基于指纹图谱和化学计量学的白芍产地溯源和质量评价

目的 建立白芍高效液相色谱(high performance liquid chromatography, HPLC)指纹图谱,并结合化学计量学进行分析与评价。方法 采用HPLC法测定31批不同产地白芍中没食子酸、儿茶素、氧化芍药苷、芍药内酯苷、芍药苷、五没食子酰葡萄糖、苯甲酰芍药苷和丹皮酚8种成分含量,并用中药指纹图谱相似度评价系统进行相似度评价。结合聚类分析、主成分分析和正交偏最小二乘法分析化学计量学方法,对其进行质量评价。结果 所建立的白芍HPLC指纹图谱共标定了11个色谱峰,经对照品比对鉴定出8个色谱峰并进行含量测定;相似度和聚类分析结果显示,不同产地白芍质量存在差异;含量测定结果显示不同产地白芍中8个成分种类并无差异,但含量差异较大,其中山西产地芍药苷、芍药内酯苷平均含量较高,四川产地五没食子酰葡萄糖和丹皮酚平均含量较低;进一步用主成分分析进行综合评价,发现山西和浙江产地白芍质量较优;利用正交偏最小二乘法分析得出白芍总苷、芍药内酯苷和芍药苷为主要差异成分。结论 本研究建立的白芍HPLC指纹图谱结合化学计量学的方法能够快速、科学、准确地应用到白芍的产地溯源和质量评价中。

Geographical origin traceability and quality evaluation of Paeonia lactiflora based on fingerprint and stoichiometry

ABSTRACT: Objective To establish a high performance liquid chromatography (HPLC) fingerprint of Paeonia lactiflora and combined with stoichiometry analysis and evaluation. Methods 8 kind of component content, including Gallic acid, Catechin, Oxypaeoniflorin, Albiflorin, Paeoniflorin, Pentagalloylglucose, Benzoylpaeoniflorin and Paeonol in 31 batches of Paeonia lactiflora from 5 regions were simultaneously detected and analyzed by HPLC. The similarity evaluation system of traditional Chinese medicine fingerprint was performed to analyze and evaluate the Paeonia lactiflora from different regions, combined with Hierarchical clustering analysis (HCA), principal component analysis (PCA) and orthogonal partial least squares analysis (OPLS-DA). Results The consensus of HPLC fingerprint of Paeonia lactiflora was established to calibrate 11 peaks and 8 of them were identified and determined by comparison with reference substance; The results showed that the similarity ranged from 0.615 to 0.924 in 31 batches and indicated that there were different from Paeonia lactiflora from different regions; The results of content determination showed that there was quite difference of 8 components in Paeonia lactiflora from different regions. The contents of Albiflorin, Paeoniflorin are higher, while the content of Paeonol was lower. HCA and PCA results showed that the samples from the same origin were clustered together, but the samples from different origin were scattered, suggesting that the growth environment and climate conditions of different origin may be the reason for this result. OPLS-DA results showed that TGP, Albiflorin and Paeoniflorin were the main components of Paeonia lactiflora from different areas, suggesting that these components could be used as indicators for quality evaluation of Paeonia lactiflora. The results of comprehensive score showed that the quality of Paeonia lactiflora from Shanxi and Zhejiang provinces were better. Conclusion In this study, the HPLC fingerprint combined with stoichiometry could be quickly, scientifically and accurately applied to the geographical origin traceability and quality evaluation of Paeonia lactiflora.