A Bayesian approach to the Japanese Black cattle carcass genetic evaluation

Abstract

Volumes of the routine carcass field data used in the official genetic evaluation for carcass traits in Japanese Black cattle are increasing rapidly. The purposes of this paper are to describe a Bayesian approach via Gibbs sampling (GS) to be used in the Japanese Black carcass genetic evaluation, and in particular using a very large carcass field data, to compare breeding values for sires and dams of animals with records estimated using GS and the conventional empirical best linear unbiased prediction (EBLUP) employing the restricted maximum likelihood (REML) estimates of variance components. The total of six carcass traits evaluated were carcass weight, rib eye area, rib thickness, subcutaneous fat thickness, estimated muscle yield percentage and marbling score. As prior distributions for GS, uniform, normal and independently scaled inverted chi-square distributions with degree of belief and scale parameters of –2 and 0 were used for nuisance parameters, breeding values and variance components, respectively. The posterior means were calculated using every 10th sample from a total of 90 000 samples, after 10 000 samples had been discarded. Moment and rank correlations between breeding values estimated by the GS and the REML-EBLUP were all very close to one, and the coefficients and the intercepts for linear regression of the GS on the REML-EBLUP estimates were substantially one and zero, respectively, showing a very good agreement between breeding value estimation by the GS and the REML-EBLUP.