Bayesian estimation of genetic parameters for growth and carcass traits of grass-fed beef cattle by Full Conjugate Gibbs

Abstract. Growth and carcass data of Angus cattle were used to estimate heritabilities and genetic and environmental correlations between growth and carcass traits by means of a Bayesian data augmentation (DA) algorithm. Records were taken on 739 Angus steers from 31 sires, during 10 years of a designed progeny test. The cattle were entirely fed on grass during their lifelong. Growth traits evaluated were birth (BW), weaning (WW) and 18-month (W18) weights; and carcass traits were the weights of half the carcass (HCW), of hind "pistola" cut (HPW) and of three retail cuts (ECW). The model used for estimation was a multiple trait additive animal model. The prior densities used in the analyses were the multivariate normal for the fixed effects (with very large variances) and for the breeding values, and the inverted Wishart for the additive and environmental covariance matrices. The observed residual vector was augmented with sampled residuals for missing traits. The total number of samples drawn was 200,000. The heritabilities of growth traits increased with age at measure, and those of carcass traits were of sizeable magnitude. Whereas estimates of the genetic correlations were similar to those found in the literature for cattle fed on concentrates, environmental correlations were lower. Additive correlations between growth traits with either the HPW or ECW, were smaller than the correlations between growth characters and HCW.