In animal breeding, more considerable attention is drawn to reveal the relationship between live body weight and morphological traits in identifying breed and species standards. The aim of this study was to predict live body weight from morphological characteristics in the Hy-line silver brown commercial layer and indigenous Potchefstroom Koekoek breed, native to South African. In the prediction of live body weight, eleven morphological measurements, i.e., wing length, back length, beak length, shank length, shank circumference, chest circumference, wingspan, keel length, body girth, toe length, and body length, were taken. As tree-based regression tree methods, predictive performances of CART, CHAID, and exhaustive CHAID algorithms were measured for body weight prediction. Among those, CART was found to be the best decision tree algorithm that gave the highest predictive accuracy. CART visual results reflected that the heaviest body weight mean (2.000 kg) was obtained from the chickens with 10.250 cm < WL ≤ 10.500 cm. As a result, it could be suggested that the CART decision tree might help to determine breed standards of the Hy-line silver brown commercial layer and, especially, indigenous Potchefstroom Koekoek breeds for breeding programs.

在动物育种中，在确定品种和物种标准时，需要更多的注意力来揭示活体重与形态特征之间的关系。这项研究的目的是根据Hy-line银棕色商业层和南非原生的Potchefstroom Koekoek品种的形态特征预测活体重。在预测活体重时，进行了11种形态学测量，即翼长，后背长，喙长，小腿长，小腿周长，胸围，翼展，龙骨长，体围，趾长和体长。作为基于树的回归树方法，对CART，CHAID和详尽的CHAID算法的预测性能进行了测量，以进行体重预测。在这些，发现CART是提供最高预测准确性的最佳决策树算法。CART视觉结果反映出，从体重为10.250 cm <WL≤10.500 cm的鸡身上获得的平均体重最高（2.000 kg）。结果，可以建议CART决策树可能有助于确定Hy-line银棕色商业层的品种标准，尤其是用于繁殖计划的本地Potchefstroom Koekoek品种。