ArticleAnimals : an open access journal from MDPI2023
Classification of Daily Body Weight Gains in Beef Calves Using Decision Trees, Artificial Neural Networks, and Logistic Regression.
Article in Animals : an open access journal from MDPI, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 9 citations in OpenAlex.
- Beef Cattle Body Weight Estimation Based on Dual-View RGB Images.Animals : an open access journal from MDPI · 2026Article
- Early prediction of final body weight in Hanwoo steers using machine and deep learning models.Animal bioscience · 2026Article
- Decision tree-based evaluation of IGF-1 and CAST gene polymorphisms associated with morphometric traits in sheep.Molecular biology reports · 2026Article
- End-to-end deep SAE-DNN model for predicting Egyptian buffalo calf sex, weight, and daily milk yield.Tropical animal health and production · 2025Article
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5 authors at 2 institutions in 1 country.
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Abstract
The aim of the present study was to compare the predictive performance of decision trees, artificial neural networks, and logistic regression used for the classification of daily body weight gains in beef calves. A total of 680 pure-breed Simmental and 373 Limousin cows from the largest farm in the West Pomeranian Province, whose calves were fattened between 2014 and 2016, were included in the study. Pre-weaning daily body weight gains were divided into two categories: A-equal to or lower than the weighted mean for each breed and sex and B-higher than the mean. Models were developed separately for each breed. Sensitivity, specificity, accuracy, and area under the curve on a test set for the best model (random forest) were 0.83, 0.67, 0.76, and 0.82 and 0.68, 0.86, 0.78, and 0.81 for the Limousin and Simmental breeds, respectively. The most important predictors were daily weight gains of the dam when she was a calf, daily weight gains of the first calf, sex of the third calf, milk yield at first lactation, birth weight of the third calf, dam birth weight, dam hip height, and second calving season. The selected machine learning models can be used quite effectively for the classification of calves based on their daily weight gains.
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