目的 建立克比热提片的UPLC指纹图谱，结合化学模式识别技术评价其质量。方法 构建16批克比热提片样品的UPLC指纹图谱，进行相似度分析，结合层次聚类分析（HCA）、主成分分析（PCA）、正交偏最小二乘判别分析（OPLS-DA）开展化学模式识别。结果 共确定26个共有峰，指认出10个色谱峰，分别为新绿原酸、绿原酸、隐绿原酸、3,4-O-二咖啡酰奎宁酸、3,5-O-二咖啡酰奎宁酸、4,5-O-二咖啡酰奎宁酸、墙草碱、猪苓酸C、去氢茯苓酸和茯苓酸；HCA、PCA将16批样品分为4类，结果一致；OPLS-DA模型无过度拟合，筛选出9个差异性特征成分。结论 建立的UPLC指纹图谱结合化学模式识别的方法稳定可靠、专属性强，可有效评价克比热提片质量。

Objective To establish a UPLC fingerprint combined with chemical pattern recognition technology for the quality evaluation of Kebireti Tablets. Methods UPLC fingerprints of 16 batches of Kebireti Tablets samples were constructed, and the similarities were analyzed. Chemical pattern recognition research was conducted by combining HCA, PCA, and OPLS-DA analyses. Results A total of 26 common peaks were identified, and 10 chromatographic peaks were identified, namely neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, 3,4-O-dicaffeoylquinic acid, 3,5-O-dicaffeoylquinic acid, 4,5-O-dicaffeoylquinic acid, pellitorine, polyporenic acid C, dehydropachymic acid, and pachymic acid. 16 Batches of samples were divided into 4 categories by HCA and PCA, and the results were consistent. The OPLS-DA model had no overfitting and 9 differential feature components were screened out. Conclusion The UPLC fingerprint combined with chemical pattern recognition method established is stable, reliable, and highly specific, which can effectively evaluate the quality of Kebireti Tablets.

中央引导地方科技发展资金项目（2025ZY-XCZXZS-27）；陕西省科技厅中医药制剂及新药研发中试基地项目（2025ZY1-ZSJD-14）；秦创原“科学家＋工程师”队伍项目（2025QCY-KXJ-104）