Comparison of growth curves by growth models in slow-growing chicken genotypes raised the organic system.
Hasan Eleroğlu, Arda Yıldırım, Ahmet Şekeroǧlu, F. Nafi Çoksöyler, Mustafa Duman
Abstract
Hasan Eleroğlu, Arda Yıldırım, Ahmet Şekeroǧlu, F. Nafi Çoksöyler, Mustafa Duman
Abstract
Two hundred and forty slow–growing chickens consisting of equal numbers of Hubbard S757 (S757) and Hubbard Grey Barred JA (GB–JA) strains were utilized for the investigation in organics system and were used to estimate growth curve in Gompertz and Logistic model. The asymptotic weights for GB–JA and S757 genotype female; male in the Gompertz model were estimated 3725.34 g; 6109.60 g and 4876.10 g; 6496.47 g and same parameter were found in Logistic model 2133.33 g; 2906.35 g and 2790.37 g; 3635.00 g respectively. The Gompertz model was higher estimate than Logistic model for the asymptotic weights parameter. The instantaneous growth rate for GB–JA and S757 genotype female; male in the Gompertz model were estimated 0.1424; 0.1288 and 0.1525; 0.1495 and same parameter values were found in Logistic model 0.3753; 0.3734 and 0.3873; 0.3949 respectively. Significant difference was observed for the instantaneous growth rate parameter between GB–JA and S757 genotypes in each of models. According to the results of goodness of fit in Gompertz and Logistic growth curve models, the coefficient of determination (R) and adjusted coefficient of determination (adj.R) were detected above 0.996 in boot models for two genotype broilers. The highest value of R and adj.R were obtained from the Logistic model in GB–JA. The two models were all fitted the growth curves of slow–growing chicken genotypes in organic system very well, and the fitting degrees R were all above 0.998; for the two models; however Logistic model was the best (0.999%). © 2014 Friends Science Publishers
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Two hundred and forty slow–growing chickens consisting of equal numbers of Hubbard S757 (S757) and Hubbard Grey Barred JA (GB–JA) strains were utilized for the investigation in organics system and were used to estimate growth curve in Gompertz and Logistic model. The asymptotic weights for GB–JA and S757 genotype female; male in the Gompertz model were estimated 3725.34 g; 6109.60 g and 4876.10 g; 6496.47 g and same parameter were found in Logistic model 2133.33 g; 2906.35 g and 2790.37 g; 3635.00 g respectively. The Gompertz model was higher estimate than Logistic model for the asymptotic weights parameter. The instantaneous growth rate for GB–JA and S757 genotype female; male in the Gompertz model were estimated 0.1424; 0.1288 and 0.1525; 0.1495 and same parameter values were found in Logistic model 0.3753; 0.3734 and 0.3873; 0.3949 respectively. Significant difference was observed for the instantaneous growth rate parameter between GB–JA and S757 genotypes in each of models. According to the results of goodness of fit in Gompertz and Logistic growth curve models, the coefficient of determination (R) and adjusted coefficient of determination (adj.R) were detected above 0.996 in boot models for two genotype broilers. The highest value of R and adj.R were obtained from the Logistic model in GB–JA. The two models were all fitted the growth curves of slow–growing chicken genotypes in organic system very well, and the fitting degrees R were all above 0.998; for the two models; however Logistic model was the best (0.999%). © 2014 Friends Science Publishers
Key concepts: Gompertz function, Logistic function, Logistic regression, Growth curve (statistics), Biology, Goodness of fit, Statistics, Growth rate