different producers; therefore, the management, origin and age of the queens were heterogeneous, a condition shared by the three regions studied. It was assumed that, as a whole and due to the large number of repetitions, the average management conditions in the state were adequately represented. The value of this work lies in that it makes relative comparisons of the conditions of honey bee colonies between regions. The colonies were distributed in 15 municipalities that belong to the three ecological regions with the greatest apicutural importance for the state of Zacatecas, Mexico (22Â° 57' N, 102Â° 42' W) (Figure 1). In each region, 50 colonies were analyzed in the fall, and 50 in the spring, and so were 8 to 13 colonies in each municipality. The main characteristics of each region in terms of climate and vegetation are described below.

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Figure 1: Map of Zacatecas showing the location of the colonies analyzed in the various regions

Semi-dry temperate: Fresnillo (1), Villanueva (2), Villa García (3), Guadalupe (4), Ojo Caliente, (5) and Zacatecas (6). Sub-humid temperate: Tepechitlán (7), Tlantenango (8), Momax (9), Nochistlán (10), and Valparaíso (11). Semi-dry semi-warm: Tabasco (12), Jalpa (13), Juchipila (14), and Moyahua (15).

Semi-dry temperate Region (SDT). It covers 60 % of the surface area of the state’s territory and is the most arid, high, cold and dry of the three regions studied. Its mean annual precipitation, temperature and relative humidity are 469 mm, 15 °C and 54 %, respectively. This region has less diversity of plant species than the other regions of the state, and the dominant vegetation type is the medium-sized open grassland(5). Two important nectar flows occur every year, one in the spring (mainly from mesquite (Prosopis laevigata)), and another in the fall. The latter is the most important for apiculture in the state and is a product of the blossoming of various shrubs, such as aceitilla or Spanish needle (Bidens odorata), lampote or Mexican sunflower (Tithonia tubaeformis) and lampotillo or bushsunflower (Simsia amplexicaulis)(5-7). The colonies of this region were located in nine apiaries of the municipalities of Fresnillo, Villanueva, Villa García, Guadalupe, Ojo Caliente and Zacatecas, at altitudes of 1,800 to 2,400 m asl. Sub-humid temperate region (SHT). The mean annual precipitation, temperature and relative humidity parameters of this region are 680 mm, 18 °C and 66.7 %, respectively. The climate of the region constitutes a transition between the SDT and SDSW regions. The vegetation is deciduous sclerophyllous broadleaved(5), and the flora with apicultural importance during the spring consists of tepame or feather acacia (Acacia pennatula) and pointleaf manzanita (Arctostaphylos pungens), and at the end of the summer and in the fall, of catclaw mimosa (Mimosa aculeaticarpa), pointleaf manzanita (Arctostaphylos pungens), and kidneywood 202

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trees (Eysenhardtia polystachya)(5-7). The colonies in this region were located in eight apiaries in the municipalities of Tepechitlán, Tlantenango, Momax, Nochistlán, and Valparaíso, at altitudes of 1,200 to 2,000 m asl. Semi-dry semi-warm region (SDSW). The annual mean precipitation, temperature and relative humidity of this region are 704 mm, 19.5 °C and 55 %, respectively(5). It is the lowest, warmest and most humid of the three studied regions; besides, it contains a greater diversity of floral resources than the other two regions. This region exhibits two main nectar flows of herbs, trees, and deciduous shrubs. In the spring, mesquite (Prosopis laevigata) is the main plant of apicultural interest, whereas several species produce nectar or pollen in the fall, such as crownbeard (Verbesina platyptera), venadilla or torchwood copal (Bursera fagaroides), and ochote or casahuate (Ipomoea murucoides)(5-7). The colonies studied were located in eight apiaries of the municipalities of de Tabasco, Jalpa, Juchipila and Moyahua, at altitudes of between 1,000 and 1,400 m asl. The bee population of the colonies was estimated by counting the number of combs covered by bees, and multiplying them by the number of bees that occupy a jumbo-size brood frame on both sides (3,960 bees), as established for Africanized bees by Delaplane et al(8). The brood areas and food stores were estimated based on the mean percentage estimated by two operators of the surface of each side of the comb occupied by capped brood, honey, and pollen. This percent surface area was then converted to area (cm2), using as a base, the surface of a jumbo frame on both sides (2,260 cm2)(8,9). The measurements were made during the afternoon-evening period (1600 to 1900 h), when most bees were inside the hives. The data obtained for the number of bees and the comb area occupied by brood, honey, and pollen were square root-arcsine transformed to normalize their distribution(10). The two seasons of the year were compared, subjecting the data for the studied variables to Student t tests. To determine whether there were differences between the regions for the variables studied, the transformed data were subjected to analyses of variance (ANOVA), and when significant differences were detected, the means were compared using a Tukey test. Pearson’s correlation analysis was also used to determine the relationship between the registered variables(11). Considering all regions, the results show significantly larger bee populations, brood and honey areas in the spring than in the fall, whereas the pollen areas were significantly larger during the fall (Table 1).

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Table 1: Values (mean ± SE) for the number of bees and comb areas with brood, honey and pollen in honey bee colonies during the spring and fall Variable

Fall

Spring

t and P

Bees per colony

23,550±626

33,044±539

56.9 <.0001

Brood areas, cm2

9,392±362

10,168±288

41.9 <.0001

Honey areas, cm2

6,443±338

7,177±289

30.4 <.0001

1,975±161

1,328±136

15.4 <.0001

Pollen areas, cm

Likewise, considering both seasons, the results show that the colonies located in the SDSW region had larger bee populations and brood areas than the colonies in the two other regions. The honey reserve areas of the colonies in the SDT and SHT regions were larger than in the colonies of the SDSW region. The pollen areas were smaller in the SHT region than in the SDT and SDSW regions and there were no significant differences between them (Table 2).

Table 2: Values (mean ± SE) for the number of bees and comb areas with brood, honey and pollen in honey bee colonies in three regions of the state of Zacatecas Semi-dry temperate

Sub-humid temperate

Bees per colony

27,960±981a,b

26,800±876b

29,954±678a

3.52 0.030

Brood areas, cm2

9,245±448b

9,186±375b

10,874±363a

5.8 0.0032

Honey areas, cm2

7,647±304a

7,407±409a

5,392±399b

10.9 <.0001

Pollen areas, cm2

2,145±206a

1,130±124b

1,689±202a

7.7 0.0005

Variable

Semi-dry F and P semiwarm

Different letters in the same row indicate significant differences based on analyses of variance and Tukey tests.

Table 3 shows the mean values for bee populations per colony and brood area for the three regions and the two seasons of the year; the colonies of the SDSW region had a larger bee population during the fall than those of the SDT and SHT regions, between which there were no significant differences for that season. In the spring, the colonies of the SDT and SDSW regions had a similar bee population, which was significantly larger than that of the colonies located in the SHT region.

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Table 3: Values (mean ± SE) for the number of bees and comb areas with brood in honey bee colonies of three regions during the spring and fall Region

No. of bees No. of bees per colony in per colony the fall in the spring

t and P

Brood Brood areas areas (cm2) in the 2 (cm ) in the spring fall

t and P

t=112.8 P=0.0001

6,282±461c 12,268±489a

t=80.9 P=0.0001

9,695±611b 8,666±439b

t=3.8 P=0.052

Semi-dry temperate

20,908±1,091b 35,155±779a

Sub-humid temperate

t=51.2 22,888±1,200b 30,791±1,032b P=0.0001

Semi-dry semiwarm F and P ab

26,788±804a

33,185±913a

F=8.38 P=0.0004

F=5.79 P=0.003

t=28.2 a b P=0.0001 12,141±526 9,582±445 F=30.72 P=0.0001

t=14 P=0.0003

F=16.92 P=0.0001

Different letters in the same column indicate significant differences. The t and associated probability values are the result of the comparison between the seasons of the year for each region.

In the fall, the brood areas were largest in the colonies of the SDSW region, while in the spring, the brood areas were significantly larger in the SDT region than in the other two regions (Table 3). Table 4 shows that there was significantly less honey stored in the hives of the SDSW region during the fall than in the hives of other regions. The honey areas in the colonies of the three regions were not significantly different in the spring. In the fall, the pollen areas were largest in colonies of the SDSW region, while those of the SDT region were significantly larger than those of the colonies of the other regions. Table 4: Mean values for comb areas with honey and pollen of three regions during spring and fall Region

Honey areas Honey areas (cm2) in the (cm2) in the fall spring

Pollen areas t and P (cm2) in the fall

Pollen areas (cm2) in the spring

t and P

Semi-dry temperate

8,701±474a

6,572±320a

t=13.7 P=0.0003

1,943±304b

2,352±286a

t=.98 P=0.32

Sub-humid temperate

7,774±561a

7,033±609a

t=1,6 P=0.20

1,175±159c

1,083±196b

t=.27 P=0.60

Semi-dry semiwarm

2,924±351b

7,910±530a

t=62.9 P=0.0001

2,791±310ª

565±139b

t=43.1 P=0.0001

F=44.55 P=0.0001

F=1.88 P=0.15

F and P ab

F=9.32 P=0.0002

F=18.64, P=0.0001

Different letters in the same column indicate significant differences. The t and associated probability values are the result of the comparison between the seasons of the year.

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A positive and significant correlation was found between the number of bees and the brood areas of the colonies in the two seasons of the year (fall: r= 0.79, P<0.001; spring: r= 0.54, P<0.001, n= 150). The bee population in the fall was positively and significantly correlated with the bee population and brood and honey areas registered in the spring (r= 0.32, r= 0.36, r= 0.28, respectively; n= 150, P<0.0001). Likewise, the brood area of the colonies in the fall showed a significant correlation with the bee population and brood and honey areas in the spring (r= 0.30, r= 0.33, r= 0.26, respectively; n= 150, P<0.001). No significant correlations were found in either season between the pollen areas and the bee population of the colonies. These results show that the population conditions and honey stores were better in the spring than in the fall, and that the SDSW region had a larger bee population and brood areas than those of the SDT and SHT regions, both of which have lower temperatures, precipitations and diversity of plant species than the SDSW region(5). Considering the three regions and the two seasons as a whole, the results show that the bee population size and the brood areas were largest in the fall for the colonies located in the SDSW region, and only in the spring were the brood areas largest in the SDT region. This may be due mainly to differences between the regions in terms of environmental conditions such as the diversity of plant species, precipitation, temperature and humidity. For example, the fact that the pollen stores (a source of protein) were relatively high in the fall and relatively low in the spring in the colonies of the SDSW region may account to some extent for the fact that the colonies of this region had significantly more brood and bees in the fall than those of the two other regions. There may be a higher availability of pollen from the plant species of the semi-dry semi-warm region (Verbesina platyptera, Bursera fagaroides and Ipomoea murucoides) than from the species of the semi-dry temperate region (Bidens odorata, Tithonia tubaeformis and Simsia amplexicaulis) and the sub-humid temperate region (Mimosa aculeaticarpa, Arctostaphylos pungens and Eysenhardtia polystachya). Notably, the largest bee population and brood sizes in the fall for the colonies of the SDSW region did not result in a larger amount of stored honey. In this region, more honey and less pollen were found in the spring, and more pollen and less honey in the fall, than in the SDT and SHT regions, possibly because the intensity of the nectar flow from the flowers was insufficient to result in a high storage of food reserves, which also diminished due to a greater consumption of food by the increased bee population. Such large bee and brood population size may not have lasted long, since the reduction in the amount of food would reduce the egg laying rate of the queen and, therefore, in the bee population(12). Although a high honey production would not be expected, the production of bees and brood in the SDSW region during the fall is sufficient to use it for the production of honey bee nuclei, which have a high commercial value. The brood area and bee populations depend on the food stores in the colony and on the availability of these in the field(13). If the stores and availability of pollen are low, there will be less protein with which to feed larvae, and therefore the quality (in terms of size, nutrition 206

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and viability) and quantity of bees in the next generation (35 d) may be reduced. This, in turn, has a negative impact on colony development (14,15). This scenario agrees with the findings of this study in the sense that there was a significant relationship between the number of bees and brood area in the fall and in the spring. The protein content of flowersâ&#x20AC;&#x2122; pollen in Mexico has not been studied; however, reports from other countries reveal wide variations between plant species (2 to 62 %)(16). Because of this, when the colony does not have sufficient pollen, or when the protein content of the stored pollen is lower than 20 %, the colony tends to collect a larger amount of pollen to cover its nutritional requirements; otherwise, the egg laying rate of the queen will decrease(17), and this will lead to a less than optimal development of the colony. The different regions of the present study vary in diversity, distribution and abundance of plant species, and therefore, based on the amount of stored pollen, we may speculate that there may be a different contribution of nutritional elements in the pollen collected by the bees in the various regions, and the absence of correlation between the pollen reserve areas and the population size (brood and bees) of the colonies. However, this hypothesis must be proven in future studies. The bee population and the food reserves of the colonies in the fall have been reported to influence the population size in the following spring(4); this, in turn, can impact the bee populations in the summer and, therefore, the productivity of the colony. This coincides with the correlations found in the present study, which suggest that, if the bee population, the brood area and honey stores increase in mid-autumn, they will also increase in the spring. Furthermore, GuzmĂĄn-Novoa et al(4) found that a low population size and low food stores are associated, respectively, with 69 and 68 % of the colony mortality cases during winter. Both seasons analyzed in this study, correspond to blossom periods and honey harvests in the semi-arid high plateau of Mexico. However, it was observed that, with the exception of the SDSW region, the best conditions for the development of colonies occurred in the spring, when bee populations and pollen stores in the colonies were larger. The environmental conditions and the management of colonies are factors that vary and thus have a significant impact on the survival and population size of honey bee colonies, as well as on their honey production. In Zacatecas, the average yields of honey per hive range between 17.5 and 30 kg per blossom season(18,19); however, it is highly probable that these yields could be improved. For this reason, it is indispensable that beekeepers monitor the sanitary, population, and nutritional status of their colonies at various times of the year, to implement management strategies previous to harvesting, such as requeening of colonies, disease control, use of nutritional supplements, and hive mobilization, (at least 45 d) before the nectar flow. This will allow time to achieve the maximum bee populations in the colonies to coincide with the beginning of the nectar flow. The mean populations of approximately 21,000 to 35,000 bees per hive found in the blossom seasons in the present study were above those reported in Apis mellifera syriaca colonies of 207

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Jordan, under semi-arid conditions of the Mediterranean(20), and similar to the mean populations of colonies under tropical conditions in the state of Chiapas, México(21), but inferior to those of colonies in Canada, where populations of over 50,000 bees per colony have been registered(2). It may be inferred that the management previous to the honey harvest of the colonies studied herein might have not been adequate. This hypothesis is based on the fact that, unlike the regions of Chiapas and Canada, the blossom periods of the semi-arid high plateau of Mexico are generally sudden and short but occur with an abundant nectar flow, which demands that the beekeepers be more efficient in managing their colonies to be able to better exploit the floral resources available. The low population size of colonies observed in this study is understandable, because most beekeepers in Mexico prefer not to feed their colonies before the blossom seasons, expecting that they will strengthen during the season (personal observation). As a result of this strategy, the mean yield per colony tends to be low, since the colonies reach their maximum populations at the end of the blossom season. Therefore, it would make sense to carry out studies to compare honey yields between colonies with alternate management strategies that include requeening and the administration of artificial feeding (energetic and protein), as well as disease and parasite control previous to the blossom seasons, since it is known that various pathologies can significantly affect the productivity and populations of honey bee colonies in the Mexican high plateau(19,22,23). Such studies would allow making specific recommendations for increasing the honey production and survival of honey bee colonies in the winter. It is concluded that, compared to other regions, the natural conditions of the semi-dry semiwarm region offer the best possibilities of development for honey bee colonies, particularly in the fall, which does not necessarily result in a larger amount of stored honey, but may translate into a larger amount of brood and bees for reproductive purposes meant to produce honey bee nuclei. It is also concluded that, in general, the size of the bee populations found in the colonies studied during two blossom seasons are not optimal for the production of honey, and thus, it is proposed that they may be increased with management practices validated by scientific studies.

Acknowledgements The authors wish to thank Laura Espinosa, José Luis Uribe, Carlos Aréchiga, and Ramón Gutiérrez for their valuable contributions to a previous version of this manuscript.

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Secretaría de Agricultura, Ganadería, Desarrollo Rural, Pesca y Alimentación. (SAGARPA). Servicio de información estadística agroalimentaria y pesquera (SIAP). 2011. http://www.siap.sagarpa.gob.mx. Consultado Sep 18, 2017.

Szabo TI, Lefkovich LP. Effect of brood production and population size on honey production of honeybee colonies in Alberta, Canada. Apidologie 1989;20(2):157-163.

Fewell JH, Winston ML. Colony state and regulation of pollen foraging in the honey bee, Apis mellifera L. Behav Ecol Soc 1992;30(6):387-393.

Guzmán-Novoa E, Eccles L, Calvete Y, Mcgowan J, Kelly PG, Correa-Benítez A. Varroa destructor is the main culprit for the death and reduced populations of overwintered honey bee (Apis mellifera) colonies in Ontario, Canada. Apidologie 2010;41(4):443-450.

INEGI. Instituto Nacional de Estadística Geografía e Informática. Municipios de Zacatecas. 2005.

Acosta-Castellanos S, Quiroz-García L, Arreguín-Sánchez MDLL, Fernández-Nava R. Análisis polínico de tres muestras de miel de Zacatecas, México. Polibotánica 2011;(32):179-191.

Franco OVH, Siqueiros DME, Hernández AEG. Flora apícola del estado de Aguascalientes. 1ra ed. Aguascalientes, México: Universidad Autónoma de Aguascalientes; 2012.

Delaplane KS, van der Steen J, Guzman-Novoa E. Standard methods for estimating strength parameters of Apis mellifera colonies. J Apic Res 2013;52(1): 1-12.

Guzmán-Novoa E, Correa BA, Espinosa MLG, Guzmán G. Colonización, impacto y control de las abejas melíferas africanizadas en México. Vet Méx 2011;42(2):149-178.

