PRODUCTION EVALUATION AND CARCASE MEAT QUALITY OF F1 RED ANGUS-BRAHMAN AND CHAROLAIS-BRAHMAN CROSSES.
FINAL REPORT San José, Costa Rica March 3, 2018.
The present project was executed in twelve cow-calf operation type cattle farms during a period of four years (2013-2016) in Costa Rica. Base cow herd of the farms were Brahman pure breed the most. Bulls breeds used were Charolais and Red Angus as semen which straws were donated by the Department of Agricultures of Kansas and the Department of Agriculture of Montana with the support of the American International Charolais Association (AICA), as partners with INTA in the project.
About 548 cows were time fixed artificial inseminated during the period, out of which 111 offspring were born and some 68 cows are still pregnant. This means, a pregnant rate of about 32,7 %. This low rate is the result of several factors related to cows being inseminated along the year without any consideration of regional and seasonal natural effects on cow fertility rates, nutritionally unprepared cows for breeding, synchronization protocols failures due to its design for zones different to tropical ones, i.e. tropically unadjusted and even more important no designed for Cebu type of cattle. This issue is retaken again as a proposal of a shorter study at the end of this document, looking for improvements of this important aspect of the technology.
Although only small group of the available set of animals could be statistically analyzed, the rest of animals showed similar tendency. The results indicate performance of crossed bread F1´s resulted in better live weights as adjusted, weaning weight, year and 18 month weights, than Brahman pure animals. This is particularly true for F1´s Charolais.
Testing of meat quality was possible only in a small group of animals. As consecuence, only tendencies can be showned. As averages meat quality in terms of tenderness, flavor, color and juicity was superior in crosses F1´s than Brahmans, particularly in Charolais F1´s.
Results as animal performance and meat quality of crosses, were as expected in the project, even though statisticall analysis is limited. Quite certainly the results give support and evidence of the benefits of the crosses in productivity and meat quality, particularly of the Charolais F1´s as terminal crosses. Otherwise, using F1´s as females in the herd would make quite difficult to handle it by the costarrican cattleman in his small caw-calf operation, and reducing his chances of produce F1´s and its benefits continuously.
Under such conditions, is quite difficult the spreading of the technology of F1´s crossings, let say with Charolais semen, because of the failures of the time fixed AI (TFAI). This is the justification of a second, shorter part, of the project being proposed at the end of this document, which is based in a strategy of herd management as a whole, more than TFAI as unique component to take care of.
A Cooperation Agreement was signed by INTA and the Departments of Agriculture of Kansas (DAK) and Montana (DAM) and the American International Charolais Association (AICA). The objective of this initiative is the promotion of scientific and technological exchange between participating institutions. The agreement established a Project of Artificial Insemination in beef cattle and the evaluation and dissemination of performance and meat quality of Charolais and Red Angus crosses with Brahman cows in collaborative Costa Rica farms.
An inmediate positive effect on productivity of cattle farms is derived from reproduction management via breed crosses. For maximum expression of heterosis in crossed animals, which can reach up to 20 % in weaning and market weight, use of distance genetic pools is needed, such as European (Bos Taurus) and Zebu (Bos indicus) type of breeds
This es particulary true in F1´s animales like the ones being promoted by the present Project: Charolais x Brahman and Red Angus x Brahmans (50 % blood from both parents). The idea is not to change the genetics of the Costa Rica cow herd of Brahman breed, because it is the basis to express that potencial hybrid vigor being looking for. That cow herd has to be maintained and in constant improvement to get the most of F1 crosses with Charolais and Red Angus semen of the best animals available in Kansas and Montana. It has to be a terminal F1 crossed animals like the ones just mentioned. The present Project aim is to solve problems of low weaning weights, low daily body gain per animal and per hectare, and low meat quality in Costa Rica cattle Industry. This can be done modifying the reproductive managment of the cow herd using the best pool gen of european cattle breeds available in USA, without exposing the genetic Brahman base and potential of the beef industry of Costa Rica.
To evaluate production and carcass quality performance of breeding crosses (F1) between Brahman based cows and Charolais and Angus breeds of high quality genetic bulls from Kansas and Montana, USA in different agro ecological environments and farm managements.
If crossing practices were of extended use in Costa Rica, cattle industry would increase its productivity and improve meat quality, which benefits cattlemen and consumers as well.
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I. Comparative Breed Types Performance based on data from Los Diamantes Experimental Station of INTA at Guápiles.
This result indicates that contemporary groups of animals, under pasture grazing system, Charolais x Brahman F1 (C50/B/50) performed by 25 % better than pure bred Brahman animals; and Red Angus F1 (A50/B50) performed by 13 % better than pure bred Brahman animals at 18 months age adjusted weight.
Data analyzed includes n=67, male and females, BR100 n=44 ; A50/B50 n=10; C50/B50 n=9; and F1 Brangus x Brahman n=4 which are not included in this graph. Total data analysis is shown in appendix.
Eventhough the small set of data of the study, consistency of the differences across time makes the results very confident, as can be seen in the next chart. Quite the same tendency ocurrs if data is separated by animal sex. At the appendix the whole data is shown for further analysis. Handling the biological differences between Charolais F1´s and pure Brahman animals is much easier to see the meaning of these differences. For instance, the following graph shows the weaning adjusted
Even more, if biological differences, are translated in terms of money, is still much easier, to get the meaning of them. For instance, in a typical cattle farm in Costa Rica with a cow herd of 50 animals, and expecting 60 % pregnancy (30 offsprings) the cattleman would produce 850 kg more of alive weight at weaning age with F1 Charolais than with pure commercial Brahman. In terms of money this means an extra income of $1636, under pasture grazing conditions, with only mineral supplementation, being the unique difference, reproductive management to obtain crossed animals.
Even more, animal inventory will rotate faster, because F1´s animals reach market weight much before than pure Brahmans, as can see in this next chart.
So far up to this point things look a promising future for cattlemen if use this technology. However, there is a one problem that does not allow to go further, for the following and very important factor.
