The popularity of Tartary buckwheat [Fagopyrum tataricum (L.) Gaertn], as a medicinal and food crop, has been increasing in recent years. However, its low yield seriously restricts its industrial development. Amongst the various studies conducted to enhance the productivity of Tartary buckwheat, the association between yield and main agronomic traits has formed the foundation for the breeding and cultivation of high‐yielding varieties, becoming the primary interest of breeders. The commonly used methods are often restricted by sample size, distribution assumptions and trait properties and confined to the linear relationship. In this paper, the random forest regression model was used to obtain a comprehensive and reliable evaluation. The phenotypic data of 200 Tartary buckwheat landraces with 15 quantitative and two qualitative agronomic traits for two consecutive years were used. Results were compared between planting seasons and with those from classical methods, such as the correlation analyses and the multiple linear regression model. The random forest model distinguished the number of grains per plant, plant height, and 1,000‐grain weight as the most influential agronomic traits in both seasons. The main and interactive effects were explored using the accumulated local effects plot and showed great conformity between the two seasons. The robustness and reliability of the random forest model make it a desirable methodology for breeding new varieties and germplasm innovation of Tartary buckwheat and other crops.

中文翻译：

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用随机森林模型评价苦荞的产量与主要农艺性状的关联

苦荞的流行[ Fagopyrum tataricum（L.）Gaertn]，作为药物和粮食作物，近年来一直在增长。但是，其低产量严重限制了其工业发展。为了提高苦荞的生产力而进行的各种研究中，产量与主要农艺性状之间的联系已为高产品种的选育奠定了基础，成为育种者的主要兴趣。常用的方法通常受样本量，分布假设和性状特性的限制，并局限于线性关系。本文使用随机森林回归模型来获得全面而可靠的评估。连续两年使用了200个具有15个定量和两个定性农艺性状的苦荞型地方品种的表型数据。将种植季节之间的结果与经典方法（如相关分析和多元线性回归模型）的结果进行比较。随机森林模型将两个季节中最有影响力的农艺性状区分为单株谷物数量，株高和1,000粒重。使用累积的局部效应图探索了主要和互动效应，并显示了两个季节之间的一致性。随机森林模型的鲁棒性和可靠性使其成为T苦荞麦和其他农作物的新品种选育和种质创新的理想方法。两种季节中最有影响力的农艺性状是株高，千粒重。使用累积的局部效应图探索了主要和互动效应，并显示了两个季节之间的一致性。随机森林模型的鲁棒性和可靠性使其成为T苦荞麦和其他农作物的新品种选育和种质创新的理想方法。两种季节中最有影响力的农艺性状是株高，千粒重。使用累积的局部效应图探索了主要和互动效应，并显示了两个季节之间的一致性。随机森林模型的鲁棒性和可靠性使其成为T苦荞麦和其他农作物的新品种选育和种质创新的理想方法。