10. Zarr JH. Biostatistical analysis. . Upper Saddle River, New Jersey: Prentice Hall; 1999. 11. SAS. SAS User´s Guide: Statistics (version 9 ed.). Cary NC, USA: SAS Inst. Inc. 2002. 12. Woyke, J. Correlations and interactions between population, length of worker life and honey production by honeybees in a temperate region. J Apic Res 1984;23(3):148-156.

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13. Winston ML. The biology of the honey bee. Cambridge Massachusets EU: Harvard University Press; 1991. 14. Schmickl T, Crailsheim K. Inner nest homeostasis in a changing environment with special emphasis on honey bee brood nursing and pollen supply. Apidologie 2004; 35(3):249-263. 15. Brodschneider R, Crailsheim Apidologie 2010;41(3):278-294.

Nutrition

and

health

honey

bees.

16. Keller I, Fluri P, Imdorf A. Pollen nutrition and colony development in honey bees: part 1. Bee World 2005;(86):3-10. 17. Somerville, D. Fat bees skinny bees. A manual on honey bee nutrition for beekeepers. Australian Government Rural Industries Research and Development Corporation, Goulburn. 2005; 1-142. file:///C:/Users/HDC/Downloads/05-054.pdf. Accessed Jan 13, 2017. 18. Medina-Flores CA, Guzmán-Novoa E, Aréchiga-Flores CF, Aguilera-Soto JI, Gutiérrez-Piña FJ. Effect of Varroa destructor infestations on honey yields of Apis mellifera colonies in Mexico’s semi-arid high plateau. Rev Mex Cienc Pecu 2011;2(3):313-317. 19. Medina-Flores CA, Guzmán-Novoa E, Aréchiga Flores CF, Gutiérrez Bañuelos H, Aguilera Soto JI. Producción de miel e infestación con Varroa destructor de abejas africanizadas (Apis mellifera) con alto y bajo comportamiento higiénico. Rev Mex Cienc Pecu 2014;5(2):157-170. 20. Zaitoun ST, Al-Ghzawi AM, Shannag HK. Population dynamics of the Syrian Honeybee, Apis mellifera syriaca, under semi-arid Mediterranean conditions. Zoology in the Middle East 2000;21(1):129-132. 21. Mondragón L, Spivak M, Vandame R. A multifactorial study of the resistance of honeybees Apis mellifera to the mite Varroa destructor over one year in Mexico. Apidologie 2005;36(3):345-358. 22. Arechavaleta-Velasco ME, Guzmán-Novoa E. Honey production with fluvalinatetreated and untreated honey bee (Apis mellifera L.) colonies in Valle de Bravo, Mexico. Vet Méx 2000;(31):381-384.

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23. Medina-Flores CA, Guzmán-Novoa E, Espinosa-Montaño LG, Uribe-Rubio JL, Gutiérrez-Luna R, Gutiérrez-Piña FJ. Frequency of varroosis and nosemosis in honey bee (Apis mellifera) colonies in the state of Zacatecas, Mexico. Rev Chapingo Ser Cie 2014;20(3):159-167.

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http://dx.doi.org/10.22319/rmcp.v10i1.4451 Technical note

Botanical composition and nutritive value of the diet consumed by cattle in an area invaded by natal grass [Melinis repens (Willd.) Zizka]

Obed Gabriel Gutiérrez Gutiérreza Carlos Raúl Morales Nietoa* José Carlos Villalobos Gonzálezb Oscar Ruíz Barreraa Juan Ángel Ortega Gutiérreza Jorge Palacio Nuñezc

Universidad Autónoma de Chihuahua. Facultad de Zootecnia y Ecología. Km 1 Perif. Francisco R. Aldama, 31453, Chihuahua, Chih. México. b

Texas Tech University. Lubbock Texas. USA.

Colegio de Posgraduados, Campus San Luis Potosí. México.

*Correspondingauthor: cnieto@uach.mx

Abstract: The objective was to evaluate the botanical composition and nutritional value in the diet of bovine cattle in areas invaded by natal grass [Melinis repens (Willd.) Zizka]. The research was conducted at the Salinas Ranch, in the municipality of Satevó, Chihuahua, in a brush grassland. Botanical composition of the area was determined by the line-point intercept method. Sampling was conducted from August 2013 to February 2014. The botanical composition of the diet (microhistological technique) and the nutritional value were determined using two esophageal-fistulated Hereford/Angus heifers (350 ± 5 kg). The data were subjected to a variance analysis, and the chemical composition of the diet was fitted using the PROC MIXED procedure of SAS to a mixed model. The average available forage during the four phenological stages was 1,279 kg DM ha-1, with a presence of 87.5 % natal grass (1,119.13 kg DM ha-1). The highest preference indexes were for Aristida divaricata (8.43) and Croton pottsii (12.95) during the growing stage; whereas the least preferred 212

Rev Mex Cienc Pecu 2019;10(1):212-226

species was Melinis repens (0.33 to 0.41). The highest crude protein content was observed during the growing (13.23 %) and flowering stages (10.71 %). During this study the best quality of the diet was determined during the growing and flowering stages and was mainly composed of Melinis repens during four stages. Key words: Preference index, Voluntary intake, Melinis repens.

Received: 25/03/2017 Accepted: 06/03/2018

Beef production in extensive systems depends mainly on the quantity and quality of available forage that are present in the pasturelands and are the cheapest food for the cattle. In northern Mexico, rainfalls usually occur from June to September (80 %), the period with the highest weight gains and the highest profitability(1). One of the most important economic activities for livestock in the state of Chihuahua is the cow/calf system, which consists in the production of calves for export(2,3). However, in recent years, the cattle industry has suffered losses due to droughts and to poor management of the grasslands. The result has been a loss in the output of the grassland and a reduction of the rangeland, due to forced sales and to the slaughter of the livestock under poor conditions(4,5). Furthermore, large grassland areas have undergone changes in their structure due to the introduction of, and invasion by non-native species, which have an ecological impact through the loss of native forage species(6,7). Natal grass (Melinis repens) is an opportunistic species that has spread in the last 30 yr across the Mexican territory(7), as it establishes quickly and displaces native species with an ecological, economic and livestock importance(8). Its forage value ranges between fair and bad during the latency period, when it can attain raw protein (RP) values of 4 %(7). However, the degree of preference by grazing animals is unknown. In Chihuahua, this species has moved from the center-south to the north of the state and is located mainly in areas that have been degraded due to overgrazing and in abandoned lands that were opened to agricultural use. The studies on the diets of grazing bovine cattle in Chihuahua date back to the 1980s; these studies were performed in areas of the central-northern region and at a time when the invasion by M. repens was at its initial stage or when this species was not yet present(9,10,11). Knowledge of the composition of the diet and of the nutritional contribution of forage plants in invaded areas may be helpful for designing and executing schemes of use and management of both the grasslands and the grazing cattle. Various techniques have been utilized to gain knowledge of the botanical composition of the diet of grazing cattle. One of these is the microhistology, which allows identifying and 213

Rev Mex Cienc Pecu 2019;10(1):212-226

quantifying the botanical composition of the diet consumed(11,12). Furthermore, it is important to know the nutritional value of the diet of the grazing cattle in order to establish the necessary supplementation during the critical time, when the requirements are not met by the grazing animals. For these reasons, and because there is no information on grasslands invaded by M. repens(13), this study evaluated the botanical composition and the nutritional value of the diet of the grazing cattle in an area invaded by M. repens. This study was conducted at the “Salinas” Ranch, located in the municipality of Satevó, Chihuahua, located at 27° 57’ 00” N and 106° 07’ 00” W, and at an altitude of 1,540 m asl. Average annual temperature is 18.1 °C, and its historical mean annual precipitation, 464 mm(14). However, in the year 2013, according to CONAGUA(15), there was a mean precipitation of 550 mm; the rainfalls during the study year were mainly distributed from July to September and November (Figure 1). Climate of the area is classified, according to Köppen, as BWh(16). The soils are shallow (0 to 25 cm), regular internal drainage, and a pH of 5.3 to 6.6(16).

Figure 1: Mean precipitation (mm) in the year 2013 during the study period(14) 250

Precipitation (mm)

200 150 100 50 0 E

Months

This study was conducted in an area of 200 ha and has a rangeland coefficient of 4 ha UA-1, which was determined based on the amount of usable forage (1,470 kg ha-1) and the requirements of the type of animal(10,17). This area was selected because it is representative of the grasslands invaded by M. repens. The vegetation type is short-midgrass grassland invaded by M. repens, and with the presence of shrub species like Mimosa biuncifera and Prosopis glandulosa, and grasses like Bouteloua gracilis, Bouteloua curtipendula, among others (Table 1)(16,18).

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Table 1: Botanical composition of the area of study during the vegetative stage Coverage (%)1

Shrubs

Bouteluoa curtipendula

0.41

Aloysia wrightii

Bouteluoa gracilis

2.50

Calliandra eriophylla

Melinis repens

63.72

Grasses

Coverage Coverage Herbaceous species (%)1 (%)1 Bulbostilis 1.46 0.63 juncoides 9.60

Condalia sp. Juniperus monosperma Mimosa biuncifera

0.21 1.25 1.67

Dichondria argentea Euphorbia sp. Evolvolus alsynoides Haploppapues gracilis

0.41 0.21 9.60 0.21

Prosponis glandulosa

2.50

Macrosiphonia hypoleuca

0.21

Tecoma stands

0.21

Millia biflora

0.62

Sida procumbens

3.76

Croton pottsii

1.00

Determined with the point intercept method(18).

The botanical composition and the quality of the diet were conducted during four sampling stages (August, 2013, to February, 2014), corresponding to the phenological stages of the grasses (vegetative, reproductive, post-reproduction and dormant season) present in the area (Table 2). The first sampling was carried out during the vegetative stage (August 3 to 7, 2013); the second, during the reproductive stage (October 1 to 5, 2013); the sampling for the post-reproduction stage was carried out on December 3 to 7, 2013, and the dormant season was conducted during February 1 to 5, 2014. Two Hereford/Angus heifers with an average weight of 350 Âą 5 kg, fistulated (with a Bar DiamondTM esophageal fistula)(19,20,21). Holechek(12) mentions that the botanical composition in grasslands with a very homogeneous vegetation can be determined using two animals during two to three days; for this reason, two fistulated animals were utilized during a 5-d grazing period.

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Table 2: Botanical composition (%) of the grasses in the study area Sampling stages

Species

Vegetative

Reproductive Post-reprod. Dormancy

0.571

--2

0.611

Bothriochloa barbinodis

4.12

1.15

0.81

Bouteloua chondrosioides

4.67

0.37

0.99

Bouteloua curtipendula

9.58

7.61

3.26

3.60

Bouteloua gracilis

10.15

7.35

4.89

3.49

Bouteloua hirsuta

2.44

1.75

1.32

Heteropogon contortus

1.01

1.48

Leptochloa dubia

1.11

0.90

Muhlenbergia phleoides

1.01

0.61

0.86

79.68

71.68

86.96

85.94

Aristida divaricata

Melinis repens 1

Values calculated based on the biomass production. 2 Not observed in the reading.

Heifers were given a 3-d adaptation period in the study area before each sampling. Heifers were put in a corral during the night before sampling, fasting from water and food to avoid sampling contamination. In the morning, they were placed in the study area during 45 to 60 min, after which the bags were withdrawn with the collected sample. The samples were taken to the animal nutrition laboratory of the Faculty of Zootechnics and Ecology, to be dried in a forced air stove at 60 Â°C during 72 h, and subsequently ground using a WileyTM mill with a 1 mm mesh (Arthur H. Tomas, Philadelphia, PA, USA)(22,23). Dry matter yield. In order to estimate the dry matter yield (kg MS ha-1), 25 points were selected at random, and a 0.25 m2 quadrant was utilized to cut the forage. The grasses (separated by species) in each quadrant were cut at ground level. The forage samples were dried in a stove at 75 Â°C during 72 h and weighed at the Laboratory of Animal nutrition of the Faculty of Zootechnics and Ecology of the Universidad Autonoma de Chihuahua (FZyEUACH). The percentage of each species was calculated based on the weights obtained during the four phenological stages, using a Tor ReyTM L-EQ scale, and the dry weight was extrapolated to the production of DM per hectare, according to the following formula: DM ha-1=

đ?&#x2018;¤đ?&#x2018;&#x2019;đ?&#x2018;&#x2013;đ?&#x2018;&#x201D;â&#x201E;&#x17D;đ?&#x2018;Ą đ?&#x2018;&#x153;đ?&#x2018;&#x201C; đ?&#x2018;Ąâ&#x201E;&#x17D;đ?&#x2018;&#x2019; đ?&#x2018;&#x2018;đ?&#x2018;&#x;đ?&#x2018;Ś đ?&#x2018; đ?&#x2018;&#x17D;đ?&#x2018;&#x161;đ?&#x2018;?đ?&#x2018;&#x2122;đ?&#x2018;&#x2019; (đ?&#x2018;&#x201D;)â&#x2C6;&#x2014;4 1000 đ?&#x2018;&#x201D;

216

â&#x2C6;&#x2014; 10,000

Rev Mex Cienc Pecu 2019;10(1):212-226

Botanical composition of the area. The botanical composition was measured in two different ways: A general study of the present vegetation in July was described using the line-point intercept method(18), in order to have a reference of the species present in the study area. The measurement was taken only in July because the composition of the shrubs does not change with the various stages(17). The second vegetation measurement was done counting the presence or absence of grasses during each phenological stage using a 0.25 m2 quadrant. Botanical composition of the diet. The vegetal tissues of the species present in the diet of the cattle were identified using the microhistological technique modified by PeĂąa and Habib(11), which reads five tissue slides, and 20 fields in each of these. The work was carried out in the Water-Soil Plant Laboratory of the Colegio de Posgraduados, COLPOS), Campus SLP. Preference index. The index of preference by the species was estimated based on the botanical composition of the diet and of the area, using the formula proposed by Van Dyne and Heady(24). PI =

Botanical composition of the diet Botanical composition of the area

Higher values represent a greater preference by the cattle, and smaller values, a lower level of preference. After the samples were prepared (30 for each sampling period) were prepared, they were subjected to chemical analyses in order to determine their raw protein content and in vitro digestibility. These were conducted at the laboratory of animal nutrition of FZyEUACH. The crude protein content (CP) was determined using the Kjeldahl method: the amount of nitrogen (N) in the sample was multiplied by 6.25(22). Furthermore, the in vitro digestible organic matter was determined in a Daisy II incubator, following the methodology proposed by AnkomTM (Ankom Technology, Fairport, NY, USA)(23). The neutral (NDF) and acid detergent fiber (ADF) were determined using the methodology proposed by Van Soest et al(25). In order to carry out the statistical analysis of the botanical composition of the diet, only the category of grasses, herbs and shrubs was included. The data were subjected to a variance analysis in a completely randomized design (Îą= 0.05), using the MIXED procedures of the SAS software(26). The equation of the statistic model utilized was: đ?&#x2018;Śđ?&#x2018;&#x2013;đ?&#x2018;&#x2014; = Âľ + đ?&#x2018;&#x192; đ?&#x2018;&#x2013; + đ?&#x2018;&#x2019;đ?&#x2018;&#x2013;đ?&#x2018;&#x2014; Where: đ?&#x2019;&#x161;đ?&#x2019;&#x160;đ?&#x2019;&#x2039; = value of the response variable (for each species and for the groups) observed at the ith phenological stage; Âľ= effect of the overall mean; đ?&#x2018;ˇ đ?&#x2019;&#x160; = fixed effect of the ith phenological stage; 217

Rev Mex Cienc Pecu 2019;10(1):212-226

đ?&#x2019;&#x2020;đ?&#x2019;&#x160;đ?&#x2019;&#x2039; = term of the random error associated with the observations, where đ?&#x2018;&#x2019;đ?&#x2018;&#x2013;đ?&#x2018;&#x2014; ~đ?&#x2018; đ??źđ??źđ??ˇ(0, đ?&#x153;&#x17D; 2 ). The chemical composition data were subjected to a variance analysis, adjusting a mixed model with the PROC MIXED procedure of the SAS software(26), with the following equation: đ?&#x2018;Śđ?&#x2018;&#x2013;đ?&#x2018;&#x2014;đ?&#x2018;&#x2DC; = Âľ + đ?&#x2018;&#x192; đ?&#x2018;&#x2013; + đ?&#x2018;&#x2030;đ?&#x2018;&#x2014; + đ?&#x153;&#x192;đ?&#x2018;&#x2013;đ?&#x2018;&#x2014; + đ?&#x2018;&#x2019;đ?&#x2018;&#x2013;đ?&#x2018;&#x2014;đ?&#x2018;&#x2DC; Where: đ?&#x2019;&#x161;đ?&#x2019;&#x160;đ?&#x2019;&#x2039;đ?&#x2019;&#x152; = value of the response variable (OM, CP, ivDOM, NDF, ADF) observed at the ith phenological stage in the jth fistulated animal; Âľ= effect of the overall mean; đ?&#x2018;ˇ đ?&#x2019;&#x160; = fixed effect of the ith phenological stage; đ?&#x2018;˝đ?&#x2019;&#x2039; = random effect of the jth fistulated animal; đ?&#x153;˝đ?&#x2019;&#x160;đ?&#x2019;&#x2039; = random effect of the interaction between the ith phenological stage and the jth fistulated animal; đ?&#x2019;&#x2020;đ?&#x2019;&#x160;đ?&#x2019;&#x2039;đ?&#x2019;&#x152; = term of the random error associated with the observations, where đ?&#x2018;&#x2019;đ?&#x2018;&#x2013;đ?&#x2018;&#x2014;đ?&#x2018;&#x2DC; ~đ?&#x2018; đ??źđ??źđ??ˇ(0, đ?&#x153;&#x17D; 2 ). Where a significant effect (P<0.05) of the phenological stage was observed, the least significant difference (LSD) test was utilized for the mean comparison (Îą = 0.05). The dry matter yields were different (P<0.05) between stages (Figure 2). The greatest output (2,119 kg MS ha-1) occurred at the latency stage, due perhaps to the residual humidity of the November rainfalls. Furthermore, Figure 3 shows the forage yield of M. repens, which represents 72.38 to 88.55 % of the botanical composition of the area. However, another study(27) reports a dry matter production of 2,913 kg ha-1 in grasslands invaded by M. repens during a rainy year in Aguascalientes, Mexico. However, the production in dry years was 1,488 kg ha-1. This shows that the amount of precipitation and humidity in the soil are important factors to consider. The mean precipitation in the study area during the study year was 510 mm (considered atypical), while the historical annual mean for these areas is 462.4 mm(14).

