天然产物研究与开发 ›› 2026, Vol. 38 ›› Issue (4): 827-837.doi: 10.16333/j.1001-6880.2026.4.014 cstr: 32307.14.1001-6880.2026.4.014

• 开发研究 • 上一篇    下一篇

基于多指标定量联合化学计量学及加权TOPSIS模型的不同产地荔枝草综合质量评价

李思阳1,2*,李更东2,闫宇辉1   

  1. 1江苏食品药品职业技术学院药学院,淮安 223003;2东北林业大学生命科学学院,哈尔滨 150040
  • 出版日期:2026-04-27 发布日期:2026-04-24
  • 基金资助:
    江苏省高校自然科学研究面上项目(17KJB360002);江苏高校“青蓝工程”优秀青年骨干教师项目(苏教师函〔2022〕51号);淮安市科学技术局重点研发计划(HAG201613)

Comprehensive quality evaluation of Salviae Plebeiae Herba from different origin based on multi-index quantification combined chemometrics and weighted TOPSIS model

LI Si-yang1,2*,LI Geng-dong2,YAN Yu-hui1   

  1. 1School of Pharmacy, Jiangsu Food and Pharmaceutical Science College,Huai′an 223003,China;2School of Life Science,Northeast Forestry University,Harbin 150040,China
  • Online:2026-04-27 Published:2026-04-24

摘要:

建立多指标定量联合化学计量学及加权逼近理想解排序(technique for order preference by similarity to ideal solution,TOPSIS)模型对不同产地荔枝草进行综合质量评价的方法。研究以迷迭香酸和熊果酸为内参物,采用HPLC一测多评法同时测定荔枝草中绿原酸、咖啡酸、阿魏酸、迷迭香酸、泽兰黄酮、高车前苷、高车前素、木犀草苷、芹菜素、鼠尾草酚、熊果酸、齐墩果酸、胡萝卜苷和β-谷甾醇含量,同时对其醇溶性浸出物、水溶性浸出物和总灰分进行含量检测,建立荔枝草多指标定量检测方法;采用主成分分析、正交偏最小二乘法-判别分析等化学计量学方法对多指标定量检测结果进行数据分析,实现对不同产地荔枝草聚类分组,挖掘影响荔枝草产品质量的主要潜在标志物;同时建立加权TOPSIS模型对不同产地荔枝草样品进行质量优劣排序。实验结果显示14个定量检测成分在各自质量浓度范围内线性关系良好(r>0.999),平均加样回收率为96.97%~100.1%(相对标准偏差(relative standard deviation,RSD)<2.0%),相对校正因子耐用性良好(RSD<2.0%),一测多评法可用于荔枝草中14个成分的同步检测;18批样品聚为3类,高车前素、高车前苷、迷迭香酸、泽兰黄酮、咖啡酸、鼠尾草酚和芹菜素可能是影响荔枝草产品质量的主要潜在标志物;18批荔枝草质量评价贴近度(Jb)在0.161 8~0.661 2之间,加权TOPSIS模型可用于荔枝草样品质量优劣排序。实验结果表明本研究所建立的多指标定量检测方法操作简便、结果准确,联合化学计量学及加权TOPSIS模型可用于不同产地荔枝草综合质量评价。

关键词: 荔枝草, HPLC, 化学计量学, 加权TOPSIS法, 质量评价

Abstract:

This study aims to establish a multi-index quantification combined chemometrics and weighted TOPSIS model for comprehensive quality evaluation of Salviae Plebeiae Herba (SPH) from different producing areas. The contents of chlorogenic acid, caffeic acid, ferulic acid, nepetin, homoplantaginin, hispidulin, luteolin-7-O-glucopyranoside, apigenin, carnosol, oleanolic acid, Eleutheroside a and β-sitosterol in SPH were determined by HPLC-QAMS with rosmarinic acid and ursolic acid as internal reference substances, At the same time, the contents of alcohol-soluble extract, water-soluble extract and total ash were detected, and a multi-index quantification detection method for SPH was established. Principal component analysis, orthogonal partial least squares-discriminant analysis and other chemometric methods were used to analyze the data of multi-index quantification detection results, so as to realize the clustering of SPH from different producing areas and explore the main potential markers affecting the quality of SPH. At the same time, a weighted TOPSIS model was established to rank the quality of SPH samples from different producing areas. The experimental results showed that the 14 quantitative detection components had a good linear relationship in their respective mass concentration ranges (r> 0.999), the average recovery was 96.97%-100.1% (RSD< 2.0%), and the relative correction factor had good durability (RSD < 2.0%). The QAMS method can be used for simultaneous detection of 14 components in SPH. Eighteen batches of samples were clustered into 3 categories. Hispidulin, homoplantaginin, rosmarinic acid, nepetin, caffeic acid, carnosol and apigenin may be the main potential markers affecting the quality of SPH. The analysis results of the weighted TOPSIS method revealed that the closeness (Jb) for evaluating the quality of 18 batches of SPH ranged from 0.161 8 to 0.661 2, The weighted TOPSIS model could be used to sort the quality of SPH samples. The experimental results show that the multi-index quantification detection method established in this study is simple and accurate, and the combined chemometrics and weighted TOPSIS model can be used for the comprehensive quality evaluation of SPH from different producing areas.

Key words: Salviae Plebeiae Herba, HPLC; chemometrics, weighted TOPSIS, quality evaluation

中图分类号:  R917