Reaction norm models for the evaluation of reproductive and productive performance in Nellore cattle

This study evaluated genotype × environment interactions (G×E) in Nellore cattle for growth, reproductive, and carcass traits using reaction norm models. We analyzed the records of body weight and scrotal circumference at 12 and 18 months. (W365, W450, SC365, SC450), as well as loin eye area (LEA) and subcutaneous fat thickness (SFT), from herds across different Brazilian states were analyzed. A hierarchical one-step reaction norm model was applied, including fixed effects of contemporary groups (herd, year and season of birth, and sex), cow age at calving as a covariate, and random effects for additive genetics, permanent environment, and residuals. Bayesian inference with Gibbs sampling was used to estimate posterior distributions.Sires were classified according to environmental sensitivity into four categories: extremely robust, robust, plastic, and extremely plastic. For most traits, over 90% of sires were classified as robust or extremely robust, indicating stability of ranking across environments. Exceptions were observed for SFT and SC365, where lower correlations between extreme environmental gradients suggested G×E effects. Heritability estimates ranged from 0.07 to 0.32 for body weights and reached up to 0.76 for fat thickness, with higher values observed under more favorable environmental conditions. .These findings underscore the utility of reaction norm models for identifying environmentally robust sires under the variability of tropical production systems, thereby supporting more accurate and efficient selection decisions in genetic improvement programs.

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Publication Details

Journal
Tropical Animal Health and Production
Published
2026-03-24
DOI
https://doi.org/10.1007/s11250-026-04947-5
Primary Topic
Genetic and phenotypic traits in livestock
Type
article
Field-Weighted Citation Impact
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article

Reaction norm models for the evaluation of reproductive and productive performance in Nellore cattle

Tropical Animal Health and Production
Genetic and phenotypic traits in livestock
article

Reaction norm models for the evaluation of reproductive and productive performance in Nellore cattle

article en

Abstract

This study evaluated genotype × environment interactions (G×E) in Nellore cattle for growth, reproductive, and carcass traits using reaction norm models. We analyzed the records of body weight and scrotal circumference at 12 and 18 months. (W365, W450, SC365, SC450), as well as loin eye area (LEA) and subcutaneous fat thickness (SFT), from herds across different Brazilian states were analyzed. A hierarchical one-step reaction norm model was applied, including fixed effects of contemporary groups (herd, year and season of birth, and sex), cow age at calving as a covariate, and random effects for additive genetics, permanent environment, and residuals. Bayesian inference with Gibbs sampling was used to estimate posterior distributions.Sires were classified according to environmental sensitivity into four categories: extremely robust, robust, plastic, and extremely plastic. For most traits, over 90% of sires were classified as robust or extremely robust, indicating stability of ranking across environments. Exceptions were observed for SFT and SC365, where lower correlations between extreme environmental gradients suggested G×E effects. Heritability estimates ranged from 0.07 to 0.32 for body weights and reached up to 0.76 for fat thickness, with higher values observed under more favorable environmental conditions. .These findings underscore the utility of reaction norm models for identifying environmentally robust sires under the variability of tropical production systems, thereby supporting more accurate and efficient selection decisions in genetic improvement programs.

Tropical Animal Health and ProductionVol. 58(3)
Universidade Federal de Mato Grosso do Sul (BR), Universidade Federal de Mato Grosso (BR), Associação Brasileira de Pesquisadores em História Econômica (BR)
Openalex Percentile: Top 10%
Genetic and phenotypic traits in livestock
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