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Rev Mex Cienc Pecu 2019;10(1):212-226

Figure 2: Least square means of the total yield and of the yield of Melinis repens during the phenological stages

2500.00 Total

Melinis repens

Production, DM Kg ha-1

2000.00

d b

1500.00

c b

1000.00

500.00 a

0.00 1

Stages

abcd

Different letters between columns indicate a difference (P<0.05).

Table 3 shows the species consumed by the grazing cattle in different sampling stages; during the dormant stage, M. repens was the species with the highest content in the diet (35.5 %), compared with the vegetative, reproductive and post-reproductive stages (27, 29 and 29 %, respectively). The content of this invasive grass in the diet exhibited a difference (P<0.05); this may be due to the occurrence of a regrowth, during the dormant season, that was consumed by the cattle. Furthermore, other studies report that the abundance of a species in a particular area may influence the diet of grazing animals(28,29). The diet consumed by the bovine cattle grazing in areas invaded by M. repens consisted primarily of grasses (74.05 Âą 1.66 %) during all four phenological stages. These findings agree with those reported by other authors(30), who pointed out that grasses are the main food consumed by grazing cattle.

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Table 3: Botanical composition (%) of the diet of bovine cattle in an area invaded by Melinis repens Species

Sampling stages Reproductive Post-reprod.

Vegetative

Grasses Aristida divaricata Bothriochloa barbinodis Bouteloua chondrosioides Bouteloua curtipendula Bouteloua gracilis Bouteloua hirsuta Heteropogon contortus Leptochloa dubia Muhlenbergia phleoides

Dormancy

4.81a 0.74a 4.06a 8.84a 9.23a 2.38a 0.36a 0.36a 0.71a 26.67a

5.01a 3.29b 4.96a 10.14a 13.59b 4.24b 2.86b 3.72b 2.87a 29.27a

4.63a 3.39b 6.02a 11.19a 12.07ab 3.85b 3.01b 2.58b 1.77a 28.86a

58.16a

79.95b

77.37b

12.95a 12.95

5.54b 5.54

4.72b 4.72

4.19b 4.19

Shrubs Calliandra eriophylla Prosopis glandulosa

15.85a 13.03a

Total

28.88a

8.58b 5.93b 14.51b

11.08ab 6.83b 17.91b

8.95b 6.13b 15.08b

Melinis repens Total Herbaceous species Croton pottsii Total

3.17a 3.63b 4.97a 11.12a 10.87ab 4.08b 2.37b 2.71b 2.29a 35.53b 80.74b

Means with different letters in the same row indicate a statistical difference (P<0.05).

Melinis repens was the species with the lowest preference index (ranging between 0.33 and 0.41) during the four stages, despite its high density in the study area. However, Bouteloua chondrosioides presented a high rate (16.26) at maturity, while Aristida divaricata presented an index of 8.43 during the stage of growth (Table 4). Despite the low density of these species in the study area, they presented the highest preference rates. This performance is supported by previous studies(28,31), where it was observed that species that showed greater preference index, were less present in the study area.

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Table 4: Preference index in an area invaded Melinis repens Species

Vegetative

Sampling stages PostReprodcutive reprod.

Dormancy

Grasses Aristida divaricata Bothriochloa barbinodis Bouteloua chondrosioides Bouteloua curtipendula Bouteloua gracilis Bouteloua hirsuta Heteropogon contortus Leptochloa dubia Muhlenbergia phleoides Melinis repens

8.431a --0.92a 0.91a ----0.34a

--2 0.80a 1.06a 1.33a 1.85b 1.74a -3.36a 2.84a 0.41a

-2.95ab 16.26b 3.43b 2.47bc 2.20ab 2.98a -2.91a 0.33a

5.19a 4.49b 5.02a 3.09b 3.11c 3.09b 1.60a 3.01a 2.66a 0.41a

Herbaceous species Croton pottsii

12.95a

5.54b

4.72b

4.19b

Shrubs Calliandra eriophylla Prosopis glandulosa

1.65a 5.21a

0.89b 2.37b

1.15ab 2.73b

0.93ab 2.45b

High values represent a high preference by the cattle. Not consumed by the cattle or not observed in the reading. abc Means with different letters in the same row indicate a difference (P<0.05). 2

The content of crude protein differed (P<0.05) between phenological stages. The highest values were found during the vegetative and reproductive stages (13 and 11 %, respectively). In contrast, the lowest values occurred during the dormancy stage (6.5 %; Table 5). However, another study reports CP values of 10.49 % during the summer, and 5.49 % during the spring; this may account for the fact that the animals are unable to meet their nutritional requirements(32). Besides, other authors report that, during the rainy season, the bovine cattle can satisfy its minimum maintenance requirements thanks to the phenology of the grasses(33); however, the nutrients diminish in winter, and therefore these requirements are unmet during this season(34). The CP values registered in the present research during the vegetative and reproductive stages were probably due to the consumption of species with high CP values, such as Bouteloua gracilis and Bouteloua curtipendula, shrubs like Prosopis glandulosa and Calliandra eriophylla, and the herbaceous species Croton pottsii(35,36,37). Moreover, the season of the year is another factor to be considered in this type of studies(38). Thus, it may

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be assumed that the reported CP values were not a result of the consumption of Melinis repens, as the CP values of this species range are 4 to 6 %(7).

Table 5: Means (±SE) of the chemical composition of the diet consumed by grazing bovine cattle in an area invaded by Melinis repens, during the phenological stages Phenological stage Reproductive Post-reprod.

Variable (%)

Vegetative

13.76±0.92ª

10.72±0.92b

8.61±0.92bc

6.559±0.92c

OM ivDOM NDF ADF

85.86±0.607a 41.36±1.86a 70.71±1.54a 42.80±1.38a

85.95±0.607a 38.53±1.86a 71.19±1.54a 42.46±1.38a

81.39±0.607b 43.08±1.86a 71.02±1.54a 47.74±1.38a

81.10±0.607b 36.56±1.86a 72.64±1.54a 42.70±1.38a

Dormancy

CP= crude protein; OM= organic matter; ivDOM= in vitro digestibility of the organic matter. NDF: ADF= neutral and acid detergent fiber. abc Means with different letters in the rows indicate difference (P<0.05).

The ivDOM ranged between 36.56 and 43.08 % (P>0.05; Table 5). This may be due to the structural change of the grasses, herbs, and shrubs during the development of the plants, which affects the amount of digestible tissue present in them(39). Other authors have reported values of 52.3 to 54.9 % in areas invaded by Melinis repens during the dormancy stage(13). This result agrees with those reported in another study, in which the ivDOM values were 67.34 and 58.23 % in the summer and the spring, respectively(32). Table 5 shows the data obtained for the neutral detergent fiber (NDF), for which no differences were found (P>0.05); however, these results differed from those of another study(32), which reported NDF values of 64 to 74 % in a grassland where Melinis repens was present. Other researchers(40,41) reported values of 69.2 to 70.1 %, which were similar to those estimated in the present study. Furthermore, Murillo(42) reported similar NDF values (70.4%) to ours during the dormancy stage. Likewise, the ADF was estimated, and no significant differences were found (P>0.05). However, other authors report values above those obtained in this study(32). The content of lignified polysaccharides increases with maturity, and therefore the ADF value also increases(43). Probably for this reason, the ADF values in the diet found in the present research ranged between 42.7 and 47.74 %. A recent study reports similar ADF values (42.3 %) to those obtained in this study. The botanical composition of the diet was constituted mainly by Melinis repens during the four phenological stages, as this was the most abundant grass in the study area. The grasses were preferred by the animals during the four sampling periods, and there was only one 222

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herbaceous species (Croton pottsii) during the sampling. The highest preference indices for M. repens were obtained during the dormancy and reproductive stages. The nutritional value of the diet of grazing bovine cattle in areas invaded by Melinis repens does not meet the requirements for the production and maintenance during the post-reproductive and dormancy stages. It is advisable to carry out studies with a focus on the planning and design of utilization schemes in grasslands invaded by exotic species.

Acknowledgements

The authors wish to express their gratitude to the National Council for Science and Technology (CONACyT), to the Universidad Autónoma de Chihuahua, UACH and to the “Produce Chihuahua” Foundation for its financial support. Also, to the Colegio de Postgraduados for allowing the use of its facilities for the research work.

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INEGI. Instituto Nacional de Estadística y Geografía. Anuario estadístico y geográfico de Chihuahua. Ed. Instituto Nacional de Estadística y Geografía. Aguascalientes, México. 2015.

INEGI. Instituto Nacional de Estadística y Geografía. Anuario estadístico del Estado de Chihuahua. Gobierno de Chihuahua. 1995.

Báez GAD, Reyes LG, Melgoza CA, Royo MM, Carrillo RR. Características productivas del sistema vaca-cría en el estado de Chihuahua. Tec Pecu Mex 1999;37(2):11-24.

SNIIM. Sistema nacional de información e integración de mercados. Mercados del exterior. En: http://www. economia-sniim.gob.mx/nuevo. Consultado 17 Oct 2013.

Callejas JN, Aranda GH, Rebollar RS, De la Fuente MM. Situación económica de la producción de bovinos de carne en el Estado de Chihuahua, México. Agron Mesoam 2014;25(1):133-139.

PACP-Ch. Plan de acción para la conservación y uso sustentable de los pastizales del desierto chihuahuense en el Estado de Chihuahua 2011-2016, Guzmán-Aranda JC, et al editores. Gobierno del Estado de Chihuahua, México. 2011.

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Melgoza CA, Balandrán MI, Mata GR, Pinedo C. Biología del pasto rosado Melinis repens (Will.) e implicaciones para su aprovechamiento o control. Revisión. Rev Mex Cienc Pecu 2014;5(4):429-442.

Villaseñor RJL, Espinosa GFJ. Catálogo de malezas de México. Universidad Nacional Autónoma de México. Consejo nacional consultivo fitosanitario. Fondo de Cultura Económica. México, DF. 1998.

Chávez SAH, González MH, Fierro LC. Consumo voluntario de forraje en vacas gestantes durante la época de sequía. Bol Pastizales. RELC-INIP-SARH. 1981.

10. Chávez SAH, Fierro LC, Habib R, Sánchez E, Ortiz V. Composición botánica y valor nutricional de la dieta de bovinos en un pastizal mediano abierto en la región central de Chihuahua. Téc Pecu Méx 1986;50:90-105. 11. Peña JM, Habib R. La técnica microhistológica; un método para determinar la composición botánica de la dieta de herbívoros. INIP-SARH. 1980;1:3-82. 12. Holechek JL, Vavra M, Pieper RD. Methods for determining the nutritive quality of range ruminant diets: A review. J Anim Sci 1982:54(2):363-376. 13. González FJ, Martínez M, Serna O, Carrete F. Georreferenciación de la dieta del ganado bovino durante el período de sequía en diferentes localidades en Durango. RELCINIFAP. 2012. 14. Medina G, Díaz G, Berzoza M, Silva MM, Chávez AH, Báez AD. Estadísticas climatológicas básicas del Estado de Chihuahua (periodo 1961-2003). INIFAP-CIRNC. Libro técnico No 1. 2006. 15. CONAGUA. Reporte del clima en México. Coordinación general del servicio meteorológico nacional gerencia de meteorología y climatología subgerencia de pronóstico a mediano y largo plazo. Reporte Anual 2013. 16. COTECOCA. Comisión Técnica Consultiva para la Determinación de los Coeficientes de Agostadero. Determinación de los Coeficientes de Agostadero Chihuahua. Secretaria de Agricultura y Recursos Hidráulicos. México. 1978. 17. Chávez SAH, Pérez GA, Sánchez GE. Intensidad de pastoreo y esquema de utilización en la selección de la dieta del ganado bovino durante la sequía. Téc Pecu Méx 2000;38(1):19-34. 18. Herrick JE, Van Zee JW, Havstad KM, Burkett LM, Whitford WG. Monitoring manual for grassland, shrubland and savanna ecosystems. Volume I: Quick start. USDA - ARS Jornada Experimental Range. Las Cruces, New Mexico. 2009.

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19. Holechek JL, Vavra M. The effects of slide and frequency observation numbers on the precision of microhistological analysis. J Range Manage 1981;34(4):337-338. 20. Holechek JL, Vavra M. Fistula sample numbers required to determine cattle diets on forest and grassland ranges. J Range Manage 1983;36:323-326. 21. Ellis WC, Bailey EM, Taylor CA. A silicone esophageal cannula; its surgical installation and use in research with grazing cattle, sheep or goats. J Anim Sci 1984;59(1):204-209. 22. AOAC. Official methods of analysis of the assoc. off anal. chem. 19ª ed. Wahington, DC. USA. 2012. 23. Ankom Technology. Procedures for fiber and in vitro analysis. https://www.ankom.com/product-catalog/daisy-incubator. Consultada 16 Nov, 2014. 24. Van Dyne GM, Heady HF. Botanical composition of sheep and cattle diets on a mature annual range. Hilgardia 1965;36:465-492. 25. Van Soest, PJ, Robertson JB, Lewis BA. Methods for dietary fiber, neutral detergent fiber, and non-starch polysaccharides in relation to animal nutrition. J Dairy Sci 1991;74(10):3583-3597. 26. SAS Institute Inc. SAS 9.1.3 User´s guide. Cary, NC, USA. 2006. 27. Díaz RA, Flores E, De Luna A, Luna JJ, Frías JT, Olalde V. Biomasa aérea, cantidad y calidad de semilla de Melinis repens (Willd.) Zizka, en Aguascalientes, México. Rev Mex Cienc Pecu 2012;3(1):33-47. 28. Launchbaugh KL, Stuth JW, Holloway JW. Inﬂuence of range site on diet selection and nutrient intake of cattle. J Range Manage 1990;43:109-115. 29. Ralphs MH, Pfister JA. Cattle diets in tall forb communities on mountain rangelands. J Range Manage 1992;45:534-537. 30. Beck JL, Peek JM. Diet composition, forage selection, and potential for forage competition among elk, deer, and livestock on aspen–sagebrush summer range. Rangeland Ecol Manag 2005;58(2):135-147. 31. Vásquez F, Pezo D, Mora DJ, Skarpe C. Selectividad de especies forrajeras por bovinos en pastizales seminaturales del trópico centroamericano: un estudio basado en la observación sistemática del pastoreo. Zootecnia Trop 2012;30: 063-080. 32. Reyes-Estrada O, Murillo-Ortiz M, Herrera-Torres E, Gurrola-Reyes JN, CarreteCarreón FO. Cambios estacionales en consumo, composición química y degradabilidad

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ruminal de la dieta seleccionada por novillos en pastoreo. Ecosistemas y Recursos Agropecuarios 2014;1(2):97-106. 33. Murillo OM, Reyes EO, Herrera TE, Martínez GJH, Villareal RG. Annual and seasonal variation in nutritive quality and ruminal fermentation patters of diets in steers grazing native rangelands. African J Agr Res 2013;8(33):4408-4413. 34. Villalobos GC, González VE, Ortega SJA. Técnicas para estimar la degradación de la proteína y materia orgánica en el rumen y su importancia en rumiantes en pastoreo. Téc Pecu Méx 2000;38(2):119-134. 35. Tena J, Ortiz V, Gómez F. Composición química de zacates nativos, introducidos y arbustivas en cuatro estados fenológicos. Bol. Pastizales. RELC-INIP-SARH. 1984. 36. CIPES. Centro de Investigaciones Pecuarias del Estado de Sonora. Manejo de Pastizales. 20 años de investigación pecuaria en el estado de Sonora. INIFAP-SARH. Gobierno del Estado. UGRS. 1989. 37. Morales NC, Madrid L, Melgoza A, Martínez M, Arévalo S, Rascón Q, Jurado P. Análisis morfológico de la diversidad del pasto navajita [Bouteloua gracilis (Willd. ex Kunth) Lag. ex Steud.], en Chihuahua, México. Téc Pecu Méx 2009;47(3):245-256. 38. Reyes O, Murillo M, Herrera E, Carrete FO. Seasonal and annual changes in the quality of native rangeland selected by grazing steers in northern Mexico. Cienc Inv Agr 2016;43(2):203-212 39. Vázquez de Aldana BR, García CA, Pérez CE, García CB. Elemental content in grassland of semiarid zones: effect of topographic position and botanical composition. Commun Soil Sci Plant Anal 1993;24(15-16):1975-1989. 40. Olson KC. Diet sample collection by esophageal fistula and rumen evacuation techniques. J Range Manage 1991;44:515-519. 41. Clark A Del Curto T, Vavra M, Dick BL. Stocking rate and fuels reduction effects on beef cattle diet composition and quality. Rangeland Ecol Manag 2013;66:714-720. 42. Murillo OM, Palacio CC, Reyes EP, Carrete CFO, Ruiz BO. Valor nutricional de la dieta consumida por ganado bovino en un pastizal mediano arbosufrutescente durante tres estaciones del año. AGROFAZ 2004;4:561-566. 43. Scales, CH, Streeter CL, Denham AH, Ward GM. Effect of mastication, salivary contamination and leaching on the chemical composition of forage samples collected via esophageal fistulae. J Anim Sci 1974;38(6):1278-1283.

