为了评估新疆沙湾市农田的土壤质量状况，明确影响生产力水平的关键影响因子，推进沙湾市高标准农田建设。运用主成分分析法（PCA）及聚类分析法（CA）分别建立农田土壤质量评价指标的最小数据集，再结合障碍因子诊断模型揭示沙湾市农田土壤质量特征及其障碍因素。结果表明：（1） 基于不同数据集的土壤质量评价结果差异明显，其中基于聚类分析的土壤质量指数与全数据集呈显著正相关（R²=0.591，P<0.1），Nash有效系数为-4.923，均大于基于主成分分析的最小数据集，这表明基于聚类分析的最小数据集较基于主成分分析的最小数据集更适合替代全数据集对农田土壤质量进行评价。（2） 研究区土壤质量总体处于中等及以上水平，土壤质量指数为0.130~0.641；基于最小数据集的土壤质量指数将沙湾市农田划分为5级，Ⅰ级土壤主要分布在研究区北部及西北方向，Ⅴ级土壤主要分布在东南方向，整体呈现出西北高、东南低的空间分布格局。（3） 土壤有机质含量低、氮素缺失、电导率高是影响研究区土壤质量的主要障碍因子。研究结果可用于有效提升当地农田土壤质量，建议在农田管理过程中，除了施用有机肥之外，还可以通过深耕、种植杂草、覆盖秸秆、地膜覆盖等措施改良土壤。

In order to evaluate the soil quality status of farmland in Shawan City of Xinjiang, China and to clarify the key influencing factors on productivity level, and promote the construction of high standard farmland in Shawan City, this paper build the minimum dataset of farmland soil quality with principal component analysis and cluster analysis, and combined with an obstacle factor diagnostic model, the characteristics and obstacle factors of agricultural soil quality in the Shawan area were revealed. The results led to three main conclusions. (1) There were significant differences between the results of soil quality evaluations using different datasets. The soil quality indices determined using the minimum dataset based on cluster analysis and using the total dataset significantly positively correlated (R²=0.591, P<0.1),the Nash effective coefficient was -4.923, indicating that the minimum dataset based on cluster analysis gave better results than the minimum dataset based on principal component analysis. This indicated that the minimum dataset based on cluster analysis was more suitable than the minimum dataset based on principal component analysis for replacing the total dataset when evaluating farmland soil quality. (2) The overall soil quality in the study area was found to be moderate and better, and the soil quality indices were 0.130-0.641. Farmland in Shawan City was divided into five classes using the soil quality index minimum dataset. Class I soil was mainly in the northern and northwestern parts, and class V soil was mainly in the southeastern part of the study area, indicating that the soil quality was generally high in the northwest and low in the southeast. (3) There were obvious obstacles in the research area, which low organic matter contents, insufficient nitrogen, and high electrical conductivities were the main obstacles. The research results can be used to effectively improve the soil quality of local farmland. It is recommended that in the process of farmland management, not only applying organic fertilizer, take measures such as deep tillage, planting weeds, covering straw, and plastic film to improve the soil.