Evaluation of growth curve for South African non-descript indigenous goats using non-linear models

Abstract

ABSTRACT Six non-linear regression models (3P and 4P Gompertz, 3P, 4P and 5P Logistic and Neural network) were computed to construct the growth curves of 50 South African non-descript indigenous goats (males = 20 and female = 30) from birth to twelve months of age, raised at the University of Limpopo Experimental Farm, South Africa. Candidate non-linear models were compared for the best predictive values based on the adjusted coefficient of determination (AdjR 2), root mean square error (RMSE), Akaike’s information criterion (AIC) and Bayesian information criterion (BIC). The results suggest that South African non-descript indigenous goats’ growth curve was best reconstructed in males using Logistic 4P, while Logistic 5P for the females. The growth parameters obtained from the current study might be used to define the feeding programmes to meet nutritional needs of South African non-descript indigenous goats from birth to one year of age.