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http://dx.doi.org/10.22319/rmcp.v10i1.4327 Technical note

Mean lethal dose (LD50) and growth reduction (GR50) due to gamma radiation in Wilman lovegrass (Eragrostis superba)

Alan Álvarez-Holguína,b Carlos Raúl Morales-Nietob* Carlos Hugo Avendaño-Arrazatec Raúl Corrales-Lermab Federico Villarreal-Guerrerob Eduardo Santellano-Estradab Yaudiel Gómez-Simutad a

Instituto del Nacional de Investigaciones Forestales, Agrícolas y Pecuarias (INIFAP). Campo Experimental La Campana. Carretera Chihuahua-Ojinaga, Km 33.3. Aldama, Chihuahua, México. b

Universidad Autónoma de Chihuahua. Facultad de Zootecnia y Ecología. Perif. Francisco R. Almada, Km 1. 31000 Chihuahua, Chihuahua, México. c

Instituto del Nacional de Investigaciones Forestales, Agrícolas y Pecuarias (INIFAP). Campo Experimental Rosario Izapa, Chiapas. México. d

SENASICA. Departamento de Irradiación; complejo MOSCAMED-MOSCAFRUT, Metapa de Domínguez, Chiapas. México. *Corresponding author: cnieto@uach.mx.

Abstract: Gamma radiation can be utilized as a mutagenic agent for inducing genetic variability in plant species. However, the adequate dose of radiation must be established before starting a mutagenesisbased breeding program. The objective was to determine the mean lethal dose (LD50) and the dose for the mean growth reduction (GR50) in Wilman lovegrass (Eragrostis superba Peyr.). For this purpose, the seeds were radiated with doses of 0 (control treatment), 100, 200, 300, 450, 600, 900,

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1400, 2000 and 4000 Gray. The evaluated variables were germination percentage, germination speed index, plumule length, radicle length, forage yield, seed production, leaf-stem ratio and chlorophyll concentration index. The data were analyzed through regression analyses and the Dunnettâ&#x20AC;&#x2122;s mean comparison test. The LD50 and GR50 generated for each of the evaluated variables were calculated with the resulting regression equation. Based on the values of LD50 and GR50, a weighted mean was estimated; the LD50 was weighted with 30 % while the GR50 with 10%. In general, all the evaluated characteristics were affected by the radiation treatment (P<0.05), and their behavior was adjusted to linear square models (P<0.05), allowing the determination of the LD50 and the GR50. The weighting average of both parameters, estimated at 2486 Gy, is recommended for the genetic breeding of Wilman lovegrass. The results of this study will allow implementing mutagenesis-based plant breeding programs in Wilman lovegrass. Key words: Cobalt 60, Gamma radiation, Mutations, DL50, RC50.

Received: 15/11/2016 Accepted: 01/05/2018

The median lethal dose (LD50) and the median growth reduction (GR50) are parameters utilized to establish the adequate irradiation dose to induce mutations in plant breeding programs. Mutation induction has the purpose of generate genetic and phenotypic variability, which may allow to select plants with characteristics that are not found in nature. Several researchers agree that the highest probability to generate useful mutations for breeding programs occurs at doses where the 50% of the irradiated individuals die(1-4). Likewise, other researchers have pointed out that another dose with a high probability of producing effective mutations, besides the LD50, is where the 50% of a growth reduction (GR50) occurs(5,6). Notably, both parameters (LD50 and GR50) are based on the assumption that low doses of irradiation produce minimum impacts on the genome, which rarely generate phenotypic changes; whereas high doses may produce multiple impacts on the genome which consistently produce aberrations or negative changes(7,8). Therefore, the first step in a mutagenesis-based breeding process is to determine the LD50 and the GR50. In Mexico, most of the arid and semi-arid grasslands are degraded due to the overgrazing and other anthropogenic practices(9). Such degradation has caused a drop in the vegetation cover, large stretches of bare ground and biodiversity loss, reducing the functionality and productivity of these ecosystems. An alternative to rehabilitate these degraded systems is the revegetation by seeding, for which the use of native vegetation is recommended. Nevertheless, this type of vegetation has a limited establishment ability in areas with a high degree of degradation.

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Therefore, the alternative is to use introduced species with a higher rusticity and establishment ability, like the Wilman lovegrass (Eragrostis superba). This grass is considered one of the species with the highest potential to be used in grassland rehabilitation programs(10), as it has a higher establishment ability than the native species used in this type of programs, like sideoats grama (Bouteloua curtipendula) and blue grama (Bouteloua gracilis), and even introduced species like weeping lovegrass (Eragrostis curvula)(11). However, it has a lower nutritional value and forage yield than other introduced grasses, such as buffel grass (Pennisetum ciliare), klein grass (Panicum coloratum) and even weeping lovegrass(12). The aforementioned suggests the possibility to subject the Wilman lovegrass to a plant breeding process. Nevertheless, since it is an introduced species, there may be little genetic variability of this species in Mexico. In this sense, mutagenesis may be an alternative for the genetic improvement of Wilman lovegrass, as it has proven to be a viable technique for inducing variability in grasses(13,14,15). However, the dose with the highest probabilities of producing effective mutations in this species is unknown so far. For this reason, the objective was to determine the LD50 and the GR50 in Wilman lovegrass in order to establish the optimal dose of gamma radiation for mutagenesis induction into this species. The experiment was carried out under laboratory and greenhouse conditions. Seeds of Wilman lovegrass var. Palar were radiated. The seeds were imported from the Curtis & Curtis company, located in Clovis, New Mexico, USA. Nine radiation doses and a control were evaluated: 0 (control), 100, 200, 300, 450, 600, 900, 1400, 2000 and 4000 Gray (Gy). The exposure times for the evaluated doses were determined using the Gafchromic dosimetry system and a RADCAL® Accu-dose ion chamber (Serial No. 4094118, USA). The seeds were radiated at the MOSCAFRUT SAGARPA//IICA Complex in Metapa de Domínguez, Chiapas, Mexico, in collaboration with the “Rosario Izapa” Experimental Station of INIFAP in Chiapas. The doses were applied within a Nordion GammaBeamTM-127 panoramic Gamma irradiator, with a dry storage source and an activity of 15 000 Curies of Co-60. The experimental design utilized for this test was completely randomized, with 10 radiation treatments and four repeats per dose, and considering each 90 mm Petri dish with cotton and filter paper and 50 seeds per repeat as the experimental unit. The Petri dishes were moisturized with 25 ml of water at the beginning of the test, and were subsequently sprayed with 2.0 ml every other day during the 15 d of duration of the test. The Petri dishes were then placed in a Precision Scientific 6M incubator at a temperature of 28 ± 2 °C. Those seeds that attained a 0.5 cm plumule or radicle were considered as germinated(16). The assessed variables were: germination percentage (GP), germination speed index (GSI), plumule length (PL), and radicle length (RL). In order to obtain the RL and the PL, three seedlings per Petri dish were allowed to grow for 7 d after germination. The GSI was estimated using the following equation(16): GSI=∑ ni/t Where: GSI = germination speed, n¡ = number of seeds germinated per day, t = day of germination.

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The greenhouse experiment was assessed using a randomized block experimental design with 10 repeats per treatment, establishing the blocks perpendicularly at the sunlight expose during the day. Twenty (20) seeds were sown in each flowerpot in order to ensure emergence and establishment; however, only one plant was left per pot. The seeds were sown in black polyethylene bags with a height of 26 cm and a diameter of 18 cm, perforated at the bottom. The bags were filled with 23 cm of alluvial loamy sandy soil. They were watered up to the saturation point every two or three days, according to the desiccation of the soil. The test was conducted during 16 wk from April to August. The assessed variables were forage yield (FY), seed production (SP), leaf:stem ratio (LSR), and chlorophyll concentration index (CCI). All the seeds of each plant were collected and put into paper bags in order to calculate the SP. For the FY, the biomass was cut at 5 cm from the ground; the stems and the leaves were then separated and placed in paper bags. The samples of both forage and seeds were dried in an oven at 65 °C during 72 h. Once the samples were dry, they were weighed in a Mettler Viper BC analytical scale. The CCI was measured at the middle part of five leaves selected at random, using an Opti-Sciences CCM-200 meter. In order to ensure the ranges of temperature (T) and relative humidity (RH) required by Wilman lovegrass, measurements were taken at the nursery with an HMP60 probe (Vaisala, Woburn, MA, USA). These data were registered every second and were averaged every minute in a CR1000 datalogger (Campbell Scientific Inc., Logan, UT, USA). The mean T during the experiment was 26.7 ± 5.6 °C, with a minimum temperature of 17.1 °C and a maximum temperature of 44.7 °C. The mean RH was 52.0 ± 16.8 %. The data were analyzed with a regression analysis for each variable. The mean lethal dose (LD50) was estimated using the resulting regression equation from the germination percentage. The same procedure was utilized to estimate the mean growth reduction (GR50) of the variables germination speed index, plumule length, radicle length, forage yield, seed weight, leaf:stem ratio, and chlorophyll concentration index. Furthermore, all the data were subjected to a variance analysis and to Dunnett’s mean comparison test, where the influence factor was the radiation dose with a significance level of 0.05 (α=0.05). The analyses were performed using the REG and GLM procedures of the SAS 9.1.3 statistical package(17). A weighted mean was estimated based on the results of the LD50 and the GR50 obtained for the eight variables. The LD50 was weighted with 30 %, and the GR50, with 10 % for the remaining variables (GP, GSI, PL, RL, FY, SP, LSR, and CCI). A single value was thus obtained, whereby the optimal dose of gamma radiation for inducing mutagenesis in Wilman lovegrass was established. The germination percentage was the variable to which the highest weighting was assigned, because the death of the individual indicates the maximum damage that radiation can produce. The behavior of the GP exhibited a quadratic tendency (P=0.008). Furthermore, there were differences (P<0.05) between all the radiation doses and the control treatment (T-0). In general, 230

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the GP tended to diminish as the radiation dose increased (Figure 1a). The regression equation indicates that the LD50 in Wilman lovegrass occurs at 1,529.1 Gy. Likewise, the GSI exhibited a quadratic tendency (P=0.001), and there were differences (P<0.05) between all the radiation treatments and the T-0. The GSI also diminished as the radiation dose increased (Figure 1b). According to the regression equation, for this variable, the GR50 occurred at 805.3 Gy.

Figure 1: Effect of different doses of radiation with Co-60 on the germination percentage (a), the germination speed index (b), the plumule length (c) and the radicle length (d) of Wilman lovegrass (Eragrostis superba) 10

60 y = 2E-06x2 - 0.0156x + 49.928 R² = 0.75

50 40 30 20 10

Germination speed index

Germination percentage (%)

y = 5E-07x2 - 0.0029x + 6.2704 R² = 0.71

7 6 5 4 3 2 1

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1000

2000

3000

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Gamma Irradiation Doses (Gy)

c) y = -0.0003x + 2.2007 R² = 0.94

2000

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1.5

0.5

Radicle length (cm)

Plumule length (cm)

2.5

1000

2.5

y = 2E-07x2 - 0.0012x + 2.0883 R² = 0.91

1.5 1 0.5 0

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1000

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Gamma Irradiation Doses (Gy)

The PL exhibited a negative linear tendency (P<0.0001). However, only the doses of 2,000 and 4,000 Gy exhibited a lower PL (P<0.05) than the T-0 (Figure 1c). According to the regression equation, in this variable the GR50 occurred at 3,905.3 Gy. Likewise, the RL exhibited a quadratic tendency (P<0.0001). For this variable, only the 900, 1400, 2000 and 4000 Gy treatments had a

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lower RL (P<0.05) than the T-0 (Figure 1d). The equation showed that, for this variable, the GR50 occurred at 1 037.8 Gy. The behavior of the FY exhibited a quadratic tendency (P=0.0009). There was an increase in this variable (P<0.05) with the doses of 450 and 600 Gy. It subsequently tended to diminish until it reached 4000 Gy, with which dose all the plants died before reaching 21 days of age (Figure 2a). The regression equation for this variable indicates that the GR50 occurred at 2,262.8 Gy.

Figure 2: Effect of different doses of radiation with Co-60 on the forage yield (a), seed production (b), leaf:stem ratio (c), and chlorophyll concentration index (d) of Wilman lovegrass (Eragrostis superba) a)

Forage yield (g)

y = -1E-06x2 + 0.0018x + 11.809 R² = 0.94

12 10 8 6

1800

Seed production (mg)

y = -0.0002x2 + 0.7417x + 719.06 R² = 0.75

1400 1200 1000 800 600 400 200

0 0

1000

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3000

4000

2.5

y = -0.0006x + 2.2999 R² = 0.82

2 1.5 1 0.5 0 0

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Gamma Irradiation Doses (Gy)

chlorophyll concentration index

Gamma Irradiation Doses (Gy)

leaf:stem ratio

1600

8 7

y = -0.0016x + 7.0164 R² = 0.83

6 5

4 3 2 1 0

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1000

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Gamma Irradiation Doses (Gy)

The SP exhibited a quadratic tendency (P<0.05). However, the only treatments with differences (P<0.05) in relation to the control were 1,400 and 4,000 Gy. There was an increase in the SP with the 1,400 Gy dose (P<0.05; Figure 2b). According to the regression equation, the GR50 on the SP occurred at 3,968.7 Gy. The LSR showed a linear tendency (P<0.0001). The only treatment that 232

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differed (P<0.05) from the control was 4,000 Gy radiation, because all the plants with this treatment died, and therefore the LSR was equal to 0. The GR50 for this variable occurred at 2,509.9 Gy. The CCI exhibited a linear behavior (P<0.0001). However, as the former variable, the only treatment that was different (P<0.05) from the control was 4,000 Gy. According to the regression equation, the GR50 occurred at 2,486.6 Gy. The weighted mean of the LD50 and GR50 resulting from the eight variables was 2 159.2 Gy. Wilman lovegrass germination decreased as the radiation dose increased. This result agrees with those of several authors, who found that the germination of various plant species tends to diminish with increasing radiation doses(18-21). The reason for this may be that high doses of radiation can inhibit functions that are vital to the cells, which may result in the death of certain cells, and even of the embryo in the seed. This phenomenon tends to increase with the radiation dose, and it is the cause of reduced germination(20). The radiation may damage compounds related to the plant metabolism â&#x20AC;&#x201D;such as auxins, ascorbic acid, chlorophyll, and proteinsâ&#x20AC;&#x201D;, potentially inhibiting the growth of the seedlings(22,23). It has been observed that, due to these disorders, seeds with high radiation doses cannot germinate, or their seedlings cannot survive beyond a few days(24), as was the case with the 4,000 Gy dose in this study. Furthermore, germination reduction has been ascribed to the fact that the frequency in chromosomal damage augments with increasing doses(22). This may change the expression of proteins and influence the functioning of the cells, potentially affecting the development of the seedlings and preventing germination(25). One of the grasses whose radiosensitivity has been most extensively studied is rice (Oryza sativa). A study of this species exposed 13 varieties to gamma radiation, and found that the LD50 ranged, according to the variety, between 345 and 423 Gy(26). Another study carried out in two varieties of rice established the LD50 at 288 and 354 Gy(27), while other researchers established it at 229 Gy(28). In other grasses, such as Pennisetum glaucum and Pennisetum typhoides, the LD50 has been determined at 669.3 and 200 Gy, respectively(28,29). As for forage grasses, the LD50 determined for different varieties of sudan grass (Sorghum sudanense) ranged between 307 and 342 Gy(3). Notably, the same agent was utilized in the above studies as in the present one. However, the results are lower than the LD50 obtained in this study for Wilman lovegrass. This result may be due, among other factors, to the variations in the moisture content of the seed between species, since the ionizing radiation may break the covalent bonds and cause the breakdown of water molecules, forming free radicals that may indirectly damage the various organelles of the cell and even the DNA molecules within the cell(30). Like the GP, the GSI of Wilman lovegrass tended to diminish with increasing radiation doses. This result agrees with the findings reported for peanut (Arachis hypogaea), where the germination speed diminished with the increased dose of radiation(31). The delay in germination may be due to the fact that high radiation doses may inhibit processes that are vital for the cell, such as protein synthesis and enzyme activity, which can delay cell division and, therefore, germination(20,32). 233

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The PL and the RL were observed to diminish with increased radiation doses. This result was also found for Eleusine coracana, in which the PL and RL were affected by the increase in the radiation dose, and the GR50 occurred at 500 Gy for both variables(33). The same effect was found in rice, where the GR50 occurred at 250 and 450 Gy, respectively, for the two variables(34). Reduction of the plumule and radicle lengths may be due to the fact that ionizing radiation usually affects plant metabolism and cell division, inhibiting or delaying the plantâ&#x20AC;&#x2122;s growth (20,31). In this regard, Kiong et al(22) found that gamma radiation can diminish the amount of proteins and chlorophyll compounds, affecting the plant metabolism. On the other hand, Preuss and Britt (35) found that the gamma radiation may inhibit plant growth because plants have a signal transduction mechanism that monitors cellular damage. This mechanism stops cell division whenever the cell structure is damaged. The FY and SP of Wilman lovegrass presented an increase with low radiation doses. This may be due to the fact that gamma radiation can increase the amount of photosynthetic pigments like aand b- chlorophylls and carotenoids(22). These pigments capture the sunlight photons for the plant to convert into energy compounds through photosynthesis(36). Therefore, an increase in the concentration of these pigments may increase the photosynthetic rates; this may have been the cause of the increase in forage yield and seed production in this study. The increase in FY and SP may also be due to the fact that gamma radiation sometimes increases the activity of antioxidant enzymes such as the superoxide dismutase and glutathione reductase, reducing the oxidative stress in the plant. This may help the plant deal more easily with the stress factors it faces on a daily basis, such as the fluctuations of temperature and sunlight that it receives, benefitting its growth(37,38). Nevertheless, after the increase in FY and SP, there was a decrease. This is due to the fact that radiation can also cause negative effects, as the exposure to gamma radiations frequently produces free radicals during the water radiolysis process. These free radicals are unstable chemical species that may damage cell organelles. In an experiment conducted by Wi et al.(39), gamma radiation was observed to produce important modifications in the structure of certain cell organelles of Arabidopsis thaliana. In this experiment, the tilacoids within the chloroplasts exhibited dilation and damages; the mitochondria displayed distorted forms, and the endoplasmic reticulum exhibited distended membranes. In addition, as it was mentioned above, radiation may cause the destruction of auxins, ascorbic acid, chlorophyll, and proteins, affecting the metabolism of the plants(22,23). It is unlikely that any of these phenomena may occur with low radiation doses; however, as the radiation dose augments, the probability of their occurrence increases(22). This may be why, after an increase in forage yield and seed production, there was a reduction of both variables. The LD50 and the GR50 are parameters utilized for determining the optimal radiation dose to induce effective mutations in genetic improvement programs. This is because the impact on the genome has been observed to be minimal and difficult to reflect, while with high doses, the genome may suffer multiple impacts that consistently produce anomalies or negative changes(7,8). Furthermore, low radiation doses may induce an increase in the cell division, the enzyme activity or the amount 234

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of photosynthetic pigments(31,34). In contrast, high radiation doses may also produce physical damage to the organelles or chemical damages in the cells, due to the destruction of enzymes and hormones, among others. However, because these changes were not produced through genetic modifications, they will not pass on to the next generations. In this sense, low and high radiation doses may generate in plants phenotypic changes that may be mistaken for genetic changes. Therefore, the optimal radiation dose must be established before starting a mutagenesis-based genetic improvement program; this will increase the possibility of finding effective mutations. The optimal radiation dose is established through the mean lethal dose or the mean growth reduction dose(6,7). In this study, the reduction that occurred in the values of all the variables due to radiation made it possible to determine the LD50 and GR50. However, the value of both parameters in each variable ranged between 805 and 3,905 Gy. Because of the amplitude of this range, a weighed mean was estimated in order to establish the optimal dose of the gamma radiation in the seed. The variable to which the highest weighting was assigned was the germination percentage, as the death of the individual indicates the maximum damage that radiation can produce. Low gamma radiation doses can produce an increase in certain agronomic attributes in Wilman lovegrass. However, in general all the assessed physical parameters were affected by high doses of gamma radiations, which made it possible to determine the mean lethal dose and the mean growth reduction. In order to attain the genetic improvement of Wilman lovegrass, it recommends using the optimal radiation dose obtained through the weighting of both parameters (2,486 Gy). This will contribute to the obtainment of new genetic material that can be utilized for the rehabilitation of grasslands.

