The aim of this study was to compare models for describing the overall and individual lactation curves in a Florida dairy goat herd to determine which mathematical model would be the better fit.

The automatic milking system (AMS) allows the determination of the individual production of each milking throughout the whole lactation. The original dataset included 104,231 milking records of 206 does obtained by AMS (an average of 505.9 milking per animal, with a mean milk yield of 1.12±0.69 kg per milking). In this study, the analysis of lactation curves was applied to the daily milk production records from kidding to 240 days of lactation (an average of 239 daily records per animal, with a mean daily milk yield of 2.28±1.14 kg).

A total of six functions (Wood, Wilmink, Ali and Schaeffer, Cobby and Le Du, Cappio-Borlino, and cubic splines) were used to model overall and individual lactation curves as a function of days in milk. Environmental factors including the number of lactations, month of kidding, and type of kidding, which significantly affect the lactation curve, were also incorporated into the models.

The goodness of fit of the models was evaluated based on the BIC (Bayesian information criterion). A cubic Spline function provided the best fit and offered an accurate description of the overall curve (followed by the Wilmink and the Wood models). In the case of the individual lactation curve, the Spline model showed the best fitting performance for 62.74% of the total animals (followed by the Wood model at 25% and the Wilmink model at 10.78%). Results from this study will provide insight into a better understanding of the lactation curve of Florida dairy goats and will serve as a tool for better herd management and selection.