This study compares the performance of XGBoost and LightGBM models for predicting live weights of Yucatecan Criollo pigs from biometric measurements and examines the structural and algorithmic differences that affect model fit. Detailed analysis of the models’ hyperparameter optimization and variable importance revealed how each model approaches the data and prioritizes features. This study was conducted on 182 Yucatecan Criollo pigs (134 females and 48 males). When model performances were evaluated, the XGBoost model showed superior prediction performance with acceptable accuracy and lower error rates in the test dataset, with R² = 0.905, RMSE = 5.704, and MAE = 3.636. In contrast, the LightGBM model produced acceptable results under certain hyperparameter combinations with R² = 0.824, RMSE = 7.772, and MAE = 5.505. While the robust performance of both models requires strategic decisions in model selection and optimization, it is recommended to consider the dataset’s nature in feature selection and hyperparameter settings. This study provides important insights for simplifying the model and improving its efficiency in machine learning applications, and serves as a reference for more effective model use.

The objective of the study was to evaluate the social and environmental sustainability of the production system with Nunkini creole cattle in Campeche, Mexico. Ten production units (PU) were evaluated, in which sustainability was determined through a general mathematical model that quantifies principles and objectives of sustainable socioenvironmental development. The results of the model are expressed in a range of values from 0 to 10 and are classified as: Unsustainable, May be sustainable, Evolving, Evolving sustainable, and Highly sustainable. Of the ten PU, one (10%) is at the evolving level, seven (70%) are evolving sustainable, and two (20%) are highly sustainable. In conclusion, the local livestock production system tends towards socioenvironmental sustainability; however, it could be more efficient if social action and participation among producers is promoted. El objetivo del estudio fue evaluar la sustentabilidad social y ambiental del sistema productivo con bovinos criollos Nunkiní en Campeche, México. Se evaluaron diez unidades de producción (UP), en las cuales la sustentabilidad se determinó a través de un modelo matemático general que cuantifica los principios y objetivos del desarrollo socioambiental sostenible. Los resultados del modelo se expresaron en un rango de valores de 0 a 10 y se clasificaron como: No sustentable, Puede ser sustentable, En evolución, Sustentable en evolución y Altamente sustentable. De las diez UP, una (10%) se encuentra en el nivel en evolución, siete (70%) son sustentables en evolución y dos (20%) altamente sustentables. En conclusión, el sistema local de producción ganadera tiende hacia la sustentabilidad socioambiental; no obstante, podría ser más eficiente si se promueve la acción social y la participación entre los productores.