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| Karaman,E; Firat,MZ; Narinc,D. |
| 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... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Absolute growth rate; Bayesian; Heritability; Quail; Relative growth rate. |
| Ano: 2014 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-635X2014000200007 |
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| Firat,MZ; Karaman,E; Başar,EK; Narinc,D. |
| 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... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Gompertz; Logistic; Richards; Non-linear; Bayesian. |
| Ano: 2016 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-635X2016000500019 |
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