Non-Linear Regression Curve Fitting of Time-Dependent Growth Performance of Cobb500 Broiler

The aim of this study was to evaluate the performance of three different mathematical models (Gompertz, Von Bertalanffy, and Logistic) in predicting the growth of broiler chickens. The coefficients for each model were estimated using the MS solver, and the results were compared to values reported in previous studies. The body weight of the broilers was found to not show parallelism based on sex profile, with differences in weight observed starting from the 21st day of breeding. The Gompertz model was found to give the best prediction of the average body weight of male and female broilers, with a high correlation coefficient and model efficiency. These findings suggest that the Gompertz model is a good fit for predicting the growth of broiler chickens and that sex-specific growth patterns should be considered in future studies.