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Articles | Volume 68, issue 4
Articles | Volume 68, issue 4
https://doi.org/10.5194/aab-68-653-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/aab-68-653-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 68, issue 4
Original study
 | 
30 Oct 2025
Original study |  | 30 Oct 2025

Predicting body weight of male Kuroiler chickens from linear body measurements using MARS and CART data-mining algorithms

Simushi Liswaniso, Ruth Kasonso, Lubabalo Bila, Madumetja Cyril Mathapo, Oswin Chibinga, Thobela Louis Tyasi, Xue Sun, Rifu Xu, and Ning Qin

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Short summary
Small-scale farmers use scales, which are difficult to access or maintain, to measure body weight. In this study, we developed models to predict body weight in Kuroiler male chickens using data-mining algorithms, namely multivariate adaptive regression splines (MARS) and classification and regression trees (CART). The CART model was more accurate than the MARS model, with both models identifying wing span and chest circumference as crucial factors in predicting body weight.
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