ASSESSMENT OF GROWTH PATTERN IN INDIGENOUS KADAKNATH CHICKENS BY NON-LINEAR MODELS

Mathematical growth functions can explain the factors influencing an animal's growth pattern. However, there remains limited understanding of the growth curve of Kadaknath chickens, which is crucial for optimizing management and feeding practices. Therefore, this study aimed to determine the gr...

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Veröffentlicht in:Journal of animal and plant sciences 2024-08, Vol.34 (4), p.1012-1019
1. Verfasser: Gautam, L
Format: Artikel
Sprache:eng
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Zusammenfassung:Mathematical growth functions can explain the factors influencing an animal's growth pattern. However, there remains limited understanding of the growth curve of Kadaknath chickens, which is crucial for optimizing management and feeding practices. Therefore, this study aimed to determine the growth curve of indigenous Kadaknath chickens' body weight using four growth curve models: Logistic, Gompertz, Von Bertalanffy, and Richard. We analyzed 96 birds for this study. The models were fitted using Curve Expert and Minitab software, and we compared them based on Akaike’s information, Bayesian information, adjusted R2, and RMSE criteria. The research revealed that the Gompertz and Richard models had higher coefficients of determination (R2) and lower RMSE values in both sexes compared to other models. The age at the inflection point was estimated to be between 11 to 17.5 weeks for males and 9 to 11.4 weeks for females. According to the Richard model, adult male birds weighed 2157g, and females weighed 1297g. In the Gompertz model, male birds weighed 2186g, and females weighed 1468g. The inflection weight of birds in the Richard model was estimated to be 797.53g for males and 519.66g for females, while in the Gompertz model, it was 803.67g for males and 510g for females. In conclusion, our study determined that the Gompertz model is a reliable predictor of the body weight of male and female Kadaknath chickens from hatching to adulthood. The Richard model also demonstrated high reliability, albeit slightly behind the Gompertz model in predictive accuracy. Key words: Body weight, growth pattern, Kadaknath, Non-linear models
ISSN:1018-7081
2309-8694
DOI:10.36899/japs.2024.4.078