Estimates of genetic parameters for monthly egg production in a commercial female broiler line using random regression models

In the present study, genetic parameters for monthly egg production, collected from weeks 24-55 on 16,200 hens during 9 generations from a pedigreed commercial female broiler line, were estimated using random regression models. With and without age at sexual maturity (ASM) as a covariate, two analyses were fitted to the data for the different models. To identify the best orders of Legendre polynomials, nine different models were compared. On the basis of Bayesian information and Akaike information criteria, a random regression model with second order Legendre polynomial for fixed effect and third order for additive genetic and permanent environmental effects, was chosen as optimal model. Without considering ASM as a covariate, the heritability estimates of monthly egg productions ranged from 0.099 to 0.229. By including ASM in the model, heritabilities for the first and second monthly records decreased by 38.86% (from 0.229 to 0.140) and 51.33% (from 0.150 to 0.073), respectively. Genetic and phenotypic correlations among monthly egg records were high between adjacent periods and decreased as the time interval increased. Genetic correlations between the first monthly records and other periods changed from positive to negative (varying from −0.095 to −0.619) with considering ASM in the model. The effect of age at sexual maturity on the estimates of heritability and genetic correlations for the first month records suggests it is necessary to include ASM in the analysis of egg production to avoid biased estimates. The heritability of the fourth month egg production and its relatively high genetic correlations with all other later ages show that it could be the most appropriate period for selection.