Estimation of genetic parameters for cumulative egg numbers in a broiler dam line by using a random regression model

The random regression model (RRM) methodology was applied to the estimation of genetic parameters for cumulative egg numbers and monthly egg production in a broiler dam line. The data were extracted from records of a commercial dam line in 2001 to 2003. A total of 99,193 records from 6,475 hens and 9,111 pedigreed animals were used in the current study. The variance components were estimated using Gibbs sampling procedure. According to the Bayesian information criterion and Bayes factor, an RRM with Legendre polynomial of 2 orders for hatching groups and additive genetic effects and of 4 orders for permanent environmental effects was chosen as the optimal model for cumulative egg numbers in the broiler dam line. The heritability estimates of the cumulative egg numbers between wk 1 and 40 of production ranged from 0.16 to 0.54, whereas heritability estimates from wk 12 to 20 of production were moderate. The ratios of permanent environmental variance to phenotypic variance were large, indicating that the RRM could produce better estimates of additive genetic effects. The genetic and phenotypic correlations between cumulative egg numbers at different production weeks estimated with the optimal RRM were generally higher when the overlapping weeks were greater. In addition, genetic parameters for monthly egg production could also be obtained by the optimal RRM, and the heritability estimates ranged from 0.03 to 0.18. It was suggested that early selection based on cumulative egg numbers in the first 19 wk of production could effectively improve annual egg production in the broiler dam line.