Modeling lactation curves for milk production, fat and protein, and evaluation of factors that affect them in Holstein cattle in Mexico

Abstract

The knowledge and modeling of lactation curves make it possible to identify factors that help explain environmental and genetic variations that allow the implementation of a selection program. This work aimed to evaluate different models for milk production, fat, and protein curves in Holstein cattle in Mexico and some factors that affect them. The information used was from 125,982 lactations belonging to 68,804 animals born from 2000 to 2020. The effect of calving number, season of the year, and herd was evaluated. R’s Lactcurves package was employed to fit the 38 models included in the package, of which the best four (Wood, Wilmink, Ali & Schaeffer, and modified Pollot) were chosen and then used to model the individual curves through a nonlinear regression model. The parameters calculated for each model were statistically different among the number of lactations (P<0.05), as well as the number of calving, calving season, and herd (P<0.01). The modeled curves have similar shapes to those reported in other studies, except those obtained for protein in the third and fourth or more calvings with the modified Pollot model. The equation proposed by Wilmink was the one that presented the best fit for the study population according to the different evaluation criteria. Using the model that best suits the data will give a closer predictions to reality, and it can be applied to different areas, such as genetic improvement.