Looking carefully the following graph, is easy to see the serious problem that might reject this good technology by cattlemen and no benefits for cattle activity can be drawn as expected, if a solution cannot be found quickly.
This graph shows very low pregnancy rates with fixed time artificial insemination. At midterm of the project, when more than half the semen straws (326) were used, a problem
of this kind was obvious we were facing, so the chart just came to confirm that. Ten different inseminators, some with more experience than others, but all with the same pregnancy rate. Immediately, semen was send to a quality exam, factor that was discarted once the report was received indicating this was not the problem. Synchronization protocol used was carefully review, appearing some doubts. Checking with some specialists, looks like the protocol used is one of a 72-hour heat detection. Doubts on that came from the visit to Montana and Kansas in June 2016. Talking with US cattlemen, both types of protocols are used, fixed time AI in the case of large ranches where no much time is available for heat detection, and this last one just mentioned, for the opposite reason in small cow-calf operations. A comparison of protocols is included in this report with the purpose if somebody reading it might have an idea on this issue and give us a help because we are no totally sure if this is the problem.
This is the problem also that we do not have enough animals by sex and by bull breed to make some comparisons. This can be seen in this following graph of 15 animals the most of each bull in an ample period of time where having contemporaries for statistical studies become quite or almost impossible.
As was said, after checking twice during the period of the project, semen quality, as the possible cause of the problem was discarded, although couple of bull’s semen resulted with less than 12 million/cc normal sperm in the last exam. The other possible source of the problem is the fix time synchronization protocols and its application, recognizing that, they were establish for climate conditions quite different to tropical ones.
Second semen quality test by February 22, 2017.
CODE BULL NAME BREED NORMAL SPERMS *
49CH2465 COOLEY ROYCE CHAROLAIS 22,5
90CH3842 EATONS LEADER CHAROLAIS 49,4
49CH2427 JDJ ROYAL TRADE CHAROLAIS 13,7
49CH2267 WH GRAHAM CHAROLAIS 7,5 **
1AR922 FRITZ GOLDEN OSCAR RED ANGUS 14,4
36ARO34 MAJESTIC LIGHTNING RED ANGUS 18,2
1AR935 MUSHRUSH LOCK N LOAD RED ANGUS 8,9 **
1AR0914 RED SIX MILES SAKIC RED ANGUS 18,9
*Andrology Lab. Vet School. Nat. Universty Feb. 22, 2017. ** < 12 million NS not recommended
The original protocol been used in the project was the one offered by the Vet. Quirós. He was supposed to be the official veterinarian to be involved in the project but, his very busy agenda did not allow it. After this, the farmers had to contract an available vet in the region, following Dr’s Quirós protocol. The figures shown in the table are product of this situation just commented.
Working las year with Antonio Correia, a fellow from Brasil and an especialist in genetics and reproduction, we realized this protocol being used is not a fixed time AI protocol, but a 72 hrs heat detection one. A month ago, comparing Dr. John Jaeger from K.State work in ITCR Costa Rica, confirmed our feelings about a protocol being applied inadequately. In a very similar protocol of Jaeger and Quirós, the first one is triyng to find out what time lapse between 54, 64, 74 or 84 hours after CIDR is retired, is the best to have the highest fertility rate, while the second one makes AI just at 48 hours. Correias protocol makes a different protocol somehow, because CIDR is retired not the day 8 but at the day 10 and waits 48 hours later for AI, which is closer to Jaeger timings 64-74 vs 96 hours of Correias as can be seen in the following table. This might explain the bad results in the project. This why in the last two groups of cows, were AI using Correia´s protocol, expecting to have much better results. We have to wait to see if this is the problem.
General description of the protocols
In trying to relief the problem, the producer, in most cases, uses a bull immediately for natural breeding to get better pregnancy rates, reaching about 70 % at the end. Others like Mr. Gilberto Rojas, get the cows repeating again, inseminated once more, and reaching similar pregnancies of 70 % as with natural breeding, mentioned before. Being said that, it is very possible that another factor, like malnutrition, more than animal condition as such, is playing an important role in this unsuccessful pregnancy result.
As expected, results of the F1´s animals weight gain performance is much better than pure Brahman contemporary counterparts, and quality meat as well. I spite of this, individual performance is not so attractive income wise, due to that so very low pregnancy rates, which increases costs per animal borne. This why we are presenting a complementing project proposal, based on herd management to take care of the problem and to get pregnancy rates of 70 % at least, meanwhile and parallel study correcting the AIFT protocol to an appropriate one to our tropical conditions, and a such to make viable this technology in Costa Rica beef commercial ranches.
As with any technology adoption, rent of its application is a must. If we check the cost of a fixed time AI, which is about $20 vet medicines, the cost of a semen straw, let say another $20 plus the inseminator service $10 more per animal is a total of $50/animal and with a 30 % pregnancy rate, each pregnant cow costs $50/0,30 = $167. This amount is almost the same extra money Mr. Eduardo Vargas got from the F1 Charolais compared to the pure Brahman animals. This means there is no benefit at all to adopt this technology under the present conditions just described in spite of performance and meat quality of the F1´s.
PRODUCT DOSIS/ANIMAL COST ₡ COSTO $
INTRAVAGINAL DEVICE 1 ₡6.210,00 $11,39
ESTRADIOL BENZOATO 2 ml ₡335,70 $0,62
CICLASE DL 2 ml ₡1.296,41 $2,38
NOVORMON 2 ml ₡2.317,00 $4,25
CIPIOSYM 2 ml ₡433,55 $0,80
PROTOCOL APLICATION ₡14.407,34 $26,43
TOTAL COST COW SYNCHRONIZED AND AI ₡25.000,00 $45,87
In the project cost of semen was offered for free to the cattlemen involved, but surely it has to be taken into account.
