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Ability of non-linear mixed models to predict growth in laying hens R. Bras. Zootec.
Galeano-Vasco,Luis Fernando; Cerón-Muñoz,Mario Fernando; Narváez-Solarte,William.
In this study, the Von Bertalanffy, Richards, Gompertz, Brody, and Logistics non-linear mixed regression models were compared for their ability to estimate the growth curve in commercial laying hens. Data were obtained from 100 Lohmann LSL layers. The animals were identified and then weighed weekly from day 20 after hatch until they were 553 days of age. All the nonlinear models used were transformed into mixed models by the inclusion of random parameters. Accuracy of the models was determined by the Akaike and Bayesian information criteria (AIC and BIC, respectively), and the correlation values. According to AIC, BIC, and correlation values, the best fit for modeling the growth curve of the birds was obtained with Gompertz, followed by Richards, and then...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Chickens; Mathematical models; Poultry; Regression analysis; Weight gain.
Ano: 2014 URL:
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