Estimate of genetic components of birth weight using multi-breed models with pedigree structures in mestizo sheep

Autores

DOI:

https://doi.org/10.18188/sap.v20i2.26991

Resumo


The objectives of this paper were to verify the influence of the multi-breed model and pedigree structure in the estimates of the genetic components to birth weight in a mestizo herd. Using 1234 birth weight records in two ways, one dataset with complete pedigree information (n = 1028) and another with incomplete pedigree information (n = 1234). The pedigree was composed for 10 sires, 366 and 448 dams for complete and incomplete pedigree, respectively. Used for analysis the maximum restricted likelihood method about the animal model, considering the birth weight trait, for a dataset with or not complete pedigree. The direct heritability coefficients in both datasets did not present large difference, 0.06 and 0.09 to best models in the complete and incomplete pedigree, respectively. However, in the incomplete pedigree, the maternal heritability was 0.29. The residual variance, which on the best model of the dataset with complete pedigree presented 0.51 and 0.35 for the best model of the dataset with incomplete pedigree. In conclusion, there was an influence of de multi-breed model only in the dataset with complete pedigree, being the best model that considered the direct and breed effects. In the dataset with incomplete pedigree, the better model was that considered the direct and maternal additive effects. In both datasets, the modeling of contemporary groups as fixed effect presented the best estimates of genetics components to birth weight in this mestizo flock.

Downloads

Publicado

30-06-2021

Como Citar

AMARILHO-SILVEIRA, F.; JOSÉ LAURINO DIONELLO, N.; WILLIAN CANAZA-CAYO, A. Estimate of genetic components of birth weight using multi-breed models with pedigree structures in mestizo sheep. Scientia Agraria Paranaensis, [S. l.], v. 20, n. 2, p. 143–149, 2021. DOI: 10.18188/sap.v20i2.26991. Disponível em: https://e-revista.unioeste.br/index.php/scientiaagraria/article/view/26991. Acesso em: 28 nov. 2021.

Edição

Seção

Artigos Científicos