基于超高效液相色谱-电喷雾检测器构建恒山黄芪指纹图谱并鉴别其产地

Construction of Hengshan Astragalus fingerprint and identification of its origin based on ultra performance liquid chromatography-charged aerosol detector

中文关键词:  恒山黄芪（恒山山脉仿野生）  超高效液相色谱仪  电喷雾检测器  指纹图谱  化学计 量学分析

英文关键词:Hengshan Astragalus  ultra performance liquid chromatography  charged aerosol detector  fingerprint  stoichiometric analysis

中文摘要:

      目的 基于超高效液相色谱-电喷雾检测器(ultra performance liquid chromatography-charged aerosol detector, UPLC-CAD)技术构建不同产地黄芪所含成分的指纹图谱, 并对其进行对比分析, 实现不同产地黄芪的质量评价与产地鉴别。方法 采用UPLC-CAD技术, 聚焦于黄酮类与皂苷类成分, 选取29批多个产地的样本绘制恒山山脉仿野生黄芪指纹图谱。运用聚类分析、主成分分析(principal component analysis, PCA)及正交偏最小二判别分析(orthogonal partial least squares discriminant analysis, OPLS-DA)等统计方法分析评价。结果 指纹图谱成功标记出26个共有峰, 鉴定出包括沙苑子苷A、芒柄花苷、黄芪皂苷Ⅰ至Ⅳ等在内的8个关键特征峰。聚类分析清晰地将样本分为两大类, 揭示了地域差异对黄芪质量的影响。PCA进一步提炼出7个主成分。OPLS-DA分析则精准预测了影响黄芪质量差异的8种关键化合物, 这些差异性化合物与产地、栽培方式及生长年限紧密相关。结论 本研究综合应用UPLC-CAD技术与多元化学计量学分析手段, 成功构建了能够区分不同基原、产地及栽培方式的黄芪指纹图谱, 可对黄芪(恒山山脉仿野生)进行指纹图谱相似度评价, 专属性强, 灵敏度高, 为恒山山脉仿野生黄芪的质量评价提供了科学依据。

英文摘要:

      Objective To construct and compare the fingerprint profiles of Astragalus samples from different origins based on ultra performance liquid chromatography-charged aerosol detector (UPLC-CAD) technology, achieve quality evaluation and origin identification of Astragalus. Methods Using UPLC-CAD technology, this study focused on flavonoid and saponin components to construct the fingerprint of wild-simulated Astragalus membranaceus from the Hengshan Mountains, based on 29 batches of samples collected from multiple geographical origins. Statistical analysis methods such as cluster analysis, principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were used for analysis and evaluation. Results The fingerprint successfully marked 26 common peaks, and 8 key characteristic peaks were identified, including complanatoside A, ononin, astragaloside I to IV, etc. Cluster analysis clearly divided the samples into two major categories, revealing the influence of regional differences on the quality of Astragalus membranaceus. PCA further extracted 7 principal components. OPLS-DA analysis accurately predicted 8 kinds of key compounds influencing the quality differences, which were closely related to origin, cultivation methods, and growth duration. Conclusion This study successfully constructed a fingerprint capable of distinguishing Astragalus based on its origin, cultivation methods, and growth conditions by integrating UPLC-CAD technology with multivariate chemometric analysis. This method can be used to evaluate the fingerprint similarity of Astragalus membranaceus (Hengshan Mountain wild-simulated), with high specificity and sensitivity, which provids a scientific basis for the quality assessment of wild-simulated Astragalus from the Hengshan Mountains.