Reaction norms models in the adjusted weight at 550 days of age for Polled Nellore cattle in Northeast Brazil
AUTOR(ES)
Ambrosini, Diego Pagung, Carneiro, Paulo Luiz Souza, Braccini Neto, José, Martins Filho, Raimundo, Amaral, Rosimira dos Santos, Cardoso, Fernando Flores, Malhado, Carlos Henrique Mendes
FONTE
R. Bras. Zootec.
DATA DE PUBLICAÇÃO
2014-07
RESUMO
The objective of this study was to evaluate the genotype-environment interaction (GEI) in the body weight adjusted to 550 days of age (W550) of Polled Nellore cattle raised in Northeastern Brazil using reaction norms (RN) models. Hierarchical RN models included fixed effects for age of cow (linear and quadratic) and random effects for contemporary groups (CG) and additive genetic RN level and slope. Four RN hierarchical models (RNHM) were used. The RNHM2S uses the solutions of contemporary groups estimated by the standard animal model (AM) and considers them as environmental level for predicting the reaction norms and the RNHM1S, which jointly estimate these two sets of unknowns. Two versions were considered for both models, one with a homogeneous (Hm) and another with a heterogeneous (He) residual variance. The one-step homogeneous residual variance model (RNHM1SHm) offered better adjustment to the data when compared with other models. For the RNHM1SHm model, estimates of additive genetic variance and heritability increased with environment improvement (260.75±75.80 kg2 to 4298.39±356.56 kg2 and 0.22±0.05 to 0.82±0.01, for low- and high-performance environments, respectively). High correlation (0.97±0.01) between the intercept and the slope of RN shows that animals with higher genetic values respond better to environment improvement. In the evaluation of breeding sires with higher genetic values in the various environments using Spearman's correlation, values between 0 and 0.98 were observed, pointing to high reclassification, especially among genetic values obtained by the animal model in comparison with those obtained via RNHM1SHm. The existence of GEI is confirmed, and so is the need for specific evaluations for low, medium and high level production environments.
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