Estimation of genetic parameters for body weight traits in Mazandaran native breeder hens by random regression models

Abstract

The primary concern of this study is to investigate appropriate random regression model for estimate genetic parameters body weight at hatch (BW1), eight (BW8), twelve (BW12) and thirty two (BW32) weeks of ages by the restricted maximum likelihood method. The body weight records set included 39872 during 16 generations of hens kept at the Mazandaran Breeding Center of Iran. Random regression were modelled using generation-hatch as a fixed effect and additive genetic and permanent environmental effects as random effects Residual variances were modeled through a step function with 1 and 3 classes. The model was considered to be the most appropriate with the highest significant log likelihood ratio test (LRT) and the lowest Akaike information criterion (AIC) and Bayesian information criterion (BIC). Heritability values increased from 0.21 for BW1, to 0.40 for BW32. Genetic correlations of body weight at different record keeping were often higher than permanent environmental correlations. Genetic correlations between pairs of body weight measures were moderate to high with a range from 0.25 to 0.97. The largest genetic correlation, as well as permanent environmental correlation, was observed between BW12and BW32. High and moderate broad sense heritability values for all studied traits shows that these traits are less influenced by residual effects which make them effectively transmitted to the progeny. Findings show that genetic improvement for body weight can be achieved by selection. The Heritability of body weight at thirty two weeks of ages and its relatively high genetic correlation with all other ages showed that it could be the most appropriate period for selection. Also, the genetic trend estimates for body weight traits showed that selection decisions made during the breeding program effectively improved the growth performance.