An adjustment model of Logistic form to describe the growth pattern of chickens
Shiv Prasad, D.P. Singh
Abstract
Shiv Prasad, D.P. Singh
Abstract
Chicken is one of the fastest growing species of poultry and its growth curve is found to be sigmoIdal in shape similar to other species. There are some nonlinear asymptotic growth models viz. logistic, Gompertz and Richards, which are generally used to estimate the growth pattern of chickens. The logistic curve is symmetrical about its point of int1ection. But, such symmetry is rarely met in growth curves of chickens and, therefore. logistic function [Wt = a/(1 + b exp (−ct)) requires some adjustment in its functional form to describe the growth pattern of chickens. In this study a modified form [Wt = a/(l + b/t + c exp (−dt)) of logistic function is proposed to describe the growth pattern of chickens. In fitting of models to four data sets of average body weights of male and female chickens the mean square errors corresponding to logistc and Gompertz models were 3268.38 and 700.48, 2670.35 and 582.09, 3512.66 and 763.03 and 3036.99 and 945.57 respectively which were reduced to 602.92, 498.00, 452.54 and 564.75 by the proposed model. Therefore, proposed model gave better fit than the logistic and Gompertz models to growth data of male and female chickens.
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Chicken is one of the fastest growing species of poultry and its growth curve is found to be sigmoIdal in shape similar to other species. There are some nonlinear asymptotic growth models viz. logistic, Gompertz and Richards, which are generally used to estimate the growth pattern of chickens. The logistic curve is symmetrical about its point of int1ection. But, such symmetry is rarely met in growth curves of chickens and, therefore. logistic function [Wt = a/(1 + b exp (−ct)) requires some adjustment in its functional form to describe the growth pattern of chickens. In this study a modified form [Wt = a/(l + b/t + c exp (−dt)) of logistic function is proposed to describe the growth pattern of chickens. In fitting of models to four data sets of average body weights of male and female chickens the mean square errors corresponding to logistc and Gompertz models were 3268.38 and 700.48, 2670.35 and 582.09, 3512.66 and 763.03 and 3036.99 and 945.57 respectively which were reduced to 602.92, 498.00, 452.54 and 564.75 by the proposed model. Therefore, proposed model gave better fit than the logistic and Gompertz models to growth data of male and female chickens.
Key concepts: Gompertz function, Logistic function, Sigmoid function, Growth curve (statistics), Logistic regression, Mathematics, Veterinary medicine, Growth model