Evaluation of egg production in layers using random regression models

The objectives of this study were to estimate genetic parameters for egg production over the age trajectory in 3 layer lines, which represent different biotypes for egg production, and to validate the use of breeding values for slope as a measure of persistency to be used in the selection program. Egg production of more than 26,000 layers per line from 6 consecutive generations were analyzed with a random regression model with a within-hatch-nested fifth-order fixed-regression polynomial and linear polynomials for random additive genetic and permanent environmental effects. Daily records were cumulated into biweekly periods. In all lines, a nonzero genetic variance for mean and slope and a positive genetic correlation between mean and slope were estimated. Genetic variance of egg production by 2-wk period was low at the beginning of lay and increased as the birds aged for all 3 lines, which resulted in heritability estimates increasing with age. Breeding values for slope reflected the shape of the egg production curve well and can be used to directly select for persistency of egg production