Genetic parameters for egg production traits in crosses between local and exotic chickens estimated by Bayesian inference

Résumé

Estimates of genetic parameters for economic traits are important to enable the breeder estimate the breeding value of individuals available for selection. Thus, this study was carried out to estimate genetic parameters namely heritability and genetic correlations among egg production traits in two strain crosses using bivariate animal model in Bayesian (MCMC) method. The egg production data were obtained from four generations which comprised the base population of two commercial egg strains and the local chicken, the inbred population derived from the base population, the F1 crossbred population obtained from the crossing of the local and exotic inbred chickens and the backcross population obtained from the backcrossing of the crossbred to their parents. A total number of 1,138 daughters of 62 sires and 620 dams were used for the study. The autocorrelations among samples in the MCMC chain were less than 0.1 for all lag values indicating that all samples of the posterior distribution were independent. The estimated heritability for age at first egg, body weight at first egg, hen day egg number, weight of first egg, egg weight at thirty week and egg weight at forty week were 0.62, 0.48, 0.47, 0.53, 0.54 and 0.56 for strain 1 crosses and 0.43, 0.48, 0.49, 0.52, 0.52 and 0.53 for strain 2 crosses. The corresponding highest posterior density interval ranged from 0.22 to 0.91 for strain 1 crosses and 0.07 to 0.83 for strain 2 crosses. The genetic correlations among egg production traits ranged from 0.06 to 1.97 in strain 1 and 0.06 to 2.59 in strain 2 crosses. The estimates were within the range reported in literature for egg production traits in chicken and imply that appreciable amount of additive genes exist in the strain crosses which could be used for the selection of superior birds. The magnitude of genetic correlations implies that selection of one trait could lead to correlated response to the other traits.