Literature cited: 1. Lajonchere G, Mesa AR, Prieto M, Sánchez E. Curva de radiosensibilidad con guinea (Panicum maximum Jacq.) cv. K-249. Rev Pastos y Forrajes 1995;18:1-8.

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2. Morela F, González V, Castro L. Efecto de la radiación Gamma sobre la diferenciación de plantas de caña de azúcar a partir de callos. Agron Trop 2002;52:311-323. 3. GolubInova I, Gecheff K. M1 cytogenetic and physiological effects of gamma-rays in sudan grass (Sorghum Sudanense (piper.) stapf). Bulg J Agric Sci 2011;17:417-423. 4. Ángeles-Espino A, Valencia-Botín AJ, Virgen-Calleros G, Ramírez-Serrano C, ParedesGutiérrez L, Hurtado-De la Peña S. Determinación de la dosis letal (DL50) con Co60 en vitroplántulas de Agave tequilana var. Azul. Rev Fitotec Mex 2013;36:381-386. 5. Akgüm I, Tosun M. Agricultural and cytological characteristics of M1 perennial rye (Secale montanum Guss.) as affected by the application of different doses of gamma rays. Pak J Biol Sci 2004;7:827-833.

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6. Khalil SA, Zamir R, Ahmad N. Effect of different propagation techniques and gamma irradiation on major steviol glycoside’s content in Stevia rebaudiana. The J Anim Plant Sci 2014;24:1743-1751. 7. Songsri P, Suriharn B, Sanitchon J, Srisawangwong S, Kesmala T. Effects of gamma radiation on germination and growth characteristics of physic nut (Jatropha curcas L.). J Biol Sci 2011;11:268-274. 8. Thole V, Peraldi A, Worland B, Nicholson P, Doonan JH, Vain P. T-DNA mutagenesis in Brachypodium distachyon. J Exp Bot 2011;10:1-10. 9. Melgoza-Castillo A, Ortega-Ochoa C, Morales-Nieto CR, Jurado-Guerra P, VelezSanchez-Verin C, Royo-Márques MH, et al. Propagación de plantas nativas para la recuperación de áreas degradadas: opción para mejorar ecosistemas. Tecnociencia 2007;3:38-41. 10. Sáenz-Flores E, Saucedo-Terán RA, Morales-Nieto CR, Jurado-Guerra P, Lara-Macías CR, Melgoza-Castillo A, et al. Producción y calidad de semilla de pastos forrajeros como respuesta a la fertilización en Aldama, Chihuahua. Tecnociencia 2015;9:111-119. 11. Esqueda CMH, Melgoza CA, Sosa CM, Carillo RR, Jiménez CJ. Emergencia y sobrevivencia de gramíneas con diferentes secuencias de humedad/sequía en tres tipos de suelo. Téc Pecu Méx 2005;43:101-115. 12. Sanderson MA, Voigt P, Jones RM. Yield and quality of warm-season grasses in central Texas. J Range Manage. 1999;52:145-150. 13. López CE, Prina A, Griffa S, Ribotta AN, Carloni E, Tommasino E, Luna C, Biderbost E, Grunberg K. Obtaining new germplasm in Cenchrus ciliaris L. through induced-mutation and in vitro selection. Phyton 2011;80:59-64. 14. Pongtongkam P, Nilratnisakorn S, Piyachoknakul S, Thongpan A, Aranananth J, Kowitwanich K, Tadsri S. Inducing salt tolerance in purple guinea grass (Panicum maximum TD58) via gamma irradiation and tissue culture. Nat Sci 2005;39:681-688. 15. Pongtongkam P, Peyachoknagul S, Arananant J, Thongpan A, Tudsri S. Production of salt tolerance dwarf napier grass (Pennisetum purpureum cv. Mott) using tissue culture and gamma irradiation. Nat Sci 2006;40:625-633. 16. Maguire JD. Speed of germination-aid in selection and evaluation for seedling emergence and vigor. Crop Sci 1962;2:176-177. 17. Statistical Analysis System (SAS) Institute Inc. User´s guide. Vesion 9.1.3 Cary, NC, USA. 2006. 18. Anbarasan K, Rajendran R, Sivalingam D, Anbazhagan M, Chidambaram AA. Effect of gamma radiation on seed germination and seedling growth of Sesame (Sesamum indicum .L.) Var.TMV3. Int J Res Bot 2013;3:27-29. 236

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19. Bharathi T, Gnanamurthy S, Dhanavel D, Murugan S, Ariraman M. Induced Physical mutagenesis on seed germination, lethal dosage and morphological mutants of Ashwagandha (Withania somnifera (L.) Dunal). Int J Adv Res 2013;1:136-141. 20. Olasupo FO, Ilori CO, Forster BP, Bado S. Mutagenic Effects of Gamma Radiation on Eight Accessions of Cowpea (Vigna unguiculata [L.] Walp.). Am J Plant Sci 2016;7:339351. 21. Rajarajan D, Saraswathi R, Sassikumar D. Determination of lethal dose and effect of gamma ray on germination percentage and seedling parameters in ADT (R) 47 rice. IJABR 2016;6:328-332. 22. Kiong ALP, Lai AG, Hussein S, Harun AR. Physiological responses of Orthosiphon stamineus plantlets to gamma irradiation. Am-Eurasian J Sustain Agric 2008;2:135–149. 23. Shah TM, Mirza JI, Haq MA, Atta BM. Radio sensitivity of various chickpea genotypes in M1 generation I-Laboratory studies. Pak J Bot 2008;40:649–665. 24. Marcu D, Damian G, Cosma C, Cristea V. Gamma radiation effects on seed germination, growth and pigment content, and ESR study of induced free radicals in maize (Zea mays). J Biol Phys 2013;39:625-634. 25. Cheng L, Yang H, Lin B, Wang Y, Li W, Wang D, Zhang F. Effect of gamma-ray radiation on physiological, morphological characters and chromosome aberrations of minitubers in Solanum tuberosum L. Int J Radiat Biol 2010;86:791-799. 26. Harding SS, Johnson SD, Taylor DR, Dixon CA, Turay MY. Effect of gamma rays on seed germination, seedling height, survival percentage and tiller production in some rice varieties cultivated in Sierra Leone. Am J Exp Agric 2012;2:247-255. 27. Ramchander S, Ushakumari R, Pillai MA. Lethal dose fixation and sensitivity of rice varieties to gamma radiation. Indian J Agr Res 2015;49:24-31. 28. Ousmane SD, Elegba W, Danso K. Radio-sensibility of pearl millet (Pennisetum glaucum (L.) R. Br.) and cowpea (Vigna unguiculata (L.) Walp.) seeds germination and seedling growth. IJIAS 2013;4:665-671. 29. Ambli K, Mullainathan L. Effect of gamma rays and ems on seed germination and seed characters in pearl millet (Pennisetum typhoides) (Burn.)Stapf. Var. CO (Cu)-9. J Chem Biol Phys Sci 2014;4:3345-3349. 30. Alegre BN. Reacción celular ante la radiación. Radiobiología 2001;1:9-11. 31. Aparna M, Chaturvedi A, Sreedhar M, Kumar DP, Venu-Babu P, Singhal RK. Impact of gamma rays on the seed germination and seedling parameters of groundnut (Arachis Hypogaea L.). Asian J Exp Biol Sci 2013;4:61-68.

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32. Chandrashekar KRA. Gamma sensitivity of forest plants of Western Ghats. J Environ Radioact 2014;132:100-107. 33. Ambavane AR, Sawardekar SV, Sawantdesai SA, Gokhale NB. Studies on mutagenic effectiveness and efﬁciency of gamma rays and its effect on quantitative traits in ﬁnger millet (Eleusine coracana L. Gaertn). J Radiat Res Appl Sci 2014;8:120-125. 34. Talebi AB, Talebi AB. Radiosensitivity Study for Identifying the Lethal Dose in MR219 (Oryza sativa L. spp. Indica cv. MR219). IJASRT 2012;2:63-67. 35. Preuss SB, Britt AB. "A DNA-damage-induced cell cycle checkpoint in Arabidopsis." Genetics 2003;164:323-334. 36. Jifon JL. Growth environment and leaf anatomy affect nondestructive estimates of chlorophyll and nitrogen in Citrus Sp. leaves. J Am Soc Hortic Sci 2005;130:152-158. 37. Kim JH, Baek MH, Chung BY, Wi SG, Kim JS. Alterations in the photosynthetic pigments and antioxidant machineries of red pepper (Capsicum annuum L.) seedlings from gammairradiated seeds. J Plant Biol. 2004;47:314-321. 38. Wi SG, Chung BY, Kim JS, Kim JH, Baek MH, Lee JW, Kim YS. Effects of gamma irradiation on morphological changes and biological responses in plants. Micron 2007;38:553-564. 39. Wi SG, Chung BY, Kim JH, Baek MH, Yang DH, Lee JW, Kim JS. Ultrastructural changes of cell organelles in Arabidopsis stem after gamma irradiation. J Plant Biol 2005;48:195– 200.

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http://dx.doi.org/10.22319/rmcp.v10i1.4631 Technical Note

Yield of forage and its components in alfalfa varieties of the Mexican high plateau Adelaido Rafael Rojas Garcíaa Nicolás Torres Saladoa María de los Ángeles Maldonado Peraltaa Jerónimo Herrera Péreza Paulino Sánchez Santillána Aldenamar Cruz Hernándezb* Félix de Jesús Mayren Mendozaa Alfonso Hernández Garayc

a Universidad Autónoma de Guerrero. Facultad de Medicina Veterinaria y Zootecnia. Cuajinicuilapa, Guerrero, México. b Universidad Juárez Autónoma de Tabasco. División Académica de Ciencias Agropecuarias. Carretera Villahermosa-Teapa, km 25. R/A La Huasteca, Tabasco, México. Tel. 01 (993) 3581500, ext. 6604. c Colegio de Postgraduados. Recursos Genéticos y Productividad Ganadería. Campus Montecillo. Texcoco. México. *Corresponding author: ingaldecruz@gmail.com

Abstract: Alfalfa (Medicago sativa L.) is the cultivated legume that is mostly used in milk and meat production in Mexico, due to its high yield and nutritional value. The objective of this study was to evaluate the yield of forage and its components, in five alfalfa varieties, with seasonally defined cutting intervals. The Aragon, Valenciana, Chipilo, Milenia and Oaxaca varieties were randomly distributed in 20 experimental, 12 x 9 m plots, according to a randomized complete block design with four repeats. The evaluations included forage yield in a dry base, stem weight, stem population m-2, plant population m-2, leaf:stem ratio, botanical and morphological composition. The highest

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and lowest yields were obtained in the Milenia and Aragon varieties, with 20,643 and 14,488 kg DM ha-1. The weight per stem was better in Aragon, Chipilo and Milenia, and lower in Valenciana and Oaxaca. Aragon had the greatest stem density, with 634 stems m-2, and Oaxaca, with 512 stems m-2, had the lowest density. The highest leaf:stem ratio was found in Aragon, with 1.31, and the lowest was found in Oaxaca, with 1.13. In fall and winter, a larger amount of leaves was obtained, independently of the variety, and in summer, there was an increase in all weed varieties. Seasonality was related to yield, with a greater production in spring and summer, due to temperature, and to a greater stem weight. The variety with greatest dry matter yield was Milenia, and Aragon had the lowest yield. Key words: Forage yield, leaf:stem ratio, stem population.

Received: 18/09/2017 Accepted: 07/05/2018

Alfalfa (Medicago sativa L.) has great importance due to its high yield per surface unit and its forage nutritional value(1), and because it is appealing to diverse animals when consumed fresh, as hay or as ensilage(2). Alfalfa is also used to improve vegetal covers, avoid soil erosion, prevent the degradation of prairies and to support sustainability in agriculture and cattle raising activities (3). When this legume is associated with a grain, the prairieâ&#x20AC;&#x2122;s production increases, seasonality is minimized, the nutritional value improves and production costs are reduced, compared to balanced diets(4). Researchers(5,6) showed that the fequency and intensity of alfalfa cutting must be defined based on the state of the plantâ&#x20AC;&#x2122;s development and the season. These parameters are important to achieve balance between quantity, quality and the prairieâ&#x20AC;&#x2122;s persistence(7). It has been observed that alfalfa yield is greater in spring-summer and lower in fall and winter(8,9). Villegas et al(10) also reported that forage yield of the alfalfa varieties was higher in spring, followed by that of winter and summer, and the lowest yield was recorded in the fall. Idris and Adam(11) obtained a higher and lower annual yield in the Hagazi and Cuf 101variety, with harvest frequencies of 25 and 30 d, respectively. Stem population density and weight have been evaluated in several parts of the world, since they are forage production indicators (12). In an investigation carried out by Chen et al (3), an increase in the alfalfa cutting frequency was strongly linked to stem density, increasing until it reached a point of decline, independently of the variety and year of evaluation, with 645, 734 and 688 stems m -2, at a frequency of 30, 40 and 50 d. These same authors observed the lower and higher weight per stem, with 0.27 and 0.45 g for the lower and higher frequencies, respectively; this was related to 240

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yield. Other investigations(13) mention a strong correlation between a greater weight per stem and higher yield and temperature. Some authors(14) report the highest alfalfa yield with a density of 25 plants m-2. Morales et a (15) found a high leaf:stem ratio in 14 alfalfa varieties, with the highest total yield, growth rate and stem density. They also stated(5), that a greater percentage of leaves was obtained in winter, with an average 65 %, and this percentage was lowest in spring. Nevertheless, in Mexico, there is scarce information on these production parameters. The objective of this study was to evaluate the yield components of five commercial alfalfa varieties, at seasonally defined cutting intervals, with the following attributes: forage yield, weight per stem, stem density, plant density, leaf:stem ratio, botanical and morphological composition. The study was carried out in the experimental field of the Colegio de Postgraduados, in Montecillo, Texcoco, State of Mexico (19° 29’ N and 98° 53’ W, at an altitude of 2,240 m) from June, 2010 to June, 2011. The climate is temperate sub-humid, the dryest of the sub-humid climates, with a mean annual precipitation of 636.5 mm; rainy season in summer (June to October) and an annual average temperature of 15.2 °C(16). The soil is a Typic Udipsamments, with a sandy loam texture, a pH between 7 and 8 and 2.4 % organic matter(17). Five commercial alfalfa varieties were used: Aragon, Valenciana, Chipilo, Milenia and Oaxaca, sown by broadcast on April 18, 2008. The sown density was 30 kg ha-1 of pure live seed, adjusted by the germination percentage of each variety. The study area was divided into 20 plots covering 108 m2 (12 x 9 m). At the beginning of the experiment (June 2, 2010) standardization cutting was carried out with a tractor-mounted pruning machine, at an average height of 5cm; the experimental phase concluded on June 21, 2011. The cutting interval varied according to the season: in spring and summer the plants were cut every 4 wk in fall, every 5 wk and in winter, every 6 wk, according to recommendations of Mendoza et al(5). The prairies were not fertilized and in the seasons with minimal rainfall, these were irrigated at field capacity every two weeks. In order to evaluate forage yield for each variety, at the start of the study, two fixed squares of 0.25m-2 per repeat, were randomly placed. The forage present within each square was harvested one day before cutting, at a height of 5 cm; it was placed in labeled paper bags and dried in a forced air oven, until reaching constant weight. Once dry, the sample’s weight was recorded to estimate the dry matter yield per surface unit (kg DM ha-1). One day before cutting, 10 stems were randomly cut in each treatment and repeat at ground level, and dried in a forced air oven, until reaching constant weight. Later, average weight per stem was calculated. At the beginning of the experiment, two fixed 20 x 20 cm squares were randomly placed in each experimental unit; stems present in each square were counted monthly and later on the average number per season was calculated. When the experiment began, a 1 m2 fixed square was placed in an experimental box, at ground level, where the alfalfa plants were counted on a monthly basis, and changes in population density were recorded, averaging them seasonally. 241

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The leaf:stem ratio was calculated dividing the dry weight of each fraction (leaf/stem), expressed in kg ha-1, obtained from the subsample used to estimate the botanical and morphological composition. To obtain the botanical composition, one day before each cutting, a subsample was taken of approximately 20 % of the forage samples harvested to estimate the yield, and each subsample was separated into alfalfa and weeds. Each component was dried in a forced air oven, until reaching a constant weight, and its dry weight was recorded; subsequently, the seasonal yields were averaged. Data including maximum and minimum temperatures and rainfall accumulated during the study period, were obtained from the agro-meteorological station of the Colegio de Postgraduados, located 100m from the experimental area (Figure 1). The maximum temperature was observed in July, 2010 and between March and June, 2011, with an average of 28 Â° C, corresponding mainly to spring and summer. The minimal recorded temperature was in December, 2010 and in January and February, 2011, with an average -1 Â°C, corresponding to winter. The greatest precipitation (mm) was in July, August, Sept and Nov, 2010 and in June, 2011, with an accumulation of 404 mm; this mainly represented the summer and fall seasons. In winter and spring, the plants were irrigated to field capacity every 15 d. The effect of the studied factors on the response variables was evaluated through an analysis of variance (ANOVA) using the mixed models(18) procedure, with a randomized complete block design with four repeats. The comparison of means was done using the Tukey test (P= 0.05).

