Random Regression Models on Genetic Parameters of Meat-Type Quails Raised With Different Threonine Levels.

Abstract

We aimed to evaluate the inclusion of fixed effects and residual variance classes in random regression models in the estimation of genetic parameters for ICA1 and ICA2 meat-type quails at 21 and 35 days of age raised with five levels of threonine (1.14%, 1.24%, 1.34%, 1.44%, and 1.54%). We used 920 body weight records from three incubations and a pedigree comprising 5407 animals from five generations. The effects of sex, incubation, sex by incubation interaction, and birth weight were tested using a multivariate analysis of variance. We compared five models considering residual variance classes according to threonine levels: homogeneous, with a single class (1.14%-1.54%), and heterogeneous models with two classes (1.14%-1.34% and 1.44%-1.54%), three classes (1.14%-1.24%, 1.34%, and 1.44%-1.54%), four classes (1.14%, 1.24%, 1.34%, and 1.44%-1.54%), and five classes (1.14%, 1.24%, 1.34%, 1.44%, and 1.54%). The effects of sex, incubation, and linear birth weight were significant. There was no significant difference in Log(L) among any of the models according to the likelihood ratio test (LRT). The homogeneous model provided the best fit for ICA1 and ICA2 according to the Bayesian Information Criterion (BIC).