Project is very gratefull with Julio Rodríguez and Olger Murillo, from ITCR, who gave support to the project on this analysis
Introduction.-
One of the expected benefits of crosses, other than those related with growth and feed efficiency, is the improvement in meat quality. It is well known that European breeds have much better meat quality than zebu animals. As such, one can expect Bos taurus genes participating in F1 crosses should improve meat quality of these animals.
Marbling and tenderness are the two most important factors or indicators of meat quality. Given that tenderness is a much easier measure to take, this was chosen in the present study as the parameter of meat quality.
Been this said, the objective of the present study was to compare meat tenderness of F1´s Charolais x Brahman, Red Angus x Brhaman and pure Brahman animals.
Literature review.-
According with Prescott 1966, mentioned by IPCVA, the most important factors that affect animal and meat quality are weight, sex, animal age, fatting grade, growth curve, feeding and breed of animals.
On this base, the present study is looking for meat quality characteristics thinking in the consumer, but also production efficiency, considering producer interest. The present project utilized breed as the factor that by means of reproduction makes use of European breed genes which are considered to transfer better meat quality characteristics (tenderness and marbling). Age, as meat quality factor, is automatically included since the expected better feed efficiency in F1´s means, younger age to reach market weight.
A small group of cattle animals (n=12) of four genetic cattle types were evaluated to see tendencies in meat quality. The results indicated a tendency of F1 Charolais x Brahman crosses to be superior than the other three groups, particularly than Brahman pure counterparts.
Materials and methods .-
1.- Animals.
In the present case, there was not possible to have an experimental study for meat quality, meanly because the many animals needed for this type of tests. Instead, a monitoring type of study was implemented. A group of 12 contemporary animals were used, all of them coming from the project activities executed in “Los Diamantes” Experimental Station of INTA, located in Guápiles, Atlantic Zone. Groups of 3 animals were used for each of 4 genetic profiles in the test.
If age of an animal to slaughter has positive effect on meat quality, it is expected that crossed animals between Zebu and European breeds, had better meat quality as well, particularly F1´s because the recognized characteristics of growth rate of these animals and the better meat quality of European breeds, which are part of the cross.
Animals.
With the purpose of execute the test of meat quality, with crossed animals of Brahman cows with bull semen of the Project, sixteen of they were selected from Los Diamantes Experimental Station of INTA in Guápiles.
Selected animal were the following aspects:
All three genetic profiles of the Project had to be represented, plus one more that was available in Los Diamantes, Brangus x Brahman crosses, although they were mostly females and it was of interest to see meat quality of them.
In this type of studies is important to have contemporary animals and of the same sex. Even more relevant would be animals close to slaughter weight, so an effort was made in this sense. However, this was a difficult task, because animals were
contemporaires but of different genetic profile, so their performance were different as was shown initially in this document. In this case Charolais F1´s were at the top and pure Brahman at the bottom.
List of animals tested for meat quality
Because Budget limits and above considerations only 4 animals were possible to have by group.
Because confusion, at the time of picking the animals at the end F1 Charolais group had 5 animals an F1 Red Angus only 2.
Genetic profile ID Sex
Charolais F1
Kg Initial Weight Age PA550
Graham 457/15 M 467 22,5 408 Royal 455/15 M 458 22,5 426 Eaton 451/15 M 417 23,0 373 Cooley 465/15 M 402 23,0 ND
Average 436 22,8
Angus Rojo
Majestic 441/15 M 349 23,0 261 Mushrush 443/15 M 372 18,5 290
Average 360,5 20,8
Brahman puro 653/15 M 313 22,0 274 643/15 M 300 23,0 231 627/15 M 331 23,0 250
Average 314,5 22,7
Brangus F1 412/15 H 294 21,5 285 390/15 H 344 23,5 294 394/15 H 267 23,0 293 Average 301,7 22,7
RESULTS.
1. Liveweight of animals at slaughterhouse. This chart shows the different body weight of the four group of animals. Age wise they were 22 months old 0 50 100 150 200 250 300 350 400 450 BRAHMAN CHAROLAIS ANGUSROJO BRANGUS
In all cases, F1 animals showed a tendency of better tenderness, juicy and flavor than pure Brahman animals
Even though there is not possible to say meat quality is better in F1´s animals than pure Brahman animals, because of the nature of this study. However, the tendency observed in this sense might indicate, chances are of that possibility according with the reasoning mentioned initially in this document. This has to be proved and which we expect it will occur with coming data from Gilberto Rojas, in some 18 months.
mlm.modelo.003_PDAj205_REML<-lme(PDAj205~1+Sexo+Raza+Sexo:Raza ,random=list(REP=pdIdent(~1)) ,method=\"REML\" ,control=lmeControl(niterEM=150 ,msMaxIter=200) ,na.action=na.omit ,data=mlm.modeloR.data00 ,keep.data=FALSE)
Resultados para el modelo: mlm.modelo.003_PDAj205_REML
Variable dependiente: PDAj205
n AIC BIC logLik Sigma R2_0 R2_1 67 549,06 569,84 -264,53 19,20 0,25 0,25 AIC y BIC menores implica mejor Pruebas de hipótesis secuenciales
numDF denDF F-value p-value (Intercept) 1 34 5836,31 <0,0001 Sexo 1 34 0,04 0,8418 Raza 3 34 3,72 0,0205 Sexo:Raza 3 34 2,72 0,0599
Source numDF denDF F-value p-value Sexo 1 34 1,11 0,3000 Raza 3 34 4,10 0,0138 Sexo:Raza 3 34 2,72 0,0599
PDAj205 - Medias ajustadas y errores estándares para Sexo*Raza LSD Fisher (Alfa=0,05) Procedimiento de corrección de p-valores: No
Sexo Raza Medias E.E.
