Accounting for herd, year and season effects in genetic evaluations of dairy cattle: a review

Summary

The simulated population was characterized by its small herd size and the occurrence of preferential treatment for animals, which was modelled as a non-random association between sires and herds or as an extra effect due to the sire's genetic advantage. Robustness for prediction was compared between animal models with fixed herd effect and random herd effect. No difference in empirical accuracy was observed between the prediction models if data included only large herds, whereas for data with small herds, the random herd model had a higher accuracy and smaller empirical MSE than the fixed herd model in general. This superiority of the random herd model did not change under selection. The empirical MSE particularly increased when the extra effect, due to the sire's merit, was very large, where the MSE of the random herd model was significantly larger than the fixed herd model. This result suggested a larger bias in the random herd model. On the contrary, the random herd model had a higher accuracy and a lower MSE than the fixed herd model, when the extra effect was small. As the large magnitude of this extra effect is unrealistic, the random herd model is concluded to be superior to the fixed herd model in general.



Zusammenfassung

Behandlung kleiner Herden als fixeoder zufallige Grosle in einem Tiermodell



Die simulierte Population ist charakterisiert durch kleine Herdengrosen und Vorzugsbehandlung von Tieren, was im Modell einmal als nicht-zufallige Assoziation von Stieren und Herden, oder als Extra Einflus wegen des Zuchtwertes eines Stieres eingebaut wurde. Die Robustheit der Voraussage wurde durch Vergleich von Tiermodellen mit fixen und mit zufaalligem Herdeneffekt gepruft. Bei grosen Herden zeigte sich kein Unterschied zwischen den Voraussagemodellen, aber bei kleinen Herden zeigte das Modell mit zufalligen Herdeneinflussen hohere Genauigkeit und geringeren empirischen MSE, was bei Vorhandensein von Selektion sich nicht anderte. Der empirische MSE nahm zu, wenn die Sonderwirkung des vaterlichen Zuchtwertes gros war, wo dann der MSE des zufalligen Herdenmodells groser als beim fixen war, was eine grosere Verzerrung in ersterem vermuten last. Bei kleinen Extrawirkungen verhielt es sich umgekehrt. Nachdem grose Extrawirkungen unrealistisch sein durgten, sollte im allgemeinen das Modell mit zufalligen Herdenwirkungen uberlegen sein.

Treating small herds as fixed or random in an animal model.

