Body Weight Estimation in Holstein × Zebu Crossbred Heifers: Comparative Analysis of XGBoost and LightGBM Algorithms
Herrera-Camacho J. Tırınk C. Parra-Cortés R.I. Bayyurt L. Uskenov R. Omarova K. Makhanbetova A. Chekirov K. Chay-Canul A.J.
July 2025John Wiley and Sons Inc
Veterinary Medicine and Science
2025#11Issue 4
This study evaluates the effectiveness of XGBoost and LightGBM algorithms for estimating the live weight of Holstein×Zebu crossbred heifers. The study compares the performance of both algorithms using a wide range of biometric measurements and tests various hyperparameter settings. The research results show that the XGBoost algorithm provides almost perfect agreement with an R2 value of 0.999 on the training set and high performance with an R2 value of 0.986 on the test set. The LightGBM algorithm also achieved effective results with R2 values of 0.986 and 0.981 on both training and test sets. The machine learning algorithms used in the current study stand out as having the potential to provide a practical and economical solution for live weight estimation in livestock enterprises and especially for herd management applications in rural areas through input variables such as body measurements, milk yield, etc. However, the obtained results in the current study reveal the potential of machine learning algorithms for live weight estimation in the livestock sector and indicate that advanced research is needed for the optimisation of these algorithms.
body weight prediction , crossbred heifer , LightGBM , machine learning , XGBoost
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Universidad Michoacana de San Nicolás de Hidalgo, Michoacán, Morelia, Mexico
Department of Animal Science, Igdir University, Faculty of Agriculture, Iğdır, Turkey
Universidad de Ciencias Aplicadas y Ambientales U.D.C.A, Área de Ciencias Agropecuarias, Grupo de Investigación en Ciencia Animal, Bogotá, Colombia
Faculty of Agriculture, Department of Animal Science, Tokat Gaziosmanpaşa University, Tokat, Turkey
Agronomic Faculty, Saken Seifullin Kazakh Agrotechnical University, Astana, Kazakhstan
Faculty of Veterinary and Livestock Technology, Saken Seifullin Kazakh Agrotechnical University, Astana, Kazakhstan
Kyrgyz-Turkish Manas University, Bishkek, Kyrgyzstan
División Académica de Ciencias Agropecuarias, Universidad Juárez Autónoma de Tabasco, Tabasco, Villahermosa, Mexico
Universidad Michoacana de San Nicolás de Hidalgo
Department of Animal Science
Universidad de Ciencias Aplicadas y Ambientales U.D.C.A
Faculty of Agriculture
Agronomic Faculty
Faculty of Veterinary and Livestock Technology
Kyrgyz-Turkish Manas University
División Académica de Ciencias Agropecuarias
10 лет помогаем публиковать статьи Международный издатель
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