H ch 211,00 13,58 A M ch 192,71 7,26 A B H ang 192,29 7,26 A B
M bran 188,00 19,20 A B C
H bran 181,67 11,09 A B C M bra 177,65 3,77 B C H bra 169,33 4,53 C M ang 163,67 11,09 C Medias con una letra común no son significativamente diferentes (p > 0,05)
Parámetros de los efectos aleatorios
Modelo de covarianzas de los efectos aleatorios: pdIdent Formula: ~1 | REP
Desvíos estándares y correlaciones (Intercept) (Intercept) 1,0E-03
Especificación del modelo en R
mlm.modelo.004_PAAj365_REML<-lme(PAAj365~1+Sexo+Raza+Sexo:Raza ,random=list(REP=pdIdent(~1)) ,method=\"REML\" ,control=lmeControl(niterEM=150 ,msMaxIter=200) ,na.action=na.omit ,data=mlm.modeloR.data00 ,keep.data=FALSE)
Resultados para el modelo: mlm.modelo.004_PAAj365_REML
Variable dependiente: PAAj365
Medidas de ajuste del modelo
n AIC BIC logLik Sigma R2_0 R2_1 67 600,25 621,03 -290,13 29,63 0,55 0,55 AIC y BIC menores implica mejor
Pruebas de hipótesis secuenciales
numDF denDF F-value p-value (Intercept) 1 34 3992,44 <0,0001 Sexo 1 34 0,12 0,7322 Raza 3 34 19,81 <0,0001 Sexo:Raza 3 34 4,51 0,0091
Pruebas de hipótesis marginales
Source numDF denDF F-value p-value Sexo 1 34 0,75 0,3929 Raza 3 34 14,43 <0,0001 Sexo:Raza 3 34 4,51 0,0091
PAAj365 - Medias ajustadas y errores estándares para Sexo*Raza LSD Fisher (Alfa=0,05) Procedimiento de corrección de p-valores: No
Sexo Raza Medias E.E. H ch 292,00 20,95 A
M ch 290,00 11,20 A
H ang 268,43 11,20 A B
M bran 263,00 29,63 A B C
H bran 234,00 17,11 B C
M bra 213,23 5,81 C H bra 207,72 6,98 C M ang 195,00 17,11 C Medias con una letra común no son significativamente diferentes (p > 0,05)
Parámetros de los efectos aleatorios
Modelo de covarianzas de los efectos aleatorios: pdIdent Formula: ~1 | REP
Desvíos estándares y correlaciones (Intercept) (Intercept) 0,01
Especificación del modelo en R
mlm.modelo.005_P18Aj550_REML<-lme(P18Aj550~1+Sexo+Raza+Sexo:Raza ,random=list(REP=pdIdent(~1)) ,method=\"REML\" ,control=lmeControl(niterEM=150 ,msMaxIter=200) ,na.action=na.omit ,data=mlm.modeloR.data00 ,keep.data=FALSE)
Resultados para el modelo: mlm.modelo.005_P18Aj550_REML Variable dependiente: P18Aj550
Medidas de ajuste del modelo
n AIC BIC logLik Sigma R2_0 R2_1 43 375,73 391,29 -177,87 33,60 0,63 0,63 AIC y BIC menores implica mejor
Pruebas de hipótesis secuenciales
numDF denDF F-value p-value (Intercept) 1 22 3534,06 <0,0001 Sexo 1 13 2,28 0,1546 Raza 3 13 16,97 0,0001 Sexo:Raza 3 13 1,98 0,1668
Pruebas de hipótesis marginales
Source numDF denDF F-value p-value
Sexo 1 13 0,64 0,4391 Raza 3 13 10,01 0,0011 Sexo:Raza 3 13 1,98 0,1668
P18Aj550 - Medias ajustadas y errores estándares para Sexo*Raza LSD Fisher (Alfa=0,05)
Procedimiento de corrección de p-valores: No
Sexo Raza Medias E.E.
M ch 383,33 13,72 A
H ch 360,00 33,60 A B
M bran 349,00 33,60 A B C
H ang 342,25 16,80 A B C
M ang 298,33 19,40 B C D
H bran 290,67 19,40 B C D
M bra 282,40 8,68 C D H bra 271,80 10,63 D Medias con una letra común no son significativamente diferentes (p > 0,05)
Parámetros de los efectos aleatorios
Modelo de covarianzas de los efectos aleatorios: pdIdent Formula: ~1 | REP
Desvíos estándares y correlaciones (Intercept) (Intercept) 1,9E-03
Número Sexo F.Nto P.Nto Raza #Padre Raza Padre FecDestete P.Dest. E.Dest. PDAj205 GDPD F.PA PA E.PA EA-ED PAAj365 GDPA F.P18 P18 EP18 E18-ED PAj550 GDP18 390-15 H 28/02/2015 35 BRANGUS50 973-4 BRA/100 24/11/2015 229 269 183 0,721 15/04/2016 285 412 143 246 0,392 25/08/2016 318 544 275 294 0,324 621-15 M 09/03/2015 33 BRA/100 973-4 BRA/100 24/11/2015 201 260 165 0,646 15/04/2016 215 403 143 181 0,098 25/08/2016 287 535 275 273 0,313 394-15 H 09/03/2015 32 BRANGUS50 973-4 BRA/100 24/11/2015 205 260 168 0,665 15/04/2016 267 403 143 238 0,434 25/08/2016 304 535 275 293 0,360 608-15 H 11/03/2015 34 BRA/100 973-4 BRA/100 24/11/2015 179 258 149 0,562 15/04/2016 208 401 143 182 0,203 25/08/2016 228 533 275 211 0,178 610-15 H 11/03/2015 39 BRA/100 269-6 BRA/100 24/11/2015 226 258 188 0,725 15/04/2016 319 401 143 292 0,650 25/08/2016 317 533 275 302 0,331 612-15 H 16/03/2015 34 BRA/100 973-4 BRA/100 24/11/2015 205 253 173 0,676 15/04/2016 223 396 143 193 0,126 25/08/2016 250 