The present study was undertaken on 91 first lactation records of Tharparkar cattle maintained at Livestock Research Station Beechwal, Bikaner, Rajasthan over a period of 15 years (2002-2016). The study was conducted on least squares means, genetic and phenotypic parameters of first lactation traits, breeding value estimation of sires for first lactation traits. The overall least-squares means for first lactation traits viz. AFC, FSP, FCI, FDP, FLL, FLMY, LMY/FLL and LMY/FCI were 1510.88 ± 22.29 days, 149.66 ± 5.15 days, 423.60 ± 6.23 days, 148.14 ± 6.05 days, 283.65 ± 7.65 days, 1832.99 ± 42.43 kg, 6.18 ± 0.14 kg/day and 4.03 ± 0.12 kg/day, respectively. The heritability estimates for first lactation traits viz. AFC, FSP, FCI, FDP, FLL, FLMY, LMY/FLL and LMY/FCI were 0.52±0.070, 0.12±0.166, 0.18±0.232, 0.04±0.030, 0.33±0.288, 0.40±0.394, 0.19±0.142 and 0.15±0.194, respectively. A mixed model least-squares analysis showed significant effect of sire on all the traits. The effect of period of birth was highly significant and effect of season of birth was non-significant for age at first calving. The effect of period of calving was highly significant for first calving interval and significant for first lactation length and lactation milk yield per day of first calving interval whereas effect of season of calving was nonsignificant for all first lactation reproduction and production traits. The breeding values of 10 Tharparkar bulls were estimated for various first lactation traits by four sire evaluation methods: simple daughter's average (D ), contemporary comparison method (CC), least-squares method (LSM) and best linear unbiased prediction method (BLUP). The breeding value for first lactation yield was also estimated by using sire index incorporating one auxiliary trait. The results showed that the LSM had the lowest error variance and highest coefficient of determination for all the first lactation performance traits. Therefore, the LSM method was considered to be the best method of sire evaluation. Although, higher rank correlations (> 0.92) between LSM and BLUP methods of sire evaluation for various traits indicated that there was higher degree of similarity of ranking of the sires (>92%) by both the methods of sire evaluation method for present set of data. Fkkjikjdj xk;ksa esa izFke nwX/k mRiknu xq.kksa ds mi;ksx ls lkaMkas dk sa sa z w q sa s s s a as sa sa z w q sa s s s a as sa sa z w q sa s s s a as ewY;kadu w a w a w a Lukrdksrj 'kks/k xzUFk s s z s s z s s z i'kq qq q vkuqokaf'kdh ,oa iztuu foHkkx q a a z q a a z q a a z i'kq fpfdRlk ,oa i'kq foKku egkfo|ky;] q a q q a q q a q jktLFkku i'kq fpfdRlk vkSj i'kq foKku fo'ofo|ky;] q S q q S q q S q chdkusj ss s 'kks/kdrkZ s Z s Z s Z% xfjek pkS/kjh SS S eq[; qq q lekns"Vk ss s % MkW WW WmfeZyk ikuw Z w Z w Z w vuq{ksi.k q s q s q s orZeku v/;;u esa i'kq/ku vuqla/kku dsanz] chNoky] chdkusj] jktLFkku esa iksf"kr Fkkjikjdj xk;ksa ds 15 o"kZ dh vof/k 1⁄42002&20161⁄2 rd ds 91 izFke nwX/k mRiknu vfHkys[kksa dk iz;ksx fd;k x;kA bl v/;;u esa i'kqvks dh izFke mRiknu ,oa iztuu {kerk fu/kkZj.k] lkaMks ds mRiknu ewY; dk fo'ys"k.k fd;k x;kA bl v/;;u ds nkSjku Fkkjikjdj xk;ks ds iztuu ekud izFke C;kar vkSlr vk;q 1510-88±22-29 fnu] izFke xHkZLFkkiu dky 149-66±5-15 fnu] izFke C;kar varjky 423-60±6-23 fnu] izFke 'kq"d vof/k 148-14±6-05 fnu] izFke nwX/k l=o.k vof/k 283-65±7-65fnu] izFke nwX/k mRiknu 1832-99±42-43 fdxzk] nwX/k mRiknu izfr izFke nwX/k mRiknu vof/k 6-18±0-14 fdxzk izfrfnu ,oa nwX/k mRiknu izfr izFke C;kar varjky 4-03±0-12 fdxzk izfrfnu ik;s x;sA leLr vkadM+ks ds fy, oa'kkxfrRo Øe'k% 0-52±0-070 izFke C;kar vkSlr vk;q 0-12±0-166 izFke xHkZLFkkiu dky] 0-18±0-232 izFke C;kar varjky] 0-04±0-030 izFke 'kq"d vof/k] 0-33±0-288 izFke nwX/k L=o.k vof/k] 0-40±0-394 izFke nwX/k mRiknu] 0-19±0-142 nwX/k mRiknu izfr izFke nwX/k mRiknu vof/k ,oa 0-15±0-194 nwX/k mRiknu izfr izFke C;kar varjky ik;k x;kA U;wure oxZ izfreku fo'ys"k.k esa xk; ds tud dk lHkh xq.kksa ij vFkZiw.kZ izHkko ik;k x;kA izFke C;kar vk;q ds fy;s tUe dh le;kof/k dk izHkko vfr&vFkZiw.kZ ,oa tUe _rq dk izHkko xSj&vFkZiw.kZ FkkA C;kar dh le;kof/k dk izHkko izFke C;kar varjky ij vfrvFkZiw.kZ] izFke nwX/k L=o.k vof/k ,oa nwX/k mRiknu izfr izFke C;kar varjky ij vFkZiw.kZ FkkA C;kar _rq dk izHkko lHkh xq.kksa ij xSj&vFkZiw.kZ ik;k x;kA 10 Fkkjikjdj lkaMks ds iztuu ewY;ks dk fo'ys"k.k larfr vkSlr] ledkyhu rqyuk fof/k] U;wure oxhZ; fof/k] mÙke jSf[kd i{k jfgr fu/kkZj.k fof/k ,oa izFke nwX/k mRiknu ds lkFk lgk;d xq.kksa ds mi;ksx }kjk djus ij U;wure oxhZ; fof/k loksZÙke ikbZ xbZ D;ksafd bl fof/k ds fy, =qfV izlj.k lcls de ,oa n`<+ ladYi xq.kkad lokZf/kd ik;k x;kA gkykafd U;wure oxhZ; fof/k ,oa mÙke jSf[kd i{k jfgr fu/kkZj.k fof/k ds chp mPp in lglEcU/k ladsr djrk gS] fd nksuksa fof/k;ksa ls lkaM ewY;kadu dh mikf/k orZeku fn, gq, vkadM+ks ds fy, leku gSA

