The aim of this study was to evaluate by simulation the accuracy of the prediction of the breeding value according to the heritability of the trait and the number of progenies. Populations were simulated with six progenies for males (n = 15, 30, 50, 75, 100 and 150) and three for females (n = 1, 2 and 3) and characteristics with three heritability (h2 = 0.098, 0.22 and 0.56). The prediction of the breeding values was calculated by the method of the best unbiased linear predictor and the accuracy was calculated from the diagonal of the matrix of the mixed model equation. It was found that the higher heritability the accuracy was also higher in all scenarios. Regarding the number of progenies per male, accuracy values above 0.9 were obtained when the progeny was greater than 30. In the case of females, the highest accuracies were 0.56 for heritability with values of 0.71, 0.74 and 0.76 for...

The aim of this study was to estimate genetic parameters for birth and weaning weight in guinea pigs (Cavia porcellus) reared in a farm in Cieneguilla, Lima, Peru. Univariate animal model that included sex of calf, parity, season of birth, animal and litter effect was used in the genetic analyses. In addition, the effect of number of newborns was included in the model for birth weight, and the number of born alive and age at weaning were included in the model for weaning weight. Variance components were estimated by Bayesian Gibbs sampling with a chain of100 000 rounds with the first 10 000 rounds discarded for burn-in by using MCMCglmm library of R software. Heritability estimates for birth weight was 0.155 ± 0.036 and for weaning weight was 0.246 ± 0.046. These values were similar to those estimated by using REML.

The aim of this study was to estimate genetic parameters for birth and weaning weight in guinea pigs (Cavia porcellus) reared in a farm in Cieneguilla, Lima, Peru. Univariate animal model that included sex of calf, parity, season of birth, animal and litter effect was used in the genetic analyses. In addition, the effect of number of newborns was included in the model for birth weight, and the number of born alive and age at weaning were included in the model for weaning weight. Variance components were estimated by Bayesian Gibbs sampling with a chain of100 000 rounds with the first 10 000 rounds discarded for burn-in by using MCMCglmm library of R software. Heritability estimates for birth weight was 0.155 ± 0.036 and for weaning weight was 0.246 ± 0.046. These values were similar to those estimated by using REML.