Development of growth curve and estimation of genetic parameters of Nili-Ravi buffalo calves from birth to one year of age through non-linear models.

The current study aimed to construct the growth curve and find the best-fitting non-linear model for the Nili-Ravi buffalo calves. The pedigree and monthly body weight data for 6644 calves born between 2010 and 2020 (inclusive) in six herds, maintained in different geographical regions of Punjab were collected. The study was performed under a longitudinal design and various non-linear models were used to associate the age with weight by using the easyreg package in R studio. Finally, the genetic parameters of growth curve were estimated through the bi-variate sire model in ASReml (v4.2). The model with the highest value of coefficient of determination and the lowest values of Akaike's information criterion, Bayesian information criterion, and root-mean-square error was considered as the best fit for defining the growth curve. The Brody model was found as the best fitted model with the values of 0.6648, 627871.80, 627908.10, and 30.793 for the R²adj, AIC, BIC, & RMSE respectively, for the combined dataset. The values of growth curve parameters for the Brody model were 943.99 ± 101.38Kg (A), 0.96 ± 0.004Kg (B), and 0.0005 ± 0.00Kg (K) for all animals. A higher K-value of females indicates their early maturity compared with male animals in this breed. The heritability estimates for the growth curve traits were low, while the values of genetic correlations were higher than those of phenotypic correlations. The data revealed that Asymptotic weight (A) and birth weight (B) were positively correlated with each other, while the rate of maturity (K) was negatively correlated with initial and final body weights.