Application of non-linear models in description of growth of dual purpose FUNAAB Alpha chickens

Samuel Olutunde Durosaro, Onaolapo Samuel Jeje, Babatunde Moses Ilori, Oluwaseun Serah Iyasere, Michael Ohiokhuaobo Ozoje


Growth is explained mathematically by models that have parameters with biological interpretations. This study was conducted to compare five non-linear growth models (Gompertz, Brody, Logistics, Von Bertalanffy and Negative exponential) in order to describe growth in the three genotypes (normal feather, naked neck and frizzle feather) of the dual purpose FUNAAB Alpha chickens (n=332). Doesn’t Use Derivative iterative method of nonlinear procedure in SAS was used to estimate the model parameters. Computational difficultly, goodness of fit and residuals of the five models were also evaluated. Negative exponential model predicted the highest mature weight for the three genotypes while Logistics model predicted the highest coefficient of intensity of growth. The fitting of the five models presented no computational difficulty for normal feather chickens while Logistics failed to converge for male, naked neck and frizzle feather chickens. Based on goodness of fit (coefficient of determination, Bayesian information criterion, mean square error and residuals), Gompertz model was observed to have the best fit for normal feather and naked neck chickens while Brody model have the best fit for frizzle feather chickens and Von Bertalanffy for male chickens. From subjective approach (comparison of observed and predicted body weights),  Logistics and Negative exponential models fitted well for normal feather than other models while Negative exponential model was the fittest among the models for naked neck and frizzle feather chickens and Gompertz for female chickens. It can be concluded that choice of appropriate model in description of growth depends on genotype and sex of dual purpose FUNAAB Alpha chickens.


Brody, Goodness of fit, Genotype, Growth, Logistics, Negative exponential

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