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Figure 1: Mean monthly maximum and minimum temperatures, accumulated monthly rainfall and field capacity irrigations, during the study period (June 2010 to June 2011)

No significant interactions were found (P>0.05) between the studied factors. In general, average annual contribution to yield was: summer 3 5%, spring 28 %, fall 24 % and winter 13 %. Average forage yield for the alfalfa varieties decreased in the fall (P<0.05) with respect to summer records; also, winter yield was lower (P<0.05) than what was obtained during the other three seasons (Table 1). These results coincide with the higher temperatures recorded in spring-summer (Figure 1), which favored alfalfa development(19), since the optimal temperature for alfalfa growth fluctuates between 15 and 25 Â°C. On the other hand, dry matter yield for the Milenia variety only was higher (P<0.05) than that of the Aragon variety (Table 1). Villegas et al(10) report similar yields in the Oaxaca and Valenciana varieties, in this evaluation (21,600 and 20,000 kg DM ha-1). However, independently of the alfalfa variety and cutting frequency, the average annual yield(11) was 10,552 kg DM ha-1.

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Table 1: Seasonal and annual yield (kg DM ha-1) of alfalfa varieties Variety

Summer

Aragon Valenciana Chipilo Milenia Oaxaca SEM Average

5188 Ba 6407 Aa 6162 ABa 7148 Aa 6298 ABa 345 6241 a

Fall 3334 Bb 4093 Ab 4386 Ab 4898 Ab 4512 Ab 432 4244 b

Winter 1717 Bc 2035 ABc 2412 ABc 2776 Ac 2217 ABc 355 2231 c

Spring 4248 Aab 4293 Ab 5072 Aab 5819 Aab 4911 Aab 456 4869 ab

SEM

Annual

456 398 402 434 521

14488 B 16828 AB 18034 AB 20643 A 17939 AB 897

abc= means with the same lowercase letter in the same row are not different (P>0.05). ABC= means with the same uppercase letter in the same column, are not different (P>0.05). SEM= Standard error of the mean.

Other researchers(1) got similar results in two varieties and eleven alfalfa lines, with an average 20,615 kg DM ha-1. Abusuwar and Daur(20) found, in Cuf 101 and Hegazi varieties, higher and lower yields of 18,065 and 17,545 kg DM ha-1. The greatest total accumulated alfalfa forage production was reported in the Valley of Mexico, with 33,864 and 34,457 kg DM ha-1, respectively; the greatest seasonal distribution was in spring and summer, and the lowest in fall and winter, with the same cutting intervals as in this investigation(5,8). Nevertheless, lower yields were observed in this study and could be attributed to the fact that the varieties had been established for more than 2 years (April 2008), so that forage persistence and yield decreased over time, after being sown(4). The analysis of variance did not reveal interactions (P>0.05) between the studied factors. Differences were found (P<0.05) in annual average weight per stem, between the alfalfa varieties: Aragon, Milenia and Chipilo produced heavier stems (0.71 g, average) than Valenciana and Oaxaca, with 0.67 y 0.68 g, respectively (Table 2). A seasonal effect was found in all varieties (P<0.05), the average weight per stem was greater in spring and lower in winter, with respect to the rest of the seasons. The highest values were observed in spring and were associated with the maximum temperatures recorded during the study (Figure 1). Nevetheless, the authors mention that these differences can also be due to cutting frequencies(3); upon evaluation of the alfalfa cutting frequency, these authors found the lowest and highest weight per stem to be 0.27 and 0.45 g, for the lowest and highest frequency, respectively.

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Table 2: Seasonal changes in weight per stem (g) for alfalfa varieties Variety

Summer

Fall

Winter

Spring

SEM

Average

Aragon

0.83 Aa

0.69 Aab

0.36 Bb

0.94 Aa

0.11

0.71 A

Valenciana

0.80 Aa

0.69 Ab

0.33 Bc

0.86 Ba

0.16

0.67 B

Chipilo

0.72 Ba

0.70 Aab

0.45 Ab

0.93 Aa

0.12

0.70 A

Milenia

0.75 Bb

0.71 Ab

0.34 Bc

1.04 Aa

0.21

0.71 A

Oaxaca

0.74 Ba

0.67 Aab

0.45 Ab

0.86 Ba

0.15

0.68 B

SEM

0.9

0.7

0.6

0.9

Average

0.75 b

0.69 b

0.39 c

0.93 a

0.8

Meuriot et al(21) evaluated the alfalfa cutting frequency and intensity and found that stem weight was larger (1.1 g per stem) as cutting frequency increased, with a 15 cm cutting intensity; this was related to a greater leaf area index (LAI) and yield. Avci et al(13) reported that the greater weight per stem was associated with a better yield, as was seen in the spring, during this investigation.The increase in weight per stem coincides with the decrease in stem density, mainly in spring. This behavior has been reported by other authors(22), who point out that the increase in stem density per unit of area causes a decrease in individual stem weight; this is explained by the self thinning law(23) and confirmed by other authors(24,25,26). The interactions between alfalfa varieties and the times of the year were not significant (P>0.05) with respect to this response variable. There were differences (P<0.05) between the varieties, since the Aragon had the greatest average annual stem density, with 634 stems m-2, while the Oaxaca variety had the lowest density, with 512 stems m-2 (Table 3). Seasonal differences (P<0.05) also existed, since the average stem density in summer was greater than the one recorded in winter; however, the lowest stem density was recorded in spring.

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Table 3: Seasonal changes in stem density (stems m-2) of alfalfa varieties Variety

Summer

Fall

Winter

Spring

SEM

Average

Aragรณn

715 Aa

660 Aab

585 Ab

577 Ab

234

634 A

Valenciana

708 ABa

684 Ab

483 Bd

503 Bc

145

595 B

Chipilo

739 Aa

692 Aa

525 ABb

318 Cc

124

568 B

Milenia

666 BCa

592 BCb

528 ABbc

496 Bc

571 B

Oaxaca

623 Ca

537 Cb

518 ABb

372 Cc

134

512 C

SEM

102

Average

690 a

633 ab

528 b

453 c

abc

= Means with the same lowercase letter in the same row are not different (P>0.05). ABC= means with the same uppercase letter in the same column, are not different (P>0.05). SEM= Standard error of the mean.

In another investigation(27) of four alfalfa varieties, the authors observed the same behavior as in this study, since stem density decreased as the study progressed. They recorded greater stem density in the first year of evaluation and the lowest in the fourth year, with an average 518 and 140 m-2, respectively. Nevertheless, Chen et al(28) stated that as the cutting frequency decreased, the stem density increased until it reached a point of decline, independently of the variety and year of evaluation: 645, 734 and 688 stems m-2 for cutting frequencies every 30, 40 and 50 d, respectively, which is highly related to yield. Soil temperature and humidity are the main climatic factors having an influence on stem density and weight; when these are favorable, there is constant stem production, resulting in a greater biomass production in the prairie(29). However, an inverse relationship has been mentioned(22) between stem density and dry matter production. Researchers point out that a greater number of stems results in a lower forage yield, possibly due to the low individual weight. The analysis of variance did not show significant interactions (P>0.05) between the factors under study. Just as with stem density, average plant density decreased (P<0.05) in all alfalfa varieties, as the study progressed (Table 4), from 33 plants m-2 in summer, to 22 plants m-2 in spring.The greatest average annual plant density was recorded for Milenia, with 33, and the lowest for Aragon, with 21 plants m-2. Both lost 9 and 11 plants between the beginning and end of the study, respectively. Other authors(30) mention that, in an alfalfa prairie, plant cover and density are stabilized, as time since its establishment increases; however, a time comes when these decrease, depending on the variety and the site.

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Table 4: Seasonal changes in plant density (plants m-2) for alfalfa varieties Variety

Summer

Fall

Winter

Spring

SEM

Average

Aragon

26 Ca

22 Db

20 Cb

17 Cc

21 C

Valenciana

34 Ba

32 ABb

26 Bc

22 Bd

29 B

Chipilo

33 Ba

29 BCab

26 Bbc

23 Bc

28 B

Milenia

38 Aa

36 Ab

31 Ac

27 Ad

33 A

Oaxaca

31 Ba

27 Cb

25 Bbc

22 Bc

26 B

SEM

Average

33 a

29 b

26 c

22 d

abc

Another study(31) mentions the importance of distance between the alfalfa plants. They found the highest yield in spring, related to the greatest intercepted radiation (95%) in all distances between plants (10, 15, 20, 25 and 30 cm); while in summer and winter, 95% intercepted radiation was only reached at a distance of 10 and 15 cm between plants, since alfalfa growth is related to temperature. Several authors(27,32) state that the smaller the separation between plants, the higher is the yield, which coincides with this studyâ&#x20AC;&#x2122;s findings. No interaction was recorded between the alfalfa varieties and the seasons, for this response variable. However, the leaf:stem ratios varied (P<0.05) in the different seasons (Table 5): in fall and winter there was higher average leaf:stem ratio (1.52) which was significantly different from the summer and spring relationship (0.92). On the other hand, the Aragon and Valenciana varieties showed the highest leaf:stem ratio (1.30), compared to the Chipilo and Oaxaca varieties (1.14). In a study by Rojas et al(33), they observed that independently of the variety, in fall and winter the leaf:stem ratio was greater, with a value of 1.49, compared to the value recorded in summer and spring, with 0.92 and 0.94 respectively, Villegas et al(34) observed that, with two cutting intensities, the Moapa and Tlacolula varieties had the best and worst leaf:stem ratio with 1.4 and 1.1 respectively. Other authors(8) reported values much lower than the above, and than the ones of the present study, since the annual average observed in five alfalfa varieties was 0.79, with variations throughout the year, and highest and lowest values (P<0.05) were observed in January and November, with 1.05 and 0.62, respectively. Also, Morales et al(15) recorded an average annual leaf:stem ratio of 0.68, in fourteen alfalfa varieties.

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Table 5: Seasonal changes in leaf:stem ratio in five alfalfa varieties Variety

Summer

Fall

Winter

Spring

SEM

Average

Aragon

0.94 Ab

1.65 Aa

1.66 Aa

0.99 Ab

0.23

1.31 A

Valenciana

0.92 Ab

1.59 Aa

1.69 Aa

0.96 Ab

0.32

1.29 A

Chipilo

0.84 Bb

1.40 ABa

1.44 Ba

0.94 Ab

0.21

1.15 B

Milenia

0.95 Ab

1.49 ABa

1.50 ABa

0.97 Ab

0.19

1.23 AB

Oaxaca

0.87 Bb

1.38 Ba

1.44 Ba

0.83 Bb

0.18

1.13 B

SEM

0.7

0.15

Average

0.90 b

1.50 a

1.55 a

0.94 b

0.13

abc

Hernรกndez-Garay et al(23) mention that the leaf:stem ratio of forage may be considered an indirect measurement of quality, since values greater than one show a better forage quality, having a greater amount of leaves. In this study, indexes greater than 1 were recorded in fall and winter. However, even though in these seasons alfalfa plants produced a higher leaf:stem ratio, dry matter yield tended to be lower in fall, and was the lowest in winter, compared to spring and summer (Table 1). Rojas et al(4) mention that in forage, one must obtain the best relationship between yield and quality, which happens when there is a greater amount of leaves. Independently of the variety, alfalfa constituted more than 90% of the desirable species in the prairie, during the whole study period (Figure 2). Differences were observed between seasons in the percentage of leaves, with a greater leaf contribution, 59 %, in fall and winter, and a lower one, 45 %, in spring and summer. With respect to stem percentage, the greatest contribution was found in spring and summer, and the lowest in fall and winter. No dead matter was found during the whole experimental period, since alfalfa tends to shed its senescent leaves. Inflorescences were also not found, due to the fact that the cuttings were done before the inflorescences appeared. Several researchers(5,6,8) reported similar behavior with respect to the amount of alfalfa leaves, which were most abundant during periods with the lowest temperatures.

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Figure 2: Seasonal changes in botanical and morphological composition (%) of five alfalfa varieties, ÉŞ= standard error of the mean

Only in summer was there a greater presence of weeds, compared to other seasons, being the main ones: Aristida stricta, Bromus inermis and Malva neglecta. The higher percentage of weeds in summer could be due to higher temperatures and rainfall recorded in this season (Figure 1), which are appropriate for weeds, with intraspecific competition existing with alfalfa, for light, water and nutrients(30). The varieties that showed the greatest weed invasion were Valenciana and Oaxaca, with 9 %. The greater presence of weeds in these varieties could be attributed to lower plant density (Table 4), which led to a greater invasion by undesired weeds, as reported in other works(5,14). It was conclude that alfalfa varieties displayed different behaviors and that the highest yield was found in Milenia, Chipilo, Oaxaca and Valenciana. According to the statistical differences between the general averages of each season, the dry matter yield in summer was mostly contributed by stem density and plants; also, a greater stem weight led to higher dry matter yield in spring. However, it is necessary to continue carrying out investigations and include other production 249

Rev Mex Cienc Pecu 2019;10(1):239-253

parameters, such as plant height, intercepted radiation and leaf area index, which could better explain alfalfa’s productive behavior in each season; this could contribute to improvement in crop management.

Literature cited: 1. Avci M, Cinar S, Yucel C, Inal I. Evaluation of some selected alfalfa (Medicago sativa L.) lines for herbage yield and forage quality. J Food, Agr & Environ 2010;8:545-549. 2. Han QF, Jia ZK, Wang JP. Current status and future prospects of alfalfa industry in and outside China. Pratacultural Sci 2005;3:22-25. 3. Chen JS, Tang FL, Zhu RF, Gao C, Di GL, Zhang YX. Effects of cutting frequency on alfalfa yield and yield components in Songnen Plain, Northeast China. African J Biotechnol 2012;11:4782-4790. 4. Rojas GAR, Hernández-Garay A, Quero CAR, Guerrero RJD, Ayala W, Zaragoza RJL, Trejo LC. Persistencia de Dactylis glomerata L. solo y asociado con Lolium perenne L. y Trifolium repens L. Rev Mex Cienc Agr 2016;7(4):885-895. 5. Mendoza PSI, Hernández-Garay A, Pérez PJ, Quero CAR, Escalante EJAS, Zaragoza RJL, Ramírez RO. Respuesta productiva de la alfalfa a diferentes frecuencias de corte. Rev Mex Cienc Pecu 2010;1:287-296. 6. Hernández-Garay A, Martínez HPA, Zaragoza EJ, Vaquera HH, Osnaya GF, Joaquín TBM, Velasco ZME. Caracterización del rendimiento de forraje de una pradera de alfalfa-ovillo al variar la frecuencia e intensidad de pastoreo. Rev Fitotecnia Mex 2012;35:259-266. 7. Teixeira EI, Moot DJ, Brown HE. Defoliation frequency and season affected radiation use efficiency and dry matter partitioning to roots of lucerne (Medicago sativa L.) crops. European J Agron 2008;28:103-111. 8. Rivas JMA, López CC, Hernández-Garay A, Pérez PJ. Efecto de tres regímenes de cosecha en el comportamiento productivo de cinco variedades comerciales de alfalfa (Medicago sativa L.). Téc Pecu Méx 2005;43:79-92. 9. Rojas GAR, Hernández-Garay A, Joaquín CS, Maldonado PMA, Mendoza PSI, Álvarez VP, Joaquín TBM. Comportamiento productivo de cinco variedades de alfalfa. Rev Mex Cienc Agr 2016;7(8):1855-1866. 250

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10. Villegas AY, Hernández-Garay A, Pérez PJ, López CC, Herrera HJ, Enríquez QJ, Gómez VA. Patrones estacionales de crecimiento de dos variedades de alfalfa (Medicago sativa L.). Téc Pecu Méx 2004;42:145-158. 11. Idris AE, Adam MMA. Effect of cutting intervals on yield and yield components of three alfalfa (Medicago sativa L.) genotypes. Adv Environ Biol 2013;7:4677-4681. 12. Matthew C, Hernández-Garay A, Hodgson J. Making sense of the link between tiller density and pasture production. Proc N Z Grassland Ass 1996;57:83-87. 13. Avci MA, Ozkose A, Tamkoc A. Determination of yield and quality characteristics of alfalfa (Medicago sativa L.) varieties grown in different locations. J Anim Vet Adv 2013;12:487-490. 14. Celebi SZ, Kaya I, Saharand AK, Yergin R. Effects of the weed density on grass yield of Alfalfa (Medicago sativa L.) in different row spacing applications. African J Biotechnol 2010;9:68676872. 15. Morales AJ, Jiménez VJL, Velasco VVA, Villegas AY, Enríquez VJR, Hernández-Garay A. Evaluación de 14 variedades de alfalfa con fertirriego en la mixteca de Oaxaca. Téc Pecu Méx 2006;44:277-288. 16. García E. Modificaciones al sistema de clasificación climática de Koppen. 4 ed. Universidad Nacional Autónoma de México. México, DF. 2004. 17. Ortiz SC. Colección de Monolitos. Depto. Génesis de Suelos. Edafología. IRENAT. Colegio de Postgraduados. Montecillo, Texcoco, Estado de México 1997. 18. SAS INSTITUTE. SAS/STAT® 9.2. Use´s Guide Release. Cary, NC 2009. 19. Guimire R, Norton JB, Pendall E. Alfalfa-grass biomass, soil organic carbon, and total nitrogen under different management approaches in an irrigated agroecosystem. Plant Soil 2014;374:173-184. 20. Abusuwar AO, Daur I. Effect of poultry and cow manures on yield, quality and seed production of two alfalfa (Medicago sativa L.) cultivars under natural saline environment of western Saudi Arabia. J Food Agr Environ 2014;12:747-751. 21. Meuriot F, Decau ML, Morvan-Bertrand A, Prud´Homme MP, Gastal F, Simon JC, Volenec JJ, Avice JC. Contribution of initial C and N reserves in Medicago sativa recovering from defoliation: impact of cutting height and residual leaf area. Funct Plant Biol 2005;32:321-334.

