[关键词]
[摘要]
目的 建立基于核磁共振技术1H-NMR指纹图谱-化学模式识别的四裂红景天和大花红景天的品种分类和鉴别方法。方法 采用高分辨(600 MHz)的核磁共振(NMR)指纹图谱技术,测定四裂红景天和大花红景天的全成分信息1H-NMR指纹图谱,结合相似性分析、层次聚类分析、主成分分析(PCA)和偏最小二乘法-判别分析(PLS-DA)进行化学模式识别分析。结果 1H-NMR指纹图谱-化学模式识别方法是一种有效的区分、鉴别四裂红景天和大花红景天的方法。四裂红景天和大花红景天的1H-NMR指纹图谱差异性较明显,能够真实、全面地反映红景天中的特征性成分和内在品质,四裂红景天和大花红景天主要差异成分为萜类、黄酮类,尤其萜类成分大花红天素是鉴别四裂红景天和大花红景天的特征性成分,可作为四裂红景天和大花红景天的分类和鉴别指标。结论 1H-NMR指纹图谱-化学模式识