528 275 229 0,164 396-15 H 16/03/2015 35 BRA/100 973-4 BRA/100 24/11/2015 205 253 173 0,672 15/04/2016 261 396 143 235 0,392 25/08/2016 286 528 275 274 0,295 631-15 M 18/03/2015 40 BRA/100 973-4 BRA/100 24/11/2015 174 251 149 0,534 15/04/2016 211 394 143 191 0,259 25/08/2016 244 526 275 237 0,255 629-15 M 18/03/2015 40 BRA/100 973-4 BRA/100 24/11/2015 209 251 178 0,673 15/04/2016 266 394 143 242 0,399 25/08/2016 315 526 275 311 0,385 627-15 M 18/03/2015 39 BRA/100 973-4 BRA/100 24/11/2015 221 251 188 0,725 15/04/2016 249 394 143 219 0,196 25/08/2016 271 526 275 250 0,182 441-15 M 19/03/2015 26 ANG/50-BRA/50 MUSHRU ANG/100 24/11/2015 192 250 162 0,664 15/04/2016 210 393 143 182 0,126 25/08/2016 271 525 275 261 0,287 443-15 M 19/03/2015 26 ANG/50-BRA/50 MUSHRU ANG/100 24/11/2015 192 250 162 0,664 15/04/2016 214 393 143 187 0,154 25/08/2016 294 525 275 290 0,371 445-15 M 19/03/2015 31 ANG/50-BRA/50 MUSHRU ANG/100 24/11/2015 197 250 167 0,664 15/04/2016 241 393 143 216 0,308 25/08/2016 338 525 275 344 0,513 439-15 M 19/03/2015 33 CHA/50-BRA/50 EATONS CHA/100 24/11/2015 207 250 176 0,696 15/04/2016 298 393 143 277 0,636 25/08/2016 306 525 275 300 0,360 398-15 H 19/03/2015 29 BRA/100 973-4 BRA/100 24/11/2015 224 250 189 0,317 15/04/2016 266 393 143 236 0,294 25/08/2016 323 525 275 313 0,360 614-15 H 19/03/2015 30 BRA/100 269-6 BRA/100 24/11/2015 192 250 163 0,648 15/04/2016 266 393 143 246 0,517 25/08/2016 286 525 275 281 0,342 400-15 H 20/03/2015 31 ANG/50-BRA/50 MUSHRU ANG/100 24/11/2015 205 249 174 0,699 15/04/2016 259 392 143 235 0,378 25/08/2016 319 524 275 317 0,415 633-15 M 20/03/2015 31 BRA/100 973-4 BRA/100 24/11/2015 199 249 169 0,675 15/04/2016 227 392 143 201 0,196 25/08/2016 280 524 275 271 0,295 402-15 H 23/03/2015 33 ANG/50-BRA/50 FRITZ ANG/100 24/11/2015 208 246 179 0,711 15/04/2016 260 389 143 237 0,364 25/08/2016 331 521 275 333 0,447 404-15 H 23/03/2015 32 ANG/50-BRA/50 RED ANG/100 24/11/2015 194 246 167 0,659 15/04/2016 265 389 143 246 0,497 25/08/2016 334 521 275 343 0,509 639-15 M 23/03/2015 37 BRA/100 269-6 BRA/100 24/11/2015 205 246 177 0,683 15/04/2016 277 389 143 258 0,503 25/08/2016 276 521 275 266 0,258 635-15 M 23/03/2015 41 BRA/100 973-4 BRA/100 24/11/2015 216 246 187 0,711 15/04/2016 235 389 143 208 0,133 25/08/2016 315 521 275 311 0,360 637-15 M 23/03/2015 36 BRA/100 973-4 BRA/100 24/11/2015 197 246 170 0,654 15/04/2016 255 389 143 235 0,406 25/08/2016 316 521 275 319 0,433 447-15 M 24/03/2015 30 CHA/50-BRA/50 GRAHAM CHA/100 24/11/2015 214 245 184 0,751 15/04/2016 277 388 143 254 0,441 25/08/2016 358 520 275 365 0,524 451-15 M 25/03/2015 34 CHA/50-BRA/50 EATONS CHA/100 24/11/2015 211 244 183 0,725 15/04/2016 284 387 143 264 0,510 25/08/2016 363 519 275 373 0,553 453-15 M 25/03/2015 43 CHA/50-BRA/50 COOLEY CHA/100 24/11/2015 235 244 204 0,787 15/04/2016 344 387 143 326 0,762 25/08/2016 413 519 275 428 0,647 647-15 M 25/03/2015 29 BRA/100 973-4 BRA/100 24/11/2015 172 244 149 0,586 15/04/2016 172 387 143 149 0,000 25/08/2016 279 519 275 283 0,389 643-15 M 25/03/2015 49 BRA/100 973-4 BRA/100 24/11/2015 207 244 182 0,648 15/04/2016 207 387 143 182 0,000 25/08/2016 246 519 275 231 0,142 645-15 M 25/03/2015 32 BRA/100 973-4 BRA/100 24/11/2015 185 244 161 0,627 15/04/2016 229 387 143 210 0,308 25/08/2016 302 519 275 307 0,425 408-15 H 30/03/2015 35 ANG/50-BRA/50 MAJEST ANG/100 24/11/2015 219 239 193 0,770 15/04/2016 309 382 143 294 0,629 25/08/2016 365 514 275 376 0,531 410-15 H 31/03/2015 42 CHA/50-BRA/50 GRAHAM CHA/100 24/11/2015 218 238 194 0,739 15/04/2016 310 381 143 297 0,643 25/08/2016 351 513 275 360 0,484 649-15 M 31/03/2015 33 BRA/100 973-4 BRA/100 24/11/2015 200 238 177 0,702 15/04/2016 233 381 143 214 0,231 25/08/2016 317 513 275 324 0,425 455-15 M 01/04/2015 41 CHA/50-BRA/50 ROYAL CHA/100 24/11/2015 214 237 191 0,730 15/04/2016 317 380 143 306 0,720 25/08/2016 402 512 275 426 0,684
