Estimation of genetic parameters for carcass traits in Japanese quail using Bayesian methods

The aim of this study was to estimate genetic parameters of some carcass characteristics in the Japanese quail. For this aim, carcass weight (Cw), breast weight (Bw), leg weight (Lw), abdominal fat weight (AFw), carcass yield (CP), breast percentage (BP), leg percentage (LP) and abdominal fat percentage (AFP) were measured on approximately 500 quails (offspring of 60 sires and 180 dams). Gibbs sampling (GS) under a multi-trait animal model was applied to estimate heritability and genetic correlations. Genetic analyses were performed using MTGSAM (Multiple Trait Gibbs Sampling) software. Heritability estimates for all the traits were low to moderate. Point estimates (means of marginal posterior densities) of heritabilities for Cw, Bw, Lw, AFw and CP, BP, LP, AFP were 0.42, 0.36, 0.34, 0.40 and 0.11, 0.18, 0.12, 0.29, respectively. Genetic correlations between the carcass parts (Cw, Bw, Lw, AFw) were high and positive, ranging from 0.65 to 0.87. Direct selection for total carcass weight would increase its component traits. There were moderate to high negative genetic relationships between AFP and LP (-0.27), AFP and BP (-0.34), and AFP and CP (-0.89). Therefore, a decreasing AFP in quail could be reached by direct selection for higher CP

Establishment of optimum regression models and determination of relationships between body measurements and slaughter traits in Japanese quails by path analysis

Path analysis was used to investigate direct, indirect and total effects of some morphological measurements on slaughter and carcass traits in Japanese quails. Bodyweight, shank length, shank diameter, breast circumference and body length measurements were taken from 219 Japanese quails. Bivariate correlations between carcass weight and morphological traits in quails ranged from 0.405 to 0.864. The direct effect of bodyweight on carcass weight was the strongest in the study and (path coefficient of 0.85) positively influenced carcass weight (P 0.05). These traits were indirectly realised mostly by shank diameter. Thus, they were dropped from the final regression equations to obtain much more simplified prediction models. The optimum multiple regression equation for Japanese quails included bodyweight, with coefficient of determination (R2) of 0.7463. The correlation between characters was determined in more detail by using path analysis in this study. Thus, it was shown that path analysis could be used for selecting a variable. The forecast indices obtained in this study could aid in weight estimation, selection and breeding programs. © 2015 CSIRO

Bayesian Analysis for the Comparison of Nonlinear Regression Model Parameters: an Application to the Growth of Japanese Quail

ABSTRACT This paper discusses the Bayesian approach as an alternative to the classical analysis of nonlinear models for growth curve data in Japanese quail. A Bayesian nonlinear modeling method is introduced and compared with the classical nonlinear least squares (NLS) method using three non-linear models that are widely used in modeling the growth data of poultry. The Gompertz, Richards and Logistic models were fitted to 499 Japanese quail weekly averaged body weight data. Normal prior was assumed for all growth curve parameters of the models with assuming Jeffreys' non-informative prior for residual variances. Models were compared based on the Bayesian measure of fit, deviance information criterion (DIC), and our results indicated the better fit of Gompertz and Richards models than the Logistic model to our data. Moreover, the parameter estimates of the models fitted by both approaches showed only small differences

Bayesian Analysis for the Comparison of Nonlinear Regression Model Parameters: an Application to the Growth of Japanese Quail

ABSTRACT This paper discusses the Bayesian approach as an alternative to the classical analysis of nonlinear models for growth curve data in Japanese quail. A Bayesian nonlinear modeling method is introduced and compared with the classical nonlinear least squares (NLS) method using three non-linear models that are widely used in modeling the growth data of poultry. The Gompertz, Richards and Logistic models were fitted to 499 Japanese quail weekly averaged body weight data. Normal prior was assumed for all growth curve parameters of the models with assuming Jeffreys' non-informative prior for residual variances. Models were compared based on the Bayesian measure of fit, deviance information criterion (DIC), and our results indicated the better fit of Gompertz and Richards models than the Logistic model to our data. Moreover, the parameter estimates of the models fitted by both approaches showed only small differences

Single-trait bayesian analysis of some growth traits in japanese quail

The aim of this study was to estimate the heritability for some growth traits of Japanese quail through the estimation of variance components by Bayesian methodology. For this purpose, 340 progenies of 34 sires were used. Live weight (LW42) and absolute and relative growth rates at 42 days of age (AGR42 and RGR42, respectively) were submitted to single-trait analysis under a sire model. A software (package MCMCglmm) was used for the estimations, and a single chain with 65,000 rounds was run for each trait with a thinning interval of 50. Burn-in was set at 15,000 and inferences were built on posterior samples of 1,000 draws for each trait. All marginal posterior densities were unimodal and marginal posterior distributions of sire variance are slightly skewed to the right. The results of the analyses showed high, moderate, and low heritability of LW42, AGR42, and RGR42, respectively