Comparison of Growth Curves by Growth Models in Slow-Growing Chicken Genotypes Raised the Organic System

ELEROĞLU H., YILDIRIM A., Sekeroglu A., Coksoyler F. N. , Duman M.

INTERNATIONAL JOURNAL OF AGRICULTURE AND BIOLOGY, vol.16, no.3, pp.529-535, 2014 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 16 Issue: 3
  • Publication Date: 2014
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.529-535
  • Van Yüzüncü Yıl University Affiliated: Yes


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-2) and adjusted coefficient of determination (adj. R-2) were detected above 0.996 in boot models for two genotype broilers. The highest value of R-2 and adj. R-2 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-2 were all above 0.998; for the two models; however Logistic model was the best (0.999%). c 2014 Friends Science Publishers