Comparison of Non-Linear Growth Models for Indigenous Bargur Cattle Calves

This study presents the growth data of indigenous Bargur cattle calves maintained at the Bargur Cattle Research Station, Tamil Nadu, India. Bargur cattle are an endangered breed known for their adaptability to hilly environments and production potential. The dataset included 1803 weight–age records collected from 174 calves, covering measurements from birth (age code 1) to approximately 16 months of age (age code 17). In the research station database, birth weight was recorded as age code 1, with subsequent age codes representing approximately monthly weight records. To describe the growth pattern, five non-linear models, Brody, Logistic, Von Bertalanffy, Gompertz, and Generalized Weibull, were fitted to the data. Key growth parameters, such as asymptotic weight, initial weight, and growth rate were estimated, along with indicators like age and weight at inflection. Because the available records covered growth from birth (age code 1) to approximately 16 months of age (age code 17), asymptotic weight estimates should be interpreted as model-derived projections rather than observed mature body weight. Among the models evaluated, the Von Bertalanffy model showed the best overall statistical fit based on AIC, BIC, and RMSE criteria, followed by the Gompertz model. The Logistic model, although not the best-fitting model statistically, retained biological interpretability in describing early growth patterns in calves. The dataset, along with graphical outputs of growth curves and residuals, provides useful insights into the early growth trajectory of Bargur cattle and may support conservation, management, and future breeding programs.