<b>Heterogeneity and genetic evaluation in bovines, a study using simulated data</b> - DOI: 10.4025/actascianimsci.v30i1.3621

Abstract

In order to study the effects of heterogeneity on bovine genetic evaluation, several structures of data were simulated with heterogeneity for different parameters, with and without genetic connexity among herds. The Genesys software was used to generate the data and the MTDFREML metodology was employed to analyze this data. The lowest values of the rank correlations (Spearman correlation) were obtained for the data structure of herds with heterogeneity for all parameters. For the structures of data with similar genetic means and heterogeneity for others parameters, the correlations between breeding values were greater than 70% and near those obtained for data without heterogeneity, which indicates that the heterogeneity for variances and phenotypic mean has little effect on genetic evaluation. The high genetic connexity of data improved the prediction of breeding values of bulls, but this effect was not noted for progenies and, mainly, the genetic evaluation of cows. The rank correlations based on predictions from single and multiple traits analysis were very similar, indicating that the multiple trait analysis was not efficient in eliminating the problems of genetic means heterogeneity.