Genetic parameters of weekly egg production using random regression models in two strains of Japanese quails

The main objective of the present study was to detect the most appropriate random regression model for estimating the genetic parameters of weekly egg production. Two strains of Japanese quails including wild and white quails and pure and cross mating methods were considered. The egg collection started at the seventh week of age and lasted for 7 weeks. A random regression model using Legendre polynomial was used to analyze the weekly egg records. The model with Legendre polynomial of order 1 for the additive genetic and order 3 for permanent environmental effect was chosen as the appropriate model, based on Bayesian information criterion (BIC) and Akaike information criterion (AIC). The heritability estimates for weekly egg production were low (ranging from 0.06 to 0.09). Furthermore, the ratios of permanent environmental variance to the phenotypic variance were almost moderate, varying from 0.18 to 0.44. Genetic and phenotypic correlations between weekly egg records ranged from 0.65 to 0.93 and from 0.27 to 0.67, respectively. These results indicated that the selection based on the early egg numbers could effectively improve egg production in later periods. Furthermore, the efficiency of egg production can be enhanced with a combination of breeding programs and management strategies.