目的 建立板蓝根Isatidis Radix饮片指纹图谱及代表性成分含量测定方法，通过数学模型构建质量预测体系，探究不同趁鲜加工炮制过程中板蓝根品质变化规律。方法 收集新鲜板蓝根，通过控制干燥方式、烘干温度、烘干时间和水处理时间，共制备15批板蓝根饮片。通过高效液相技术（HPLC）建立指纹图谱，标定共有峰。结合聚类分析（hierarchical cluster analysis，HCA）、主成分分析（principal component analysis，PCA）、正交偏最小二乘法-判别分析（orthogonal partial least squares discrimination analysis，OPLS-DA）对15批板蓝根质量进行评价，运用层次分析法（analytic hierarchy process，AHP）-熵权法确定各指标权重，计算综合评分。结果 建立15批板蓝根的指纹图谱，各组相似度0.891～0.997，标定11个共有峰，指认出尿苷、鸟苷、(R,S)-告依春、腺苷4个成分；HCA基于干燥工艺将样品划分为2个聚类组别；PCA共提取3个主成分，累积方差贡献率为83.973%；OPLS-DA分析表明(R,S)-告依春和鸟苷可能是区分饮片质量差异的重要标志物；熵权法综合评分显示60 ℃烘干5 h工艺评分最高。结论 指纹图谱结合化学模式识别能够区分不同趁鲜加工方法制备的板蓝根饮片，筛选影响板蓝根饮片质量的关键因素，为趁鲜加工板蓝根饮片质量控制与评价提供参考。

Objective To establish fingerprint spectra for Bailangen (Isatidis Radix) slices and methods for determining representative component content. Developing a quality prediction system through mathematical modeling to investigate the patterns of quality changes in Isatidis Radix during different fresh processing methods. Method Collecting fresh Isatidis Radix and preparing 15 batches of Isatidis Radix slices by controlling drying methods, drying temperature, drying time, and water treatment duration. HPLC was used to establish the fingerprint and calibrate the total peaks. Combining hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares discrimination analysis (OPLS-DA) to evaluate the quality of 15 batches of Isatidis Radix, the analytic hierarchy process (AHP)-entropy weighting method was used to determine the weights of each indicator, and a comprehensive score was calculated. Results HPLC fingerprints were established for 15 batches of Isatidis Radix, with a similarity of 0.891 to 0.997 between each group. Eleven common peaks were calibrated, and four components were identified: uridine, guanosine, (R,S)-goitrin, and adenosine. HCA analysis divided the samples into two clusters based on differences in the drying process; PCA extracted three principal components, with a cumulative variance contribution rate of 83.973%; OPLS-DA analysis showed that (R,S)-goitrin and guanosine may be important markers for distinguishing differences in the quality of Chinese herbal medicine slices; the comprehensive score of the entropy weight method showed that the 60 ℃ drying for 5 h process had the highest score. Conclusion Fingerprinting combined with chemical pattern recognition can distinguish Isatidis Radix slices prepared using different fresh processing methods, screen for key factors affecting the quality of Isatidis Radix slices, and provide a reference for quality control and evaluation of freshly processed fresh Isatidis Radix slices.

R282.6

优化板蓝根产地加工炮制一体化研究横向课题（KF202403）；河南省科学技术厅科技攻关项目（252102310530）；河南省杰出青年科学基金资助项目（252300421028）