Estimation of genetic parameters for weaning and yearling weights in a composite population used to form the Purunã breed

• Autor(a) principal: Otto,Pamela Itajara
• Data de Publicação: 2021
• Outros Autores: Santos,Alexandre Leseur dos, Perotto,Daniel, Oliveira,Sheila Nogueira de, Granzotto,Fernanda, Gobo,Diego Ortunio Rosa, Souza,Felipe Eduardo Zanão de, Thomazini,Guilherme
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista Brasileira de Zootecnia (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982021000100404
• topic: body weight; crossbred cattle; growth traits; maternal effect

ABSTRACT We aimed to evaluate the effects of sex and the linear and quadratic components of age of dam at calving, as well as apply a mixed model including maternal effect for the genetic evaluation of weaning (WW) and yearling (YW) weights. The phenotypic database was composed by Charolais, Caracu, Aberdeen Angus, and Canchim purebred and crossbred animals. Single-trait analyses were performed using models that included the maternal effect for WW and YW traits, and a model ignoring this effect on YW (YWNM). The Deviance Information Criterion (DIC), model posterior probabilities (MPP), accuracy of breeding values (ACC), and Spearman’s rank correlation were applied to compare the models including and ignoring the maternal effect on YW. Sex and age of dam at calving had significant effects on WW and YW. The direct heritability estimates were 0.21±0.03 and 0.05±0.02, and the maternal heritabilities were 0.11±0.02 and 0.02±0.01 for WW and YW, respectively. The heritabilities estimated for YW may have been influenced by the several genetic groups in the population and by used conventional animal model, which may not have been the better fit model to evaluate YW in this population. The DIC, MPP, and ACC values indicated that YW outperformed the YWNM model, but the rank correlation and percentages of individuals selected in common suggested that the best animals would be selected independently of the model chosen.