Estimation of inbreeding effect on conception in Czech Holstein

The influence of calculated inbreeding coefficients on the conception of heifers and cows was analysed by a two-trait binary model for conceived/not conceived after each insemination on 677 234 Czech Holstein cows and heifers with 3 248 299 insemination records as the covariable in a statistical model. The data between 1996 and 2014 were analysed. Various effects and their statistical influence on traits were tested by a generalized linear model. Consequently, genetic parameters were estimated by the Gibbs sampling method and used in predicting breeding values using the best linear unbiased prediction by animal model (BLUP-AM). The mean for the conception rate of cows averaged over lactations was 33.7% and for heifers it reached 53.8%. Average inbreeding coefficient increased from 1% in 1996 to almost 5% by 2013 and was in the range of 0–45%. The rate of inbreeding per generation was 0.20%. Although the effect of inbreeding was statistically significant (P = 0.05) for both traits, the proportion of variability explained by the models was relatively low. Estimated genetic parameters were low for both traits. Coefficient of heritability was 2.00% and 1.30% for cows and heifers, respectively, whereas coefficients of repeatability reached 6.09% and 7.08% for cows and heifers, respectively. The random effect of the permanent environment (PE) reached higher values than the additive genetic variance (G) and explained 5.67% and 4.09% of variability for cows and heifers, respectively. A negative impact of inbreeding on heifer and cow conception was observed, whereby every 10% increase in inbreeding coefficient resulted in a conception decline by 2.23%. Calculated Spearman’s rank correlation coefficient between estimated breeding values considering and not considering the effect of inbreeding was close to one. Presented results indicate that inbreeding has a negligible influence on the breeding values of conception. The results also indicate that it is not necessary to include inbreeding coefficient in the routine breeding value evaluation of conception rate of heifers and cows. On the other hand, monitoring of inbreeding is necessary to avoid an increase of its rate.

Comparative efficiency of different multiple linear regression prediction equations of first lactation 305-day milk yield for sire evaluation in Murrah buffaloes

In this study, first lactation 39059 weekly test-day milk yield records of 961 Murrah buffaloes were used to predict first lactation 305-day milk yield (FL305DMY) by stepwise backward regression method. The best single, two, three and four test day combinations were selected for prediction of FL305DMY based on adjusted R2 and RMSE values. The sires were evaluated for 305-day actual and predicted first lactation milk yield based on derived multiple regression equations using four methods viz. least squares (LSQ), simple regressed least squares (SRLS), best linear unbiased prediction sire model (BLUP-SM) and best linear unbiased prediction animal model (BLUP-AM) methods. The effectiveness of different sire evaluation methods were judged by error variance, coefficient of determination, coefficient of variation and spearman’s rank correlation. The accuracy of prediction of FL305DMY from weekly test day milk yields were observed to be best for TD-7 (48th day) and TD-22 (153rd day) combination with BLUP-AM as the most efficient method for sire evaluation. It was concluded that the FL305DMY can be predicted as early as 153rd day of lactation and further can be used for early genetic evaluation of Murrah sires.

MELHORAMENTO ANIMAL: PREDIÇÃO DE VALORES GENÉTICOS PELO MODELO ANIMAL-BLUP EM BOVINOS DE LEITE, BOVINOS DE CORTE, OVINOS E SUÍNOS

Atualmente, o procedimento padrão de avaliação genética é o BLUP sob modelo animal. O presente trabalho apresenta aspectos práticos relativos à aplicação deste procedimento no melhoramento das principais espécies de animais domésticos. São abordados vários modelos animais e as várias medidas associadas aos valores genéticos preditos e à precisão das predições. Abstract Animal model – BLUP is the standard procedure for animals genetic evaluation. This paper deals with practical aspects concerning the application of this procedure for the improvement of the main species of domestic animals. Several animal models and measures associated to the predicted breeding values and accuracy of predictions are considered.

Preselection of pigs for performance testing

An important aspect of animal improvement is the correct identification of those individuals with superior genetic merit. Testing to accurately assess merit, however, can be a costly component of improvement. In the Group Nucleus there is a substantial number of potential offspring to be tested even within a system where the farrowing and testing is practised continuously throughout the year. In order, therefore, to reduce costs it could be beneficial to accurately predict genetic worth prior to test on either mean parental breeding value or a trait expressed early before test.A Group Nucleus population was modelled by stochastic simulation with selection at two stages The model for the trait(s) selected comprised animal, common environment, herd-year-season and error components. A multivariate animal model BLUP routine was used for the evaluation.