Multi trait genetic evaluation of growth traits in Nellore sheep raised on pasture in semi-arid regions of India using Bayesian approach

Abstract

Abstract The main aim of this study is to estimate genetic parameters and (co) variance components for body weights at various ages in Nellore sheep born during the period from 1993 to 2016 (23 years). A total of 4822 lambs with pedigree descended from 144 sires and 1299 dams were included in this study. Bayesian analysis using Gibbs sampler multi trait animal model with and without maternal effects was studied. Traits included in this study were birth weight (BW), weaning weight (WW), six months body weight (6MW), nine months body weight (9 MW), Yearling weight (YW). Year-season of birth and sex of lamb (contemporary groups) were considered as fixed effects with ewe weight at lambing as a covariate. Estimates of direct heritability estimates for birth weight, WW, 6MW, 9MW and YW based on best model were 0.17, 0.28, 0.27, 26 and 0.23, respectively and the corresponding maternal heritability estimates were 0.12, 0.14, 0.14, 0.12 and 0.13, respectively. The direct-maternal genetic covariance was negative for all the studied traits. Strong and positive estimates of direct additive genetic correlations were observed in growth traits and they ranged from 0.16 to 0.83, whereas the direct-maternal genetic correlations were negative for all the traits and these estimates ranged from ˗0.89 to ˗0.08. Moderate estimates of heritability for the growth traits obtained in this study suggested the presence of better genetic variability and the possibility for genetic improvement of Nellore sheep through selection. Maternal genetic effects were significant in all the traits. Hence, it is recommended to incorporate these effects in the genetic analysis by including it as a genetic or environmental effect or both. The environmental variance obtained in the study suggested that the growth performance of Nellore sheep may be enhanced by improving the feeding and management aspects. Correlations among traits and effects should be considered while implementing breed improvement program.