Probability prediction models to estimate ages at first calving in dual-purpose bovine systems of the Huasteca Alta Veracruzana

The aim of this study was to develop probabilistic prediction models to identify and quantify the weighted impact of various factors influencing the age at first calving (AFC) in a dual-purpose bovine system (DPBS). Data were collected from 977 birth records of cows raised in cattle production units in the Huasteca Alta Veracruzana region of Mexico, along with rainfall measurements from 1990 to 2022. A dichotomous data matrix was constructed, incorporating genetic (genotype groups), environmental (rainfall levels), and technological index (degree of technification at the production unit) variables. Bivariate and multivariate logistic regression models, encompassing up to four variables, were applied. Two response variables were modeled: (1) probable AFC before 2.5 years of age and (2) probable AFC before 3 years of age. In the bivariate analysis for an AFC before 2.5 years, the technification variable presented a β1 level of 0.460 with an odds ratio of 2.37, whereas genetic variables exerted greater influence in the analysis for an AFC before 3 years. Specifically, the Predominantly European genetic group showed a β1 level of 0.642 and an odds ratio of 1.901. Interaction between the technification index and European (Holstein) genetic predominance in more complex models demonstrated a significant advantage for achieving calving before 2.5 years of age. Replacement heifers raised in technified systems were found to calve earlier (< 2.5 years). These models quantify the likelihood of cows calving for the first time at a younger age due to the studied factors; however, the development of mechanistic models, which provide higher precision but require more detailed and higher-quality data, is recommended.