Heterogeneity of Variances in Milk Yield in Murrah Buffaloes

Abstract

The aim of this study was to assess the presence of heterogeneity of variance in milk yield in the first lactation of buffaloes and its subsequent influence on the genetic evaluation of Murrah breed sires. The analysis utilized a dataset comprising 2392 milk yield records of buffaloes involved in the Programa de Melhoramento de Búfalos do Brasil. The standard deviation classes were established by standardizing the averages of contemporary group levels, with positive values constituting the high standard deviation class and values equaling or less than zero comprising the low standard deviation class. The linear mixed model incorporated fixed effects of sire group, buffalo age at calving, and heterozygosity as covariates, along with additive genetic random effects. Variance components were estimated via Bayesian inference employing the Gibbs sampler to derive posterior means. The average posterior heritability obtained in analyses without considering heterogeneity of variances (i.e., the "general analysis") was 0.21, while the averages 0.19 and 0.34 were obtained for the low and high standard deviation classes, respectively. The genetic correlation between standard deviation classes was 0.61. The genetic correlation estimates between the predictions of breeding values for milk yield were more closely aligned between the predictions obtained in the general analysis with the low standard deviation class, and more discrepant between the two standard deviation classes. In the animal genetic evaluation model, when heterogeneity of variance is disregarded, the variance components are substantially weighted towards the performance of individuals in the low phenotypic variability class. By disregarding the presence and heterogeneity of variance, the breeding values of the best sires were underestimated.

Keywords: genetic parameters; genotype-environment interaction; milk production; selection.

Figure 1

Breeding values of sires for milk yield regressed on general analysis (VGG) for the low SD (VGB) and high SD (VGA) standard deviation classes, with equations equal to y^ = −0.04474 + 1.14591X (R² = 0.88), for the low standard deviation class.