Genetic parameters estimation of growth in Polled Nellore cattle via random regression models
2017
Coutinho de Barros, Isabella | Souza Carneiro, Paulo Luiz | REIS MOTA, Rodrigo | Pinheiro da Silva, Luciano | Martins Filho, Raimundo | Mendes Malhado, Carlos Henrique
Английский. peer reviewed
Показать больше [+] Меньше [-]Английский. In genetic breeding programs, body weight is measured overtime, and is historically the main source of information from animals. Random Regression Models (RRM) have been frequently used in beef cattle evaluations, but can significantly contribute to genetic progress in all species of economic importance. To our knowledge, there are no scientific studies using RRM to evaluate Polled Nellore. We aimed to estimate genetic parameters by using RRM as a way to provide basis for guidelines development of growth of this breed. The models included direct genetic and maternal genetic, permanent environmental and maternal permanent environmental as random, contemporary groups as fixed and cow age at calving as covariate effects. The residual variances were modeled from homogeneous to six heterogeneous classes. The model of orders 4, 2, 2 and 2 for direct additive genetic, maternal additive genetic, maternal permanent environmental and permanent environmental had greater performance according to statistical criteria (smaller AIC and BIC values). Estimates of direct additive genetic increased over time (range 0-5,000 Kg2) and the heritability estimates were up to 0.73 along the growth curve. Maternal heritability estimates were low, with values close to zero. Genetic correlations between ages ranged from moderate (0.60) to high (0.97). Random regression models may be an alternative to describe the changes in body weight variances throughout lifetime.
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