Avaliação genética de uma população multirracial Angus-Nelore

• Autor(a) principal: Prestes, Alan Miranda
• Data de Publicação: 2017
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Manancial - Repositório Digital da UFSM
• Texto Completo: http://repositorio.ufsm.br/handle/1/11335
• topic: Bovinos de corte; Ganho médio diário; Heterocedasticidade; Average daily gain; Beef cattle; Heteroscedasticity; CNPQ::CIENCIAS AGRARIAS::ZOOTECNIA

The objective of this study was to evaluate the best model for the genetic evaluation for the trait average daily gain of weaning to post weaning (ADGWP), of a multiple-breed Nellore and Angus population, comprised of 49.634 animals sired by 34.006 dams and 793 sire, born between 1986 and 2015. The genetic evaluation for this population was performed through the methodology of Bayesian inference with the animal model and the criteria of choice were the Number of Parameters (Np), Deviance Information (DIC) and the conditional predictive ordinate (CPO). In the first chapter three models were tested: Traditional Animal Model (TAM), Multiple-Breed Animal Model With (MBAMW) and without segregation (MBAMWS). Based on the selection criteria, the MBAMW was chosen because it presents better adjustments, besides presenting the smallest number of parameters, thus reducing the computational demand. In the second chapter, heteroscedastic multiple-breed models (HMBM) were tested. A 2×2 factorial scheme of two residual variance models (homoscedastic (HO) or heteroscedastic (HE)) was used based on two distributive assumptions (Gaussian (G) and Student’s t (T)). The HMBM-T-HE presented the best fit for the population in question. The Spearman's ordering correlations of the breeding values predicted for the sires were high when all animals were considered (0.93 to 0.99). However, when these sires were separated in TOP (10%) these correlations were reduced drastically (from 0.05 to 0.96). These results support the implementation of robust multibreed models that account for sources of heteroscedasticity to increase the accuracy of genetic assessments of multiple-breed populations.