Introducing an alternative nonlinear model to characterize the growth curve in ostrich

By applying a sinusoidal function (as a trigonometric model), this study aimed to introduce this function into ostrich weight development research, using ostrich growth data from the literature and comparing it with some routinely used growth models such as monomolecular, Bridges, Janoschek, logistic, Von Bertalanffy, Richards, Schumacher, Morgan, Chanter, and Weibull. During the fitting of nonlinear regression curves, model performance was evaluated and model behavior was examined. Body weight data of the domestic ostriches used in this study were reported in the Blue Mountain Ostrich Nutrition e-bulletin from three different studies (data sets 1 to 3). In all data sets, body weight was measured monthly from one to twelve months of age. The adjusted coefficient of determination, root mean square error, Akaike's information criterion, and Bayesian information criterion were used to evaluate each model's overall goodness-of-fit to different data profiles. Based on the goodness-of-fit criteria, the sinusoidal model was determined to be the most suitable function for fitting the growth curve of ostriches in data sets 1 and 2. However, both monomolecular and logistic models had the worst fit to the growth curve of ostriches in these data sets. For data set 3, the Weibull model provided the best fit of the growth curve of ostriches, but the sinusoidal function had the worst fit. Absolute growth rate (AGR), calculated using the first derivative of the best model with time showed that AGR values ​​increased with age until days 174, 90, and 68 for data sets 1 to 3, respectively, and then decreased. Overall, this study offers implications for advancing research on ostrich production systems and providing insightful information on the application of alternative nonlinear models in modeling ostrich growth.