Modeling the growth curve of Iranian Shall sheep using non-linear growth models

Abstract

The objective of this study was to describe the growth pattern in Iranian Shall sheep using non-linear models. For this purpose, six non-linear mathematical functions (Brody, Negative exponential, Logistic, Gompertz, Von Bertalanffy and Richards) were used. The data set used in this study were obtained from the Animal Breeding Center of Iran and comprised 57,000 body weight records of lambs which were collected from birth to 400 days of age during 1982–2012. Each model was fitted separately to body weight records of all lambs, male and female lambs using the NLIN and MODEL procedures in SAS. The models were tested for goodness of fit using adjusted multiple coefficient of determination (Radj2), root means square error (RMSE), Durbin–Watson statistic (DW), Akaike's information criterion (AIC) and Bayesian information criterion (BIC). Richards model provided the best fit of growth curve in males, females and all lambs due to the lower values of RMSE, AIC and BIC and generally greater values of Radj2 than other models. The negative exponential model provided the worst fit of growth curve for males, females and all lambs. According to the moderate values of DW obtained from fitting different models of growth curve it was concluded that there was positive autocorrelation between the residuals for all models, but this autocorrelation was more obvious for negative exponential model than the other equations. The negative correlation of −0.99 to −0.49 between a and k parameters obtained from fitting different growth models implied that the animal with smaller mature weight will be maturing faster. Evaluation of different growth models used in this study indicated the potential of the non-linear functions for fitting body weight records of Shall sheep.