651-15 M 01/04/2015 40 BRA/100 973-4 BRA/100 24/11/2015 200 237 178 0,675 15/04/2016 240 380 143 223 0,280 25/08/2016 300 512 275 304 0,364 457-15 M 04/04/2015 44 CHA/50-BRA/50 GRAHAM CHA/100 24/11/2015 209 234 189 0,705 15/04/2016 307 377 143 298 0,685 25/08/2016 384 509 275 408 0,636 618-15 H 04/04/2015 45 BRA/100 973-4 BRA/100 24/11/2015 200 234 181 0,662 15/04/2016 228 377 143 212 0,196 25/08/2016 254 509 275 249 0,196 620-15 H 04/04/2015 35 BRA/100 973-4 BRA/100 24/11/2015 172 234 155 0,585 15/04/2016 242 377 143 233 0,490 25/08/2016 277 509 275 287 0,382 653-15 M 11/04/2015 37 BRA/100 973-4 BRA/100 24/11/2015 188 227 173 0,665 15/04/2016 240 370 143 232 0,364 25/08/2016 268 502 275 274 0,291 655-15 M 23/04/2015 34 BRA/100 973-4 BRA/100 24/11/2015 196 215 188 0,753 15/04/2016 232 358 143 229 0,252 25/08/2016 265 490 275 275 0,251 622-15 H 23/04/2015 35 BRA/100 973-4 BRA/100 24/11/2015 184 215 177 0,693 15/04/2016 214 358 143 211 0,210 25/08/2016 256 490 275 267 0,262 624-15 H 23/04/2015 36 BRA/100 973-4 BRA/100 24/11/2015 192 215 185 0,726 15/04/2016 257 358 143 257 0,455 25/08/2016 288 490 275 305 0,349 623-15 M 16/05/2015 34 BRA/100 973-4 BRA/100 24/11/2015 186 192 196 0,792 15/04/2016 229 335 143 244 0,301 659-15 M 01/06/2015 40 BRA/100 973-4 BRA/100 24/11/2015 211 176 239 0,972 26/07/2016 229 421 245 251 0,073 659-2-15 M 01/06/2015 33 BRA/100 973-4 BRA/100 24/11/2015 167 176 189 0,761 25/05/2016 225 359 183 240 0,317 418-15 H 26/07/2015 33 ANG/50-BRA/50 RED ANG/100 03/02/2016 168 192 177 0,703 26/07/2016 292 366 174 291 0,713 420-15 H 26/07/2015 48 ANG/50-BRA/50 RED ANG/100 03/02/2016 217 192 228 0,880 26/07/2016 284 366 174 290 0,385 422-15 H 26/07/2015 33 ANG/50-BRA/50 RED ANG/100 03/02/2016 216 192 228 0,953 25/08/2016 289 396 204 286 0,358 465-15 M 28/07/2015 31 CHA/50-BRA/50 COOLEY CHA/100 03/02/2016 208 190 222 0,932 25/08/2016 314 394 204 305 0,520 628-15 H 01/08/2015 35 BRA/100 973-4 BRA/100 07/06/2016 203 311 146 0,540 25/08/2016 238 390 79 217 0,443 424-15 H 03/08/2015 35 CHA/50-BRA/50 COOLEY CHA/100 03/02/2016 208 184 228 0,940 26/07/2016 272 358 174 287 0,368 663-15 M 10/08/2015 35 BRA/100 973-4 BRA/100 07/06/2016 291 302 209 0,848 25/08/2016 303 381 79 233 0,152 665-15 M 10/08/2015 36 BRA/100 973-4 BRA/100 07/06/2016 231 302 168 0,646 25/08/2016 241 381 79 189 0,127 667-15 M 14/08/2015 37 BRA/100 973-4 BRA/100 07/06/2016 222 298 164 0,621 25/08/2016 231 377 79 182 0,114 669-15 M 17/08/2015 35 BRA/100 973-4 BRA/100 07/06/2016 191 295 143 0,529 25/08/2016 215 374 79 192 0,304 630-15 H 17/08/2015 34 BRA/100 973-4 BRA/100 07/06/2016 227 295 168 0,654 25/08/2016 247 374 79 209 0,253 671-15 M 19/08/2015 37 BRA/100 973-4 BRA/100 07/06/2016 250 293 186 0,727 25/08/2016 263 372 79 212 0,165 632-15 H 19/08/2015 37 BRA/100 973-4 BRA/100 07/06/2016 203 293 153 0,567 25/08/2016 209 372 79 165 0,076 636-15 H 31/08/2015 36 BRA/100 973-4 BRA/100 07/06/2016 246 281 189 0,747 25/08/2016 241 360 79 179 -0,063 634-15 H 31/08/2015 35 BRA/100 973-4 BRA/100 07/06/2016 251 281 193 0,769 25/08/2016 253 360 79 197 0,025 673-15 M 17/09/2015 39 BRA/100 973-4 BRA/100 07/06/2016 263 264 213 0,848 25/08/2016 271 343 79 229 0,101 675-15 M 17/09/2015 34 BRA/100 973-4 BRA/100 07/06/2016 192 264 157 0,598 25/08/2016 211 343 79 195 0,241 640-15 H 17/09/2015 35 BRA/100 973-4 BRA/100 07/06/2016 192 264 157 0,595 25/08/2016 182 343 79 137 -0,127 638-15 H 17/09/2015 34 BRA/100 973-4 BRA/100 07/06/2016 183 264 150 0,564 25/08/2016 188 343 79 160 0,063 642-15 H 17/09/2015 36 BRA/100 973-4 BRA/100 07/06/2016 195 264 159 0,602 25/08/2016 204 343 79 178 0,114 677-15 M 30/09/2015 40 BRA/100 973-4 BRA/100 06/07/2016 210 280 164 0,607 25/08/2016 222 330 50 203 0,240
Semen Straws received in May 2013: 600
Detailed semen straws used is shown in next table. Twelve cattlemen participated in the project. Based on the number of straws used in each farm, five of them were the most important: René Salazar, Asdrubal Barrantes, Eduardo Vargas, INTA Exp. Stn. Farm and
Gilberto Rojas. They all together, made use of 73 % of the available semen (600 straws). Inventory indicates no semen is left but 6 semen straws of Sakic, a Red Angus bull. Last two inseminations were made this past January 2018. The next map shows the ubication of 9 of the cattlemen. At the time of the elaboration of the map in 2016 Gilberto Rojas, ITCR and Carlos Villegas were not yet in the project.
