The solution to reducing existing yield gaps on smallholder farms lies in understanding factors limiting yield in areas with agricultural intensification potential. This study applied an integrated analysis approach comprising Classification and Regression Tree (CART), generalized linear mixed model (GLMM), and factor analysis (FA), to explain soil and management‐related factors influencing maize yield gaps, in order to enhance yields. The study was conducted in Mukuyu and Shikomoli in western Kenya, sites with, respectively, high and low agroecological potential regarding soil fertility. Maize yield gaps were quantified by comparing yields on the 90th percentile of farms to yields determined in 189 fields on 70 randomly sampled smallholdings. Soil and management‐related factors were determined at early and late maize development stages.

中文翻译：

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土壤和管理相关因素导致肯尼亚西部玉米单产差距

减少小农户现有产量差距的解决方案在于了解限制具有农业集约化潜力的地区的产量的因素。这项研究应用了包括分类和回归树（CART），广义线性混合模型（GLMM）和因子分析（FA）在内的综合分析方法，以解释影响玉米单产差距的土壤和管理相关因素，以提高单产。这项研究是在肯尼亚西部的Mukuyu和Shikomoli进行的，这些地区在土壤肥力方面分别具有高和低农业生态潜力。通过比较农场第90个百分位数的产量与在70个随机采样的小农户中189个田地上确定的产量，可以量化玉米产量缺口。在玉米早期和晚期确定了土壤和管理相关因素。