Prediction of growth performance of malabari goats using non-linear models

Abstract

Different non-linear growth models were fitted to predict the best growth model for Malabari goat breed. Data on body weight of 1064 goats from birth to 12 months of age were collected between 2016 and 2018 from field centres of Indian Council of Agricultural Research – All India Coordinated Research Project on Goat Improvement on Malabari, Kerala Veterinary and Animal Sciences University, Kerala. The data of body weights were plotted against age and shape of the curve was examined. Based on shape of the curves, five non-linear growth models viz., Brody model, von Bertalanffy model, Logistic model, Gompertz model and Negative exponential model were fitted to the data. The Gompertz model was the best fit model for Malabari goats with maximum R2 (0.999) and least residual mean square error (0.210), mean absolute error (0.105) and mean absolute percentage error (0.016) followed by Logistic model. Thus, the Gompertz model could be considered as the best fit to describe the growth performance of Malabari goats.