Comparative Analysis of Parametric Growth Curves in Broiler Hens
DOI:
https://doi.org/10.24925/turjaf.v14i4.982-986.8420Keywords:
Growth curve, Broiler hens, Live weight, Mathematical modeling, SASAbstract
Accurate modelling of growth performance in broiler chickens is essential for improving productivity through optimized breeding, feeding, and management strategies. In this study, weekly body weight (BW) data obtained from fifty broiler chickens over a six week rearing period were used to evaluate the performance of nonlinear and flexible growth models. Sixteen mathematical functions, including widely used nonlinear models such as Gompertz, Logistic, Richards, Brody, and Von Bertalanffy, as well as flexible models based on polynomial and spline functions, were fitted to the mean body weight values. Model performance was assessed using the coefficient of determination (R²), mean square error (MSE), Akaike information criterion (AIC), and Bayesian information criterion (BIC). Among all evaluated models, the Logistic model exhibited the best overall fit across all statistical criteria, indicating a strong ability to describe the growth trajectory of broiler chickens under the conditions of this study. It should be noted that the use of average body weight values may limit the assessment of individual variability among birds, which represents a limitation of the study. Overall, the results highlight the suitability of nonlinear growth models for describing broiler growth patterns and provide a scientific basis for growth monitoring, genetic evaluation, and production planning in broiler production systems.
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