Information presented in this document come from those farms, with exception of Gilberto Rojas, who came into the Project just by mid-2017, reason why non calf have born yet. Information derived from Mr. Rojas becomes very important and expected, due to his feeding system on feed lot. All offspring’s of 37 pregnant cows in the project, male and females, will go to feed lot, immediately after weaning, and all of them will be meat quality tested. Base on Mr. Rojas facts, in July 2019, all those animals will leave to the slaughterhouse at age of 14 months with 500 kg body weight. So that information is expected, because it will be the most complete of the project.
All the other farms base their feeding system on pasture grazing, with some variables in supplementation. Of these five farms, only INTA´s farm is located in the Caribean Tropical Region of the country, all others are located in the dry tropical region with six month of rainy season (may to November) and 6 months of dry season (december to april). In this last region available pasture grass reduces biomass significantly, reason why animals have
to be supplemented with hay, silage, sugar cane, agroindustrial products (molasses, rice pollards, citrus and pineapple pulp, palm kernel meal, poultry manure, cassava peels and remains, etc), cutting fodders and others. This depending of available supply in the region or the farmer own previous preparation. Lately the use of rotational grazing with electric fences in beef cattle is improving the availability of pasture biomass and feeding and animal condition to perform better. However much more has to be done for farmers to adopt this technology. The fact of the matter is that, probably, under nutritional status of cows and failures in preparing cow herd, for reproductive purposes stand by the low pregnancy rates of Costa Rica livestock activity. In general, cattlemen do not use a specific breeding season, even though they know cow fertility is better during certain periods of the year. This situation makes even more difficult, to prepare cows for reproduction, which means this might be a problem for fixed time artificial insemination as well.
Information available from Eduardo Vargas, René Salazar and Asdrubal Barrantes, is not large enough because insemination was done in a set of 5 to 7 events during the 4 years of the project. Besides management of reproduction the whole year long, cow herd of most Costa Rican beef farm is small. According with a cluster analyses of cattle farms made by Edwin Pérez (2015) based in Livestock Census 2000, in which 13 clusters of subsistence farms were no taken into account, average size of beef cattle farms was 97 ha, of which 67 % s corresponds to forage area, with an average of 75 animal heads. The beef farms in the project were no different to that, with the exception of INTA´s farm with 270 ha of pastures and about 400 heads. In all cases, group of cows being inseminated at once, were frequently between 10 to less than 20 animals. Two exceptions were INTA´s farm with 30 cows in the two occasions and Nataniel Drew with 32 cows. This last farm with a very low pregnancy rate.
Under such conditions was very difficult to have a set of contemporary animals large enough to take care of sex, bull breed and so on, for a statistical analysis. This way results of animal performance and meat quality, to be presented in this report, come from INTA´s farm, although not as large as desired but good enough for a statistical analysis. In the case of meat quality, only tendencies could be observed, given similar conditions as mentioned before, and because send a minimum number of animals to slaughterhouse for this type of test is not that easy, for obvious reasons. Tendencies of animal performance of René, Eduardo and Asdrubal will be used when needed, to support findings from INTA´s data analysis.
1. ReS: René Salazar 17,6
2. AB: Asdrubal Barrantes 15,7
3. EV: Eduardo Vargas 15,1 4. ELD: INTA Exp. Station 13,07 5. GR: Gilberto Rojas 11,7 6. ND: Nataniel Drew 5,0 7. ITCR: Tech. University Farm 4,5 8. NM: Nelson Montero 3,3 9. RoS; Rodolfo Salas 2,5 10. CV: Carlos Villegas 1,3 11. Zon: Zoncuano 1,2 12. JM: José Monge 1,2 13. BR: broquen straws 4,8 14. Semen quality test: 2 (A and B) 2,8 15. TOTAL 99,8 16. Use: used (598) 99,7 17. TR: Theoretical remained straws 0,3 18. RSR: real number of straws remained in thermos (6) 1,0 19. LPI: Last paid inventory -2,7 20. Effectivelly used 598-29-8-9= 552 92,0
The inventory was prepared at the end of December, 2017. Two more farm inseminations (AB and ReS) were done in January and February 2018 using 34 semen straws, and already included in table above, remaining only six semen straws of Sakic, an Angus Red bull. This means that our numbers do not match exactly, although are quite close: in theory 2 left, in the semen tank 6 left.
The last 3 columns of the above inventory table indicates that the three parts handling the semen straws failed: the list of semen coming from USA, Vet UNA Lab. Inventory, and INTA semen control manage different numbers, which difference goes between 0,3 to 2,7 %, very small and neglible difference, that gives us all a good administrative control of this valuable biological material at INTA.
Four activities of technology transfer were executed during the period of the Project. Each one of them with the presence of the fellow american counterpart mission with Mr. Billy Brown Leadership. The American missions were represented by people from Kansas, Montana and AICA. The threee field day events dates were from 2015 to 2017 in three different locations. Mr. Eduardo Vargas farm in Jaco at the Dry Pacific Region; Los Diamantes INTA Experimental Station at the Caribian Humid Tropical Region. This particular field day had a plus of teaching American experiences, in artificial insemination and sincronization protocol management for cattlemen and technitians from Costa Rica; and Mr. Asdrubal Barrantes farm at the Peninsula de Nicoya in the Dry Tropical Zone. Each one of them had an average attendance of 80 participants, represented mostly by Costarrican cattlemen. In between several small groups of American cattlemen came to Costa Rica as part of the mission counterpart, previous to the Project agreement and field days preparation activities. It is important to mention that in each American mission visit, about six of them, one to two days were taken to visit Costa Rican Ranchs, with very much success for all participants. Definitively these interchange activities were reach in shearing experiences for both nationality people.