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22. Hernández-Garay A, Pérez PJ, Hernández GVA. Crecimiento y rendimiento de alfalfa en respuesta a diferentes regímenes de cosecha. Agrociencia 1992;2:131-144. 23. Hernández-Garay A, Matthew C, Hodgson J. The influence of defoliation height on dry-matter partitioning and CO2 exchange of perennial ryegrass miniature swards. Grass Forage Sci 2000;55:372-376. 24. Velasco ZME, Hernández-Garay A, González HVA. Cambios en componentes del rendimiento de una pradera de ballico perenne, en respuesta a la frecuencia de corte. Rev Fitotecnia Mex 2007;30(1):79-87. 25. Castro RR, Hernández-Garay A, Ramírez RO, Aguilar BG, Enríquez QJF, Mendoza PSI. Crecimiento en longitud foliar y dinámica de población de tallos de cinco asociaciones de gramíneas y leguminosa bajo pastoreo. Rev Mex Cienc Pecu 2013;4(2):201-215. 26. Rojas GAR, Ventura RJ, Hernández-Garay A, Joaquín CS, Maldonado PMA, Reyes VI. Dinámica poblacional de tallos de ovillo (Dactylis glomerata L.) solo y asociado con ballico perenne (Lolium perenne L.) y trébol blanco (Trifolium repens L.). Rev Mex Cienc Pecu 2017;8(4):419-428. 27. Stanisavljević R, Beković D, Djukić D, Stevović V, Terzić D, Milenković J, Djokić D. Influence of plant density on yield components, yield and quality of seed and forage yields of alfalfa varieties. Romanian Agr Res 2012;29:245-254. 28. Chen JS, Gao C, Di GL, Zhu RF, Zhang YX. Effects of cutting on alfalfa yield and quality in Northeast China. J Anim Vet Adv 2013;12:253-260. 29. Ventroni LM, Volenec JJ, Cangiano CA. Fall dormancy and cutting frecuency impact on alfalfa yield and yield components. Field Crops Res 2010;119:252-259. 30. Mortenson MC, Schuman GE, Ingram LJ, Nayigihugu V, Hess BW. Forage production and quality of a mixed-grass rangeland Inter seeded with Medicago sativa ssp. falcata. Rangeland Ecol Manage 2005;58:505-513. 31. Mattera J, Romero LA, Cuatrin AL, Cornaglia PS, Grimoldi AA. Yield components, light interception and radiation use efficiency of lucerne (Medicago sativa L.) in response to row spacing. European J Agron 2013;45:87-95. 32. Baldissera TC, Frak E, Carvalho PCF, Louarn G. Plant development controls leaf area expansion in alfalfa plants competing for light. Ann Botany 2014;113:145-157.

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33. Rojas GAR, Torres SN, Joaquín CS, Hernández-Garay A, Maldonado PMA, Sánchez SP. Componentes del rendimiento en variedades de alfalfa (Medicago sativa L.). Agrociencia 2017;51:697-708. 34. Villegas AY, Hernández-Garay A, Martínez HPA, Pérez PJ, Herrera HJG, López CC. Rendimiento de forraje de variedades de alfalfa en dos calendarios de corte. Rev Fitotec Mex 2006;29:369-372.

253

http://dx.doi.org/10.22319/rmcp.v10i1.4727 Technical note

Evaluation of clinical, radiological, ultrasonographic and microbiological findings of septic arthritis in 50 calves

Ä°brahim Yurdakul* Department of Surgery, Faculty of Veterinary Medicine, Cumhuriyet University, Sivas, TURKEY.

Correspondence author: ibrahimyurdakul5858@hotmail.com

Abstract: In this study, it was aimed to evaluate clinical, radiological, ultrasonographic and microbiological findings of calves with septic arthritis. Study material consisted of 50 calves with arthritis in different stocks and gender and aged between 4 to 150 d, brought to the clinic between 2016 and 2017 with lameness complaint. After obtaining medical histories, physical and microbiological examinations of calvesâ&#x20AC;&#x2122; clinical, radiographic, ultrasonographic, synovial samples were conducted. Clinically, monoarthritis was detected in 37 calves and polyarthritis was detected in 13 calves. Most of the lesions were observed in carpal and tarsal joints. In radiography results, increased opacity was found in joints with arthritis, intraarticular narrowing and degeneration on joint surface. In ultrasonographic examinations, the hyperechogenic heterogeneous appearance of synovial fluid and a smooth and apparent hyperechoic joint capsule in articular cartilage surface were observed in 43 cases. Most commonly, Staphylococcus aureus was detected in 13 cases, Trueperella pyogenes was detected in 8 cases, Streptococcus pluranimalium was detected in 8 cases, Mycoplasma bovis was detected in 5 cases, Escherichia coli was detected in 5 cases, Saprophyte spp. was detected in 1 case and Acinetobacter spp. was detected in 1 case in microbiological examination of synovial fluid. In conclusion, the together evaluation of clinical, radiological, ultrasonographic and microbiological findings in the diagnosis of septic arthritis, which is frequently encountered in calves and which causes serious economic losses with high mortality rates, would be a more effective approach for clinical practitioners in terms of treatment and prognosis. Key words: Arthritis, Calf, Clinic, Microbiology, Radiology, Ultrasonography.

254

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Received: 19/12/2017 Accepted: 18/06/2018 It is indicated that foot diseases encountered in cattle breeding cause serious economic losses such as decrease in milk yield, weight loss, decrease in reproductive performance, treatment expenses and early separation of cattle from the herd because of the disease(1-5). The most common cause of lameness in cattle is nail problems. It is reported that the diseases causing lameness in second rank are arthritides(4,6). Diseases occurring in the joints and ligaments constitute 47 % to 72.2 % of lameness cases caused by extremity(6). Arthritis are inflammations of components of a joint that shows fever, pain, swelling and lameness symptoms at different levels(7,8). During arthritis, synovial fluid, that is generally clear or slightly pale yellow and viscous, has an egg white appearance, and includes proteins, becomes abnormal, and this fluid contains a large number of leukocytes and microbial pathogens(7,9). Arthritis can affect one, several or all of the components of the joint. Arthritis can occur in only one joint (monoartritis), in multiple joints (polyarthritis), in joint ligaments and their peripheral area (periarthritis), and also in all joint components (panarthritis)(2,10,11). It is classified as acute or chronic according to the clinical course, and aseptic or septic according to the characteristic of the inflammation(2,9,12). In aseptic and septic arthritis, various levels of deformation occur in the components forming the joint, causing functional disorders. Lameness, difficulty in standing, tension in the joint capsule due to synovial fluid increase, swelling, pain and local temperature increase are the most common clinical manifestations(12-14). Aseptic joint inflammations are usually seen as a result of distortions and overextensions of the joint area of relevant leg during pulling applied in delivery to the calves. On the other hand, septic joint inflammations are caused by the direct occurrence of infection factors on joint regions as a result of trauma or by the replacement via hematogenesis as a result of diseases such as septicemia, omphalitis and pneumonia(8,11,14-17). Especially in young animals, joint infections can occur after bacteremia or sepsis. In addition, calves with hypogammaglobulinemia has been found to be more sensitive to bacteremia and septic arthritis(7). Septic arthritis is a very common disease that frequently affects newborn calves(18). The disease generally requires long-term treatment and high medical expenses. For this reason, application of treatment is sometimes not economical due to the high expense(7,18). In addition, the use of inappropriate antibiotics, delayed initiation of treatment, formation of irreversible lesions in tissues and joint structures are reported to be the causes of failure in treatment(7,8,11). Therefore, early diagnosis and treatment of the disease is very important for the reduction of prevalence and economic expenses of the disease(1,14). Several pathogens have been reported as causes of arthritis in calves in different regions of the world. Several Mycoplasma spp. species such as M. bovis, M. canadense, M. alkalenscens and M. 255

Rev Mex Cienc Pecu 2019;10(1):254-266

bovigenitalium have a constructive role in the formation of arthritis in cattle. It is reported that M. bovis is the most common isolated species in arthritis cases encountered in cattle(7,13,15,19). However, other pathogens such as Trueperella pyogenes, Actinomyces pyogenes, E. coli, S. aureus, Streptococcus spp. and Salmonella spp. also take an important place in the formation of the disease(13,18,19). In this study, it was aimed to evaluate the clinical, radiological, ultrasonographic and microbiological findings of the arthritis cases that cause great economic loss and serious health problems in calves. The material of the study consisted of 50 calves of different breed and gender (33 male and 17 female), aged between 4 to 150 d, brought to Cumhuriyet University Faculty of Veterinary Medicine Surgery Clinic, Sivas Turkey, between 2016 and 2017 with lameness and swelling complaint in joints. The place where the work was conducted; with a continental climate (hot and dry in summers, cold and snowy in winters), with an altitude of 1,285 m asl. Medical histories of calves with arthritis were obtained from their owners. Radiological and ultrasonographic examinations of the relevant joint or joints were performed after clinical examinations of the cases. Finally, synovial fluid was taken from joint or joints via aseptic method for microbiological examinations of calves with arthritis. For general clinical examination, examinations of body temperature, respiration rate, heart rate, mucosal membrane color, capillary filling time and local lymph nodules of calves with arthritis were performed primarily. The umbilical region was examined in terms of possible omphalitis. Following the determination of lameness by the inspection of calves with arthritis during standing and walking the gait and lumbar spine were determined, the relevant joint area was examined for the local temperature increase, swelling and flexion sensitivity. Radiographs of relevant joint were obtained in mediolateral (ML) and anteroposterior (AP) positions for radiographic examination. For ultrasonographic examination, the calves were put on the operation table, adjusting the position as the relevant joint was on top. Following the shaving of relevant joint hair, the joint was examined longitudinally and transversally. For sedation, xylazine hydrochloride at a dose of 0.05 mg/kg were given to the calves. Subsequently, antisepsis was ensured on the joint region that arthrocentesis will be applied with baticcon solution. Specific entry direction on the joint was determined, cannula size 18 was inserted into the joint, and approximately 4 ml synovial fluid was aspirated. Approximately 2 ml of aspirated synovial fluid was taken into a sterile tube for physical examination (color, volume, viscosity and fibrin) and the remaining 2 ml were taken into a different sterile tube for microbiological examination. The synovial fluid of the animals with arthritis was sent to a private microbiology laboratory for analysis of the agent, as there was no possibility of microbiological analysis in the animal hospital. Following the asepsis of the relevant joint of the animal, internal joint area was washed with 500 mL 0.9% physiological saline solution using "true and true" technique for treatment since different 256

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antibiotics have been given to calves with arthritis by veterinarians or animal owners givers, according to the statements of animal owners. This process was repeated until the aspirated fluid became clear. After irrigation, wet antiseptic compress was applied on the relevant joint with 0.1% batticon solution, application of wet compress once in every 24 h for 15 d was suggested to animal owner. Parenteral antibiotic Ceftiofur sodium (Ecoseft-IE) was given as 1 ml i.m. per 50 kg live weight for 5 d until the identification of bacterium in synovial fluid. Appropriate antibiotic was selected according to the microorganism isolated in microbiological examination of synovial fluid obtained from the joint and antibiotic was given parenterally for 10 d. In addition, flunixin meglumin (Flumeglin-Teknovet) was given for 3 d for postoperative pain control as 2.2 ml i.m. per 50 kg live weight. Continuous communication with animal owners was ensured during the treatment period in terms of recovery. Twenty four (24) of the 50 of calves with arthritis were Montofon calves, 23 were Simmental calves, 2 were indigenous calves and 1 was Holstein calf. Of the Montofon calves, 6 were male and 8 were female, 15 of the Simmental calves were male and 8 were female, all indigenous calves were male and Holstein calf was female. In total, there were 33 male and 17 female calves with arthritis. Clinically, general findings such as high fever, fatigue, loss of appetite, reduction in mobilization, lameness, pain in the flexion of the relevant joint, local temperature increase, swelling and sensitivity at varying levels were identified in all calves. Beside this, omphalitis was detected in 22 cases. In addition, pneumonia was detected in 2 cases, bloody diarrhea in 1 case and both pneumonia and diarrhea in 2 cases. Thirty-seven (37) calves were diagnosed with monoarthritis, and 13 calves with polyarthritis. Fourty two (42) of the lesions were found in carpal joints, 12 were in tarsal, 3 were in genu, 3 were in metacarpo-phalangeal, 2 were in coxae and 1 was in the cubital joint. The localization and clinical symptoms of the lesion with arthritis are given in Table 1.

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Table 1: Localization and clinical symptoms of lesions in calves with arthritis No Protocol 1

10 63 11 64 12 69

Age

Sex

1 F month 10 M days 25 F days 2 M month 8 days 4 month 1.5 month 1.5 month 1.5 month 1 month 5 month 2 month

Montofon

Left art. carpi

+++

Montofon

Right art. carpi

+++

Montofon

Right and left art. carpi and art. tarsi Left art. carpi

Montofon

Right art. carpi

+++

Montofon

Right art. carpi

Simmental Left art. tarsi

+++

Montofon

+++

Simmental Right art. carpi

+++

Montofon

+++

16 87

1.5 M month

23 108

15 85

22 105

+++

10 days

21 104

20 101

Simmental Left art. carpi

10 days

19 91

Simmental Left art. carpi

14 84

18 90

Decrease Pain in Heat in Lameness the Swelling Sensitivity increase mobility flexion

Montofon

4 days M

17 89

Localization of the lesion

13 78

1 month 15 days 2 month 1.5 month 1 month 15 days 1 month

Breed

Right art. coxae

Left art. carpi

Right and left Montofon art. carpi Right and left Simmental art. carpi and art. tarsi Right and left Simmental art. carpi Right and left art. carpi and art. Simmental tarsi, right art. cubiti

+ ++ +++ ++ + + ++ +

++ +++

+++

Holstein

Left art. carpi

+++

Montofon

Left art. carpi

Simmental Right art. carpi

+++

Simmental Left art. carpi

+++

Montofon

Right and left art. carpi

Native race

Left art. carpi

+++

Montofon

Left art. carpi

258

+ +

+ +++ + +++ ++ ++ +

Rev Mex Cienc Pecu 2019;10(1):254-266

24 109 25 110 26 113 27 117 28 119 29 128 30 129 31 130 32 132 33 135 34 136 35 138 36 140 37 141 38 144 39 145 40 146 41 149 42 153

1.5 month 1 month 1 month 12 days 2 month 1.5 month 15 days 20 days 2 month 2 month 1.5 month 1 month 2 month 2 month 3 month 25 days 1.5 month 2 month 20 days

Montofon

Left art. carpi

Montofon

Right art. carpi

+++

Simmental Right art. genu

Montofon

Left art. carpi

Simmental Left art. carpi

+++

Montofon

Left art. tarsi

+++

Simmental Left art. tarsi

+++

Simmental Right art. carpi

+++

Simmental Right art. genu

+++

Native race

Right art. carpi

+++

Montofon

Left art. carpi

+++

Simmental Right art. carpi

+++

Montofon

Simmental Right art. carpi

+++

Montofon

Left art. carpi

+++

Montofon

Left art. carpi

Simmental

Right art. carpi and left art. tarsi

Montofon

Left art. carpi

+++

Montofon

Left art. carpi

+++

Right and left art. tarsi

Right art. metacarpoMontofon phalangealis, right art. carpi, right art. tarsi Right and left Simmental art. carpi and art. tarsi Right art. Simmental metacarpophalangealis

43 155

1 M month

44 159

15 days

45 166

15 days

46 169

1.5 F month

Montofon

47 181

2 M month

Right art. carpi, Simmental left art. genu, left art. coxae

Right art. carpi

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48 182

1 M month

49 190

2 F month

50 191

2 F month

Right and left art. carpi, art. Simmental tarsi and art. metacarpophalangealis Right and left Simmental art. carpi, right art. tarsi Simmental Right art. carpi

+++

In radiological examination, opacity increase and joint tension due to increased purulence or increased purulence with gas were detected in 18 cases (Figure 1, A,B), intraarticular narrowing and degeneration on joint surface were detected in 6 cases. No abnormality was detected in bone tissue in 26 cases.

Figure 1: a) Radiopacity increase in punctate radiolucent appearance around the tibiotarsal joint due to arthritis purulenta in a case with tarsitis; b) Formed radiolucent appearance due to possible microorganism activity in femoropatellar and femorotibial joints in a case with gonitis a

In ultrasonographic examination, enlarged joint space and corpuscular reflective bodies (fibrin deposits or tissue residues) showing intense hyperechogenicity in the anechoic appearance of the synovial fluid were detected in 18 cases; synovial fluid had a hyperechogenic appearance and was heterogeneous (Figure 2a). In 6 cases, the articular cartilage surface had a smooth surface with an acutely apparent hyperechoic line (Figure 2b). No abnormality was detected in 26 cases.

