[关键词]
[摘要]
目的 建立甘草Glycyrrhiza uralensis超高效液相色谱(UPLC)指纹图谱及多成分定量分析方法,并结合化学计量学进行不同产地甘草的质量分析和评价。方法 采用UPLC法建立30批不同产地甘草的指纹图谱,使用OriginPro 2024及SIMCA14.1软件进行Pearson相关性分析、聚类分析(cluster analysis,CA)、主成分分析(principal component analysis,PCA)、正交偏最小二乘判别分析(orthogonal partial least squares discriminant analysis,OPLS-DA)和接受者操作特征曲线分析,并对甘草中6种成分进行定量测定。结果 建立的UPLC指纹图谱共标定了23个共有峰,Pearson相关性分析表明各共有峰之间具有复杂的相关性,CA和PCA均表明,8个产地样本分布较为独立集中,部分甘肃样本与其它省份样本间有一定相似性,但样本整体被分为甘肃、内蒙古、新疆3大类,23个共有峰被分为5组;OPLS-DA则可实现对3省产地样本的有效区分,并筛选了10个差异性标志物;3省甘草样本中6个定量成分间的差异情况与OPLS-DA分析结果相近。结论 建立的甘草UPLC指纹图谱及多指标定量分析方法稳定、可靠,结合化学计量学分析可用于为甘草药材的产地质量评价和产地选择提供参考。
[Key word]
[Abstract]
Objective To establish the ultra-high performance liquid chromatography (UPLC) fingerprint and multi-component quantitative analysis method of Glycyrrhiza uralensis, and to combine with chemometrics for the quality analysis and evaluation of G. uralensis from different origins. Methods The fingerprints of 30 batches of G. uralensis from different origins were established by UPLC. Pearson correlation analysis, cluster analysis (CA), principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), and receiver operating characteristic curve analysis were performed using OriginPro 2024 and SIMCA14.1 software. A total of six components in G. uralensis were quantitatively determined. Results A total of 23 common peaks were calibrated in the established UPLC fingerprint. Pearson correlation analysis revealed a complex correlation between the common peaks. The results of the CA and PCA analyses indicated that the distribution of samples from the eight origins (cities) was relatively independent and concentrated. Some samples from Gansu province exhibited similarities with samples from other provinces, however, all samples could be classified into three categories (provinces): Gansu, Inner Mongolia, and Xinjiang. The 23 common peaks could be divided into five groups. OPLS-DA can effectively distinguish between the samples from three provinces, and 10 differential markers were screened. The differences between the six quantitative components in G. uralensis samples from three provinces were similar to the results of the OPLS-DA analysis. Conclusion The established UPLC fingerprint and multi-index quantitative analysis method of G. uralensis are stable and reliable. Combined with chemometric analysis, it can be used to provide a reference for the quality evaluation and selection of origin of G. uralensis.
[中图分类号]
R286.2
[基金项目]
湖北省科技重大专项(2020ACA007);湖北省科技重大专项(2022ACA003);黄石市揭榜制科技项目(2023A005)