&lt;b&gt;Influence of genotype-environment interaction on the classification of Nellore bulls in Southern Brazil

Tiago Bresolin,Camila Urbano Braz,Fernanda Cristina Breda,Dionéia Magda Everling,Paulo Roberto Nogara Rorato

doi:10.4025/actascianimsci.v37i2.23602

Abstract

The aim of this study was to assess the occurrence of genotype-environment interaction, as well as its effects on the magnitude of genetic parameters and the classification of Nellore breeding bulls for the trait adjusted weight at 205 days (W205) on Southern Brazil. The components of (co)variance were estimated by Bayesian inference, using a linear-linear animal model in a bi-trait analysis. The proposed model for the analyses considers as random the direct additive genetic and maternal effects and residual effects, and as fixed effects the contemporary groups, sex, season of birth and weighing, and calving age as covariable (linear and quadratic effects). The a posteriori mean estimates of the direct heritabilities for W205 in the three States varied from 0.24 in Parana (PR) to 0.34 in Santa Catarina (SC). The estimates of maternal heritability varied from 0.23 in SC and Rio Grande do Sul (RS) to 0.28 in PR. The a posteriori mean distributions of the genetic correlation varied from 0.52 between SC and RS, to 0.84 between PR and RS, suggesting that the best breeding bulls in SC are not the same as in RS.

Highlights

Beef cattle in Brazil, due to the country’s large territorial extension, is practiced in different environmental conditions, submitting animals to variations in handling conditions during their productive live (Ferraz & Felício, 2010)
Another indicative of the Gibbs chains convergence is associated to the Monte Carlo error (MCE) for the genetic parameters
MCE was low for all the traits, indicating that the size of the chain was enough for obtaining precise estimates of the a posteriori parameters

Summary

Introduction

Beef cattle in Brazil, due to the country’s large territorial extension, is practiced in different environmental conditions, submitting animals to variations in handling conditions during their productive live (Ferraz & Felício, 2010). It is necessary to consider the interaction genotypeenvironment in programs of genetic improvement, since this effect may present biased estimates of genetic variance, leading to changes in selection criteria (Alencar et al, 2005). The genetic improvement programs in progress commonly disregard the presence of the genotypeenvironment interaction and assume constant additive and residual genetic variation for all the Maringá, v. Evidence has been found of the presence of heterogeneous variation and of genotype-environment interaction, when data are obtained from different regions of the country, as well as from different management systems (Espasandin et al, 2011; Faria et al, 2011; Lopes et al, 2008; Zapata et al, 2010)

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Conclusion