Abstract

Heterogeneity of variance in Brazilian herd environments was studied using first-lactation 305-day mature equivalent (ME) milk and fat records of Holstein cows. Herds were divided into two categories, according to low or high herd-year phenotypic standard deviation for ME milk (HYSD). There were 330 sires with daughter records in both HYSD categories. Components of (co)variance, heritability, and genetic correlations for milk and fat yields were estimated using a sire model from bivariate analyses with a restricted maximum likelihood (REML) derivative-free algorithm. Sire and residual variances for milk yield in low HYSD herds were 79 and 57% of those obtained in high HYSD herd. For fat yield they were 67 and 60%, respectively. Heritabilities for milk and fat yields in low HYSD herds were larger (0.30 and 0.22) than in high HYSD herds (0.23 and 0.20). Genetic correlation between expression in low and high HYSD herds was 0.997 for milk yield and 0.985 for fat yield. Expected correlated response in low HYSD herds based on sires selected on half-sister information from high HYSD was 0.89 kg/kg for milk and 0.80 kg/kg for fat yield. Genetic evaluations in Brazil need to account for heterogeneity of variances to increase the accuracy of evaluations and the selection efficiency for milk and fat yields of Holstein cows. Selection response will be lower in low variance herds than in high variance herds because of reduced differences in daughter response and among breeding values of sires in low HYSD herds. Genetic investments in sire selection to improve production are more likely to be successful in high HYSD herds than in low HYSD Brazilian herds.

Highlights

  • One major component in designing breeding programs is accurate assessment of breeding values

  • If favorable conditions are associated with larger sire variances in high than in low herd-year phenotypic standard deviation for ME milk (HYSD) herds, economic returns from genetic investments on imported semen to improve production are more likely to be successful in high HYSD herds than in low HYSD Brazilian herd environments

  • This study clearly revealed differences in variance components between low and high HYSD herd environments in Brazil

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Summary

Introduction

One major component in designing breeding programs is accurate assessment of breeding values. Appropriate modeling of genetic evaluations should take into account potential changes in rank, magnitude of breeding values and genetic gains across environments, which would be an indication of genotype and environment (G x E) interaction. In addition to differences in heritabilities and residual variances, genetic correlation between environments is an important parameter to consider in selection strategies to maximize genetic response in different environments (Van Vleck, 1987). Interaction between genotype and environment is defined as a change in the relative phenotypic expression of genotypes measured in different environments. Falconer (1952) proposed to utilize genetic correlation to describe G x E interaction by defining the same measure in two environments as distinct characters. Interaction of G x E may involve changes in rank between environments or relative changes in the magnitude of variances between environments

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