天然产物研究与开发 ›› 2026, Vol. 38 ›› Issue (6): 1221-1230.doi: 10.16333/j.1001-6880.2026.6.008 cstr: 32307.14.1001-6880.2026.6.008

• 研究简报 • 上一篇    下一篇

基于UPLC指纹图谱、化学模式识别及多指标成分定量的五岭龙胆质量评价研究

彭江丽1,2,3,邓美玲1,王  鹏1,彭求贤1,李顺祥1,2,3*   

  1. 1湖南中医药大学药学院;2湖南省中药活性物质筛选工程技术研究中心;3湖南省中美老年性退行性疾病治疗药物国际联合研究中心,长沙410208
  • 出版日期:2026-06-26 发布日期:2026-06-24
  • 基金资助:
    湖南省自然科学基金-科药联合项目(2026JJ80905);国家级大学生创新创业训练计划(202510541019);湖南中医药大学中药学一流学科基金(校行科字[2023]2号)

Quality evaluation of Gentiana davidii French.based on UPLC fingerprint,chemical pattern recognition and multi-component quantification

PENG Jiang-li1,2,3,DENG Mei-ling1,WANG Peng1,PENG Qiu-xian1,LI Shun-xiang1,2,3*   

  1. 1School of Pharmacy,Hunan University of Chinese Medicine;2 Hunan Engineering Research Center of Bioactive Substance Discovery of Chinese Medicine; 3Hunan Province Sino-US International Joint Research Center for Therapeutic Drugs of Senile Degenerative Diseases,Changsha 410208,China
  • Online:2026-06-26 Published:2026-06-24

摘要:

建立五岭龙胆UPLC指纹图谱、化学模式识别与多指标成分定量的整合分析方法,评价不同产地五岭龙胆药材的质量属性与差异,为其质量评价提供科学依据。采用UPLC法建立不同产地五岭龙胆的指纹图谱,运用相似度分析、聚类分析、主成分分析和正交偏最小二乘判别分析等化学模式识别技术筛选出不同产地五岭龙胆化学成分的特征成分,并进行多指标成分定量分析。UPLC指纹图谱共标定10个共有峰,指认其中6个共有峰,分别为马钱苷酸、獐牙菜苦苷、龙胆苦苷、獐牙菜苷、异荭草素、异牡荆素,其相似度为0.9以上;通过聚类分析、主成分分析和正交偏最小二乘判别分析较好地区别各产地的五岭龙胆,明确了样品之间的归类情况,13批样品聚为3类,筛选出影响五岭龙胆药材质量差异的龙胆苦苷、獐牙菜苷、异荭草素3个主要标志性成分;对五岭龙胆进行6个多指标成分分析,发现其各成分的质量浓度范围线性关系较好,平均加样回收率为95.98%~98.72%,相对标准偏差为2.7%~5.0%,13批样品6个成分含量分别为0.080 7~1.172 3、0.045 7~0.269 1、0.768 8~3.074 7、0.008 7~0.172 1、0.054 4~0.298 9、0.024 1~0.400 0 mg/g,各成分在不同产地之间存在差异。综上,基于同一色谱条件的指纹图谱和多指标成分定量分析操作方便、准确可靠,结合化学模式分析,可将龙胆苦苷、獐牙菜苷、异荭草素3个成分作为质量标志物,为其整体质量控制和评价提供参考。

关键词: 五岭龙胆, UPLC, 指纹图谱, 化学识别模式, 多指标成分定量

Abstract:

To evaluate the quality attributes of Gentiana davidii French. from different producing areas and providing a scientific basis for its quality assessment, an integrated analytical method combining UPLC fingerprinting, chemical pattern recognition and multi-component quantitative analysis was established. The UPLC fingerprint were adopted to establish for G. davidii from different habitats. Chemical pattern recognition techniques, including similarity evaluation, cluster analysis (CA), principal component analysis (PCA), and orthogonal partial least squares-discriminant analysis (OPLS-DA), were employed to evaluate the quality of  G. davidii, followed by multi-index quantitative analysis. The UPLC fingerprint identified 10 common peaks, of which six perks were identified as loganic acid, swertiamarin, gentiopicroside, sweroside, isoorientin, and isovitexin, with the similarity above 0.9. The results of CA, PCA and OPLS-DA indicated that the 13 batches of G. davidii samples were classified into three distinct clusters. Gentiopicroside, sweroside, and isoorientin were screened as quality markers (Q-Markers) by comprehensive analysis. Quantitative analysis of six components  were demonstrated good linearity across respective concentration ranges. The recovery rates were 95.98%-98.72%, with relative standard deviation of 2.7%-5.0%. The content of six components in 13 batches of sample were 0.080 7-1.172 3, 0.045 7-0.269 1, 0.768 8-3.074 7, 0.008 7-0.172 1, 0.054 4-0.298 9, 0.024 1-0.400 0 mg/g, respectively,  and the contents of each components varied among different producing areas.  In conclusion, the qualitative analysis of fingerprint and quantitative analysis of multi-component based on the same chromatographic analysis conditions are convenient, accurate and reliable. Combined with chemical pattern analysis, gentiopicroside, sweroside and isoorientin can be selected as Q-Markers, which can provide reference for quality control and evaluation of  G. davidii.

Key words: Gentiana davidii French., UPLC, fingerprint, chemical pattern recognition, multi-component quantification

中图分类号:  R284.2