Comparative assessment of Non-linear models for lactation curve fitting of Saanen goats in Central Mexico

The lactation curve is a key tool for understanding milk production dynamics in dairy goats and other mammals, supporting decisions related to management, genetic selection, and nutritional planning. This study evaluates the performance of five non-linear models: Wood, Brody, Wilmink, Dijkstra, and Cobby Le Du; in fitting lactation curves using data from 530 lactations of Saanen goats raised under an intensive production system in Mexico. Model selection was based on the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). According to these criteria, the Dijkstra, Wilmink, and Wood models provided the best fit. In conclusion, these three models are the most suitable for describing the lactation curve of Saanen goats in intensive systems in Mexico. The implications of these findings for dairy goat management and future research are also discussed.