A group of ten cattlemen from Costa Rica, including Jorge Morales as leadership of the group and Costa Rica responsible counterpart of the project, visits several Cattle Ranchs and related institutions in Kansas and Montana during a week in June, 2016. The trip was an overwhelming hospitality by the fellow American counterparts mentioned before, which allowed excellent learning experiences in all the participants.
VISIT TO USA JUNE 2016
NOMBRE DEL EVENTO “Gira de observación del potencial genético bovino de : Missouri, Kansas y Montana para Costa Rica”
1.1 DATE : Junio 12 al 18 del 2016
1.2 STATES VISITED : Estados de Missouri, Kansas y Montana, USA
1.3 MAIN PLACES : Manhattan, Estado de Kansas y Billings, estado de Montana
1.4 ENTE ORGANIZADOR : Departamento de Agricultura de Kansas (KDA), Departamento de Agricultura de Montana (MDA) y la Asociación Americana Internacional de Ganado Charolais (AICA). Por KDA estuvo a cargo Billy Brown, por MDA Treston Vermandel, por AICA Dave Hobbs. Por la contraparte INTA-Costa Rica facilitando la gestión de la gira Jorge Morales.
Dr. Jorge Morales G. 2231-2344 jmorales@inta.go.cr
Invest. eInnov.
CORRESPONSABLES TELEFONO DIRECCION ELECTRONICA DEPENDENCIA
Argerie Cruz Méndez 8882-5323 acruz@inta.go.cr
Invest. eInnov.
Ing. Edwin Orozco B. 26355119 eorozco@inta.go.cr Invest. eInnov.
COLABORADORES
Claudio Quirós 8821-3403 claudioquiros@gmail.com Veterinarian
Randall Arguedas randallarguedas15@gmail.com MAG-Sn Ramón
Juan Vicente Orozco orozco_juanvice@hotmail.com MAG-Sn Ramón
Roberto Soto rsoto@inta.go.cr INTA-Turrialba
Manuel Batista 8672-2891 mbatista@inta.go.cr
1.INTA-Farm
Eduardo Vargas 8395-2250 2.Cattleman
Nelson Montero 3.Cattleman
Rodolfo Salas 4.Cattleman René Salazar 5.Cattleman
Asdrubal Barrantes 6.Cattleman
Milton Villarreal 7.ITCR Farm Gilberto Rojas 8.Cattleman
Carlos Villegas 9.Cattleman
Zoncuano 10.Cattle Farm Acosta 11.Cattle Farm Nataniel Drew 12.Cattleman
Olger Murillo ITCR Julio Rodríguez ITCR
Bill Brown DA Kansas
Robert Williams rwilliams@charolaisusa.com ChASoc.Kansas
J.J. Jones Jones@kda.ks.gov DAG Kansas
Marty Heart mearnheart@mt.gov DAG Montana
Dee Likes Angus Asoc. Ka. Galen Fink finkbull1@twinvalley.net Fink Genetics
Dave Hobbs AICA
Given our experience with time fixe AI, and terminal crossing, whatever the cause, is only 50 % or less pregnancy, as you knows. Could be even worse if we try sexed semen, which is the ideal, given our goal, the F1´s as terminal crossing.
Some cattlemen strategy, to improve pregnancy, as Gilberto Rojas does, who is advised by Leo Navarro, is to inseminate in the following heat, the failed cows, again. As the synchronization remains effective in the next heat in many of the failed cows, these are again AI, reaching out about 70 % pregnancy, as a whole, at the end.
Another strategy of cattlemen is to leave a bull in charge of the AI failed cows, to get an acceptable pregnancy rate. Is here where it seems to me that we should give a try to a better finishing of the project.
Once the cow-calf operation already has the number needed of Brahman cows pregnant, for replacement purposes (by natural breeding or AI or both), the rest of the cow’s herd must be pregnant to get F1´s (in our case with Charolais, because its better performance, but which at the end is a choice of the cattlemen) to the market at young age with its better weight and meat quality than the pure Brahman counterparts. So we must give a complete information to the new cattlemen user of crossings, how to get the most out of the benefits of fixed time AI, and F1´s as a terminal, in such a way to have the most of income as well.
My point on which I would like to have o something your opinion and to see if there is a possibility to do something else as a final activity which for me we are this close to solve the problem. It is not an statistical but a practical study from which we can get proved practices and costs, and good base to transfer the technology with proper costarrican information. The study, as a rough idea, more or less will be as follows:
Four to 5 farms will dispose 30 Brahman cows each one. Those cows will be FT AI with Charolais, all farms at the same time, and the failing cows will be bred with a 3/84 Charolais Bull to be buy by the cattlemen involved in the project (natural breeding). But in this final activity herd management is a need where cows must be prepared for breeding season as it should be.
We might expect at least 20 calves per farm. Data will be collected from birth day until market weight and probably meat quality. Performance data will have several scenarios. First each farm conditions, which feeding is one very important because there will be under pasture and supplementation conditions and in feedlot conditions like Mr. Gilberto Rojas with high quality diet. Also a feedlot like Felix Mora in the south, with high quality cut forages, and products (like cassava root silage), etc, etc
What do you thing about a study like this. It seems to me that is a chance to have information that goes a little bit farther than only FTAI. It has to go a little bit inside herd management, in order to be successful, to fully get advantage of such a technology
Lets say that we can under this final activity 50 % pregnancy rate. Five farms times 30 cows, we need about 200 semen straws of a good Charolais bull from Kansas or Montana or both, but now it has to be sexed (male) semen. What do you do you think about it. Is it posibble to have a last donation from you guys up there to try this one last activity which might benefit both, USA Charolais cattle producers and of course to costarican ones. May be you can talk about this with Dave Hobbs in AICA and Dr. John Jaeger in Kansas University.
Well Shirley I will wait news from you. Thanks very much. And remember I will like to give a better finishing to this report.
Jorge Morales / INTA