Sire evaluation of tharparkar cattle using first lactation traits

The objective of this study was to compare models for appropriate genetic parameter estimation for milk yield (305-day) in crossbred Holsteins in the tropics, where only records from crossbred cows were avail- able. Eleven models with different effects of contemporary group (CG) at calving (herd-year-season or herd-year-month as fixed, and herd-year-month as random), age at calving (as linear or quadratic covariates, age-class, and age-class × lactation), and dominance were considered. On-farm records from small herds (n < 50) were included or excluded to validate the parameter estimates. Average Information Restricted Maximum Likeli- hood (AIREML) and Best Linear Unbiased Prediction (BLUP) were used to estimate variance components and breeding values. R-square (R 2 ) and standard error of heritability (h 2 ) were used to determine the appropriate model. The estimates of heritability from most models ranged from 0.18 to 0.22. CG formation of herd-year-month as a random effect slightly lowered the additive genetic variance but considerably decreased the permanent environmental variance. The model with age-class × lactation gave betterR 2 than other age adjust- ments. The models including records from smallholders gave similar estimates of heritability and a lower stan- dard error than the models excluding them. The estimate of dominance variance as a proportion of total variance was close to zero. The low ratio of dominance to additive genetic variance suggested that the inclusion of domi- nance effects in the model was unjustified. In conclusion, the model including the effects of herd-year-month, age-class × lactation, as well as additive genetic, permanent environmental and residual effects, was the most ap- propriate for genetic evaluation in crossbred Holsteins, where records from smallholders could be included.

/pdf/model-comparison-for-genetic-evaluation-of-milk-yield-in-3ilb0iohch.pdf

Model comparison for genetic evaluation of milk yield in crossbred Holsteins in the tropics.

Young stock survival is a trait of crucial importance in cattle breeding as calf mortality leads to economic losses and represents an animal welfare issue. The aim of this study was to estimate genetic parameters and sire breeding values for young stock survival in beef x dairy crossbred calves. Two traits were analysed with a univariate animal model: young stock survival between 1 to 30 days and 31 to 200 days after birth. Breed combinations with Belgian Blue sires outperformed all other sire breeds. The lowest survival rates were found for breed combinations with Jersey dams or Blonde d’Aquitaine sires. The results showed low but significant heritabilities (0.045 to 0.075) for both survival traits. Differences in breeding values between sires ranged from −2.5% to 3.5% and from −5.4% to 4.7% survival from 1 to 30 days and 31 to 200 days, respectively. Based on these findings, we concluded that it is feasible to breed for improved young stock survival in beef x dairy crossbred calves. This will hopefully contribute to increasing the survival rate of the calves and reduce economic losses for the farmers.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/3AF8D47B0F5E11C76EF5B6702D66D3A0/S1751731119002386a.pdf/div-class-title-estimation-of-genetic-parameters-for-young-stock-survival-in-beef-x-dairy-crossbred-calves-div.pdf

J Crettenand

Papers

Models for adjusting for herd, year and season effects in dairy sire evaluation in small herds.