MULTIPLE-TRAIT GENETIC-ANALYSIS OF UNDERLYING BIOLOGICAL VARIABLES OFPRODUCTION-FUNCTIONS

A Bayesian procedure to analyze performance data from production funct ions is presented. The method implies the consideration of each parame ter of the production function as a different trait. The systematic ef fects and genetic relationship between animals are taken into account in the adjustment of production for each animal. The method weights al l possible sources of information. In this sense, it allows estimation of the parameters of production functions with only one data along th e production cycle and to reduce the influence of outliers. Under anal ysis, marginal posterior distributions of the function parameters, bre eding values, systematic effects and (co)variance components were obta ined using the Gibbs sampling algorithm. The procedure requires the de finition of the joint posterior distribution to be generalized to any production function. From this joint posterior distribution, the full set of posterior conditional distributions needed for the Gibbs sampli ng algorithm can be easily obtained. (C) 1997 Published by Elsevier Sc ience B.V.