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Figure 2: a) Hyperechogenic and heterogenic appearance of the synovial space in a case with arthritis, (10 d male calf); b) Complex echogenicity and heterogenic appearance of the synovial space and corpuscular spots in the synovial fluid of a case with purulent arthritis, (36 d male calf) a

Seven synovial fluids taken from the calves with arthritis were mobile, clear and normal in appearance, 25 synovial fluids were cloudy and in varying colors from light yellow to dark yellowbrown and the synovial fluid viscosity decreased at varying levels, and the synovial fluid was completely purulent in 18 cases. Bacteriologically positive result was obtained from 38 of the synovial fluids, while a negative result was obtained from 12 of them. According to the results of microbiological analyzes, S. aureus was detected in 13 cases, Trueperella pyogenes in 8 cases, S. pluranimalium in 8 cases, Mycoplasma bovis in 6 cases, E. coli in 5 cases Saprophyte spp. in 1 case and Acinetobacter spp. in 1 case (Table 2). Arthritis is a common disease frequently seen in newborn calves, causing great economic losses, and showing fever, pain, swelling and lameness symptoms at different levels(7,8,18). Clinically, arthritides are classified as aseptic or septic and septic arthritides are important(9,12). In the presented study, the detection of omphalitis in 22 cases, pneumonia in 2 cases, bloody diarrhea in 1 case and pneumonia and diarrhea in 2 cases suggests that the colostrum given to calves after delivery was not sufficient and thus the infection has spread rapidly, causing septic arthritis and other clinical forms(9,17,20).

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Table 2: Microbiological findings of synovial fluid in calves with arthritis No Protocol

Age

Sex

Breed

Localization of the lesion

Ä°solated microorganism Streptococcus pluranimalium E.coli Mycoplasma bovis Staphylococcus aureus

1 month F

Simmental Left art. Carpi

2 3 6

47 53 57

M F F

Montofon Left art. Carpi Montofon Right art. Carpi Simmental Left art. Carpi

Montofon

Right art. Carpi

Mycoplasma bovis

Montofon

Right art. Carpi

Mycoplasma bovis, Staphylococcus aureus

10 days 25 days 4 month 1.5 month 1.5 month 1.5 month

Simmental Left art. Tarsi

14 84 16 87 17 89 18 90 19 91 20 101

10 days M 1.5 month 1 month 15 days 2 month 1.5 month

Simmental Right and left art. Carpi and art. Tarsi

F M F

Right and left art. Carpi and art. Tarsi, right art. Cubiti Holstein Left art. Carpi Montofon Left art. Carpi Simmental Right art. Carpi

Simmental Left art. Carpi

Simmental

Trueperella pyogenes Trueperella pyogenes Trueperella pyogenes Trueperella pyogenes Trueperella pyogenes Acinetobacter towner, Staphylococcus aureus.

1 month M

22 105

15 days M

23 108 25 110

1 month M 1 month F

Native race Montofon Montofon

28 119

2 month F

Simmental Left art. Carpi

29 128

1.5 month

Montofon

30 129

15 days M

Simmental Left art. Tarsi

31 130

20 days M

Simmental Right art. Carpi

32 132

2 month M

Simmental Right art. Genu

33 135

2 month F

Native race

Right art. Carpi

Trueperella pyogenes

Montofon

Left art. Carpi

Staphylococcus aureus

35 138

1.5 F month 1 month M

36 140

2 month M

34 136

38 144

2 a M month 3 month M

39 145

25 days M

37 141

40 146 42 153

1.5 M month 20 days M

Right and left art. Carpi

Streptococcus pluranimalium

21 104

Montofon

E.coli

Left art. Carpi

Trueperella pyogenes

Left art. Carpi Right art. Carpi

Staphylococcus aureus Staphylococcus aureus Streptococcus pluranimalium

Left art. Tarsi

Simmental Right art. Carpi Montofon

Right and left art. Tarsi

Simmental Right art. Carpi Montofon

Left art. Carpi

Montofon

Left art. Carpi

Staphylococcus aureus Trueperella pyogenes, Staphylococcus aureus, E coli Mycoplasma bovis Streptococcus pluranimalium

Staphylococcus aureus Streptococcus pluranimalium Streptococcus pluranimalium Staphylococcus aureus Sstreptococcus pluranimalium

Simmental Right art. Carpi and left art. Tarsi

E.coli

Montofon

E.coli

Left art. Carpi 262

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44 159 45 166

47 181

15 days 15 days 1.5 month 2 month

48 182

1 month M

Simmental

49 190 50 191

2 month F 2 month F

Simmental Right and left art. Carpi, right art. Tarsi Simmental Right art. Carpi

46 169

M M

Simmental Right and left art. carpi, right and left art. tarsi Simmental Right art. metacarpophalangealis

Staphylococcus aureus Staphylococcus aureus

Montofon

Trueperella pyogenes

Simmental Right art. Carpi, left art. Genu, left art. Coxae

Right art. Carpi

Right and left art. Carpi, art. Tarsi and art. Metacarpo- phalangealis

Mycoplasma bovis Mycoplasma bovis, Streptococcus pluranimalium Staphylococcus aureus Saprophyte spp.

Early definitive diagnosis of arthritis is possible with clinical, radiological and ultrasonographic examinations as well as with physical and microbiological examinations of synovial fluid(10,21,22). In this study, early diagnosis of joint diseases was ensured with anamnesis and clinical, radiological, and ultrasonographic examinations and was supported by physical and microbiological examinations of the synovial fluid. Clinical findings such as lameness at varying levels, palpation-sensitive, painful, edematous swelling with high fever and restriction of flexion movement have been reported to be observed in calves with arthritis(6,8,11). There was severe lameness observed in 30 cases, moderate lameness in 11 cases and mild lameness in 9 cases. In addition, monoarthritis were detected in 37 calves and polyarthritis in 13 calves in the study. Arthritis cases are reported to be frequently seen in carpal and genu joints in young animals and in tarsal and pastern joints in adult animals(6,17). In this study, the fact that arthritis was detected in carpal joint in 42 of the 50 calves with arthritis and in tarsal joint in 12 calves confirms this information. The first radiographic findings in arthritis are soft tissue swelling and enlargement of the joint space 24 h after the formation of the disease due to gas accumulation(11,16,21). Following the progress of the disease, the main radiographic findings are reported to appear about 10 to 14 d later. In chronic cases, there is a decrease observed in joint space due to subchondral bone lysis, periostitis, osteomyelitis and osteophytic formations(2,6,9). In radiological examination, opacity increase and capsular tension due to increased purulence or increased purulence with gas were detected in 18 cases, and intraarticular narrowing and degeneration on the joint surface were detected in 6 cases, while in 26 cases, there was no abnormality in bone tissue and joint detected. In arthritis cases, early diagnosis is very difficult before clinical symptoms occur; however, it is possible to diagnose arthritis without clinical symptoms by diagnostic ultrasonography(9). It is reported that a number of changes in synovial fluid volume, echogenic appearance of synovial fluid, synovial membrane, joint surface, and relation of joint with peripheral tissue will be formed with ultrasonographic examination(6,22). In this study ultrasonographic examination of the cases with septic arthritis revealed that the synovial fluid had a hyperechogenic appearance and heterogeneous structure, and that there were corpuscular reflective bodies showing intense 263

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hyperechogenicity in the synovial fluid in 18 cases, while the articular cartilage surface clearly formed a hyperechoic line and had a smooth surface in 6 cases. In 26 cases with arthritis, no abnormality was detected. The synovial fluid is a plasma in normally clear or slightly pale yellow color with an egg white appearance, with low fluidity and it contains proteins(7,9). It is reported that synovial fluid in arthritis cases is blurry in colors ranging from light yellow to dark yellow-brown, has a decreased viscosity and increased volume, and that joint fluid contains fibrin clots and is purulent in most cases(11,19). In this study, the synovial fluid of 7 cases showed mobile, clear and normal appearance, the synovial fluid of 25 cases had decreased viscosity, and was observed in colors varying between light yellow and dark yellow-brown, and synovial fluid was purulent in 18 cases. It is reported that M. bovis is the most common microorganism isolated from synovial fluid in cases of septic arthritis(6,7,13). Others(7,22) have indicated that S. aureus is the most commonly isolated microorganism in cases of septic arthritis. Mulon et al(17) have stated that the most common microorganism was Trueperella pyogenes in 172 cases with septic arthritis and Dogan et al(18) have stated that the most common microorganisms isolated were Trueperella pyogenes and E. coli in 82 calves with septic arthritis. In this study, S. aureus was the most common (n= 13). The other microorganisms identified were Streptococcus pluranimalium (n= 8), Trueperella pyogenes (n= 8), M. bovis (n= 6), E. coli (n= 5) Saprophyte spp. (n= 1) and Acinetobacter spp. (n= 1) according to isolation prevalence. As a result, it was concluded that clinical, radiological, utrasonographic examinations and physical and microbiological examinations of synovial fluid provide detailed information during the diagnosis of septic arthritis in calves, and that findings of microbiological examination provide important information especially in the early diagnosis of the disease, and contribute to the treatment in a large extent. It is suggested to comment that in the present study the agent that was isolated with more frequency was S. aureus (n=13). The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

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Literature cited: 1. Nouri M, Marjanmehr SH, Nowrouzian I. Deep septic arthritis of the fetlock joint in two dairy cows: clinical, radiographic and pathomorphologic findings. J Anim Poult Sci 2013;2(1):19-26. 2. Temizsoylu MD, Yigitarslan K. Arthritis and treatment options in bovine foot diseases. Türkiye Klinikleri J Vet Sci Surg-Special Topics 2015;1(1):66-72. 3. Kamiloglu A. Çiftlik hayvanlarında ayak hastalıkları. 1. Baskı, Medipres, Ankara, Türkiye: 2014. 4. Francoz D, Desrochers A, Latouche SJ. Effect of repeated arthrocentesis and single joint lavage on cytologic evaluation of synovial fluid in 5 young calves. Can J Vet Res 2007;71:129-134. 5. Heppelmann M, Kofler J, Meyer H, Rehage J, Starke A. Advances in surgical treatment of septic arthritis of the distal interphalangeal joint in cattle: A review. The Vet J 2009;182:162-175. 6. Desrochers A, Francoz D. Clinical management of septic arthritis in cattle. Vet Clin Food Anim 2014;30:177-203. 7. Goodarzi M, Khamesipour F, Mahallati SA, Karimi M, Azizi D, Azizi S. Study on prevalence of bacterıal causes ın calves arthrıtıs. ARPN J Agr Bio Sci 2015;10:6. 8. Jesse FFA, Bıtrus AA, Abba Y, Mahadzar M, Hambalı IU, Peter ID, Haron AW, Lıla MAM, Saharee AZ. Clinical management of septic arthritis in a sheep: A case report. Adv Anim Vet Sci 2017;5(6):267-270. 9. Gokhan N, Ozturk S. Evaluation of clinic, radiographic, ultrasonographic and histopathological findings of arthritis cases in calves. Erciyes Üniversitesi Vet Fak Derg 2016;13(1):19-29. 10. Yurdakul G, Saritas ZK. Evaluation of clinic, radiographic and some biochemical blood serum and synovial fluid parameters of arthritis cases in calves. Kocatepe Vet J 2013;6(2):13-22. 11. Nuss K. Synovial structures - cure or no cure? In. SIVAR International Congress, Cremona, Italy. 2011:39-40. 12. Arican M. Sığır cerrahi atlası. 1. Baskı. 290-96, Damla ofset A.Ş. Konya, Türkiye. 2017. 13. Shoieb SM, Sayed M, Ahmed M. Clinical and clinicopathological findings of arthritic camel calf associated with mycoplasma infection (Camelus dromedarius). J Dairy Vet Anim Res 2016;3(1):68.

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14. Landerer MCH, Habermacher J, Wenger B, Suter MM, Steiner A. Slow release antibiotics for treatment of septic arthritis in large animals. The Vet J 2010;184:14-20. 15. Rohde C, Anderson DE, Desrochers A, St-Jean G, Hull BL, Rings DM. Synovial fluid analysis in cattle: A review of 130 cases. Vet Surg 2000;29:341-346. 16. Jackson P. Treatment of septic artritis in calves. Farm Anim Pract 1999;596-601. 17. Mulon PY, Desrochers A, Francoz D. Surgical management of septic arthritis. Vet Clin Food Anim 2016;32:777-795. 18. Dogan E, Yanmaz LE, Okumus Z, Kaya M, Senocak MG, Cengiz S. Radiographic, ultrasonographic and thermographic findings in neonatal calves with septic arthritis: 82 cases (2006-2013). Atatürk Üniversitesi Vet Bil Derg 2016;11(1):6-12. 19. Gharagozlou MJ, Najafi J, Tabatabayi AH, Khazrainia P. Apathologic and microbiologic study on bovine arthritis associated with mycoplasma spp. Arch Razi Ins 2004;58:97-104. 20. Arican M, Elma E, Ozkan K. Clinical evaluation of infectious arthritis in extremities in calves. Turkish J Vet Surg 1998;4(1-2):5-7. 21. Bumin A, Temizsoylu MD, Kibar M, Alkan Z. Clinical, radiographic and arthroscopic evaluation of prulent arthritis in calves. Ankara Üniv Vet Fak Derg 2001;48:183-187. 22. Gorgul OS, Salci H, Özakin C, Cilo BD, Seyrek-Intas D, Celimli N, Cecen G. Arthroscopic diagnosis and comparison of arthroscopic lavage and intraarticular antibiotic applications in the treatment of experimentally induced different stage septic arthritis in goats. Kafkas Univ Vet Fak Derg 2010;16(6):957-967.

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Edición Bilingüe Bilingual Edition

Rev. Mex. Cienc. Pecu. Vol. 10 Núm. 1, pp. 1-266, ENERO-MARZO-2019

ISSN: 2448-6698

CONTENIDO CONTENTS Pags. Frecuencia de Cryptosporidium en perros asociados a establos lecheros y en áreas urbanas del estado de Aguascalientes, México

Distribución potencial de Musca domestica en el municipio de Jesús María, Aguascalientes, con el uso de escenarios de cambio climático

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Control de la helmintiasis en becerros criados en una región semiárida cálida de Brasil

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Importancia de la jerarquía social sobre los comportamientos alimenticios y parasitarios de ovinos criados en dos sistemas pastoriles

Importance of sheep social hierarchy on feeding behavior and parasite load in silvopastoral and grass monoculture grazing systems Carolina Flota-Bañuelos, Juan A. Rivera-Lorca, Bernardino Candelaria-Mar�nez........................................................................................................................................................52

Aislamiento e identificación de bacterias ácido lácticas con potencial probiótico para becerros del altiplano mexicano

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Efecto de monensina intraruminal sobre el β-hidroxibutirato, enfermedades del periparto, producción de leche y sus componentes en ganado Holstein Effect of an intraruminal monensin bolus on blood β-hydroxybutyrate, peripartum diseases, milk yield and solids in Holstein cows Pedro Melendez, Alejandra Arévalos, Mario Duchens, Pablo Pinedo..........................................................................................................................................................................84

Evaluación y análisis sensorial del Queso Bola de Ocosingo (México) desde la perspectiva del consumidor

Consumer evaluation and sensory analysis of Queso Bola de Ocosingo (Mexico) Mónica Agudelo-López, Alfredo Cesín-Vargas, Angélica Espinoza-Ortega, Benito Ramírez-Valverde........................................................................................................................104

Factors affecting the ruminal microbial composition and methods to determine microbial protein yield. Review

Factores que afectan la composición microbiana ruminal y métodos para determinar el rendimiento de la proteína microbiana. Revisión Ezequias Cas�llo-López, María G. Domínguez-Ordóñez............................................................................................................................................................................................120

Dinámica de infección por Cystoisospora suis (Isospora suis) en una granja piloto ubicada en el estado Carabobo, Venezuela

Infection dynamics of Cystoisospora suis (Isospora suis) on a pilot swine farm in Carabobo State, Venezuela Juan Carlos Pinilla León, Natalia Da Silva Borges.......................................................................................................................................................................................................149

Design of an electrochemical prototype to determine relative NaCl content and its application in fresh cheeses

Desarrollo y evaluación de un prototipo electroquímico para determinar el contenido relativo de NaCl y su aplicación en quesos frescos Rubén Cázares-Gallegos, Juan Antonio Vidales-Contreras, Alejandro Isabel Luna-Maldonado, Michael E. Hume, Ramón Silva-Vázquez, Armando Quintero-Ramos, Gerardo Méndez-Zamora 161

La calidad sanitaria del chorizo rojo tradicional que se comercializa en la ciudad de Toluca, Estado de México

Hygienic quality of the traditional red chorizo commercialized in the city of Toluca, State of Mexico Ana Laura Becerril Sánchez, Octavio Dublán García, Aurelio Domínguez-López, Daniel Arizmendi Cotero, Baciliza Quintero-Salazar....................................................................172

Impacto de la vigilancia sanitaria del clembuterol en Guerrero, México: Resultados de 2011 a 2015

Impact of health monitoring of clenbuterol in Guerrero, Mexico: Results from 2011 to 2015 Luis Alberto Chávez-Almazán, Jesús Antonio Díaz-Or�z, Diana Garibo-Ruiz, Mario Alberto Alarcón-Romero, Miguel Angel Mata-Diaz, Beatriz Pérez-Cruz, Elizabeth Godoy-Galeana..................................................................................................................................................................186

Composición botánica y valor nutritivo de la dieta consumida por bovinos en un área invadida por pasto rosado [Melinis repens (willd.) Zizka] Botanical composition and nutritive value of the diet consumed by cattle in an area invaded by natal grass [Melinis repens (Willd.) Zizka] Obed Gabriel Gu�érrez Gu�érrez, Carlos Raúl Morales Nieto, José Carlos Villalobos González, Oscar Ruíz Barrera, Juan Ángel Ortega Gu�érrez, Jorge Palacio Núñez.............212

Dosis letal media (DL50) y reducción de crecimiento (GR50) por irradiación gamma en pasto garrapata (Eragrostis superba)

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Rendimiento de forraje y sus componentes en variedades de alfalfa en el altiplano de México

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Evaluation of clinical, radiological, ultrasonographic and microbiological findings of septic arthritis in 50 calves

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Revista Mexicana de Ciencias Pecuarias Rev. Mex. Cienc. Pecu. Vol. 10 Núm. 1, pp. 1- 266, ENERO-MARZO-2019

Cryptosporidium infection frequency in dogs on dairy farms and in urban areas of the state of Aguascalientes, Mexico Irene Vitela-Mendoza, Kenia Padilla Díaz, Carlos Cruz-Vázquez, Le�cia Medina-Esparza, Miguel Ramos-Parra...........................................................................................................1

Rev. Mex. Cienc. Pecu. Vol. 10 Núm. 1, pp. 1-266, ENERO-MARZO-2019