The purpose of this paper was to utilize the decision trees technique to determine the factors responsible for high monthly milk yield in Polish Holstein‐Friesian cows from 27 herds equipped with milking robots. The applied statistical method—the decision tree technique—showed that the most important factors responsible for monthly milk yield of dairy cows using robots were, in descending order of importance: milking frequency, lactation number, month of milking, and type of lying stall. At the same time, it has been ascertained that the highest monthly milk yield (47.24 kg) can be expected from multiparous cows kept in barns with a deep bedding that were milked more frequently than three times per day. On the other hand, the lowest milk production (13.56 kg) was observed among dairy cows milked less frequently than two times a day, with an average number of milked quarters lower than 3.97. The application of the decision trees technique allows a breeder to select appropriate levels of environmental factors and parameters that will help to ensure maximized milk production.

中文翻译：

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使用决策树预测配备自动挤奶系统的农场奶牛的产奶量。

本文的目的是利用决策树技术来确定导致 27 个配备挤奶机器人的波兰荷斯坦-弗里西亚奶牛月产奶量高的因素。应用的统计方法——决策树技术——表明，影响使用机器人的奶牛月产奶量的最重要因素按重要性降序排列为：挤奶频率、泌乳次数、挤奶月份和卧床类型。同时，已经确定最高月产奶量 (47.24 公斤) 可以预期饲养在垫层较厚且每天挤奶次数超过 3 次的牛舍中的经产奶牛。另一方面，每天挤奶次数少于两次的奶牛的产奶量最低（13.56 公斤），平均挤奶季度数低于 3.97。决策树技术的应用允许饲养员选择适当水平的环境因素和参数，这将有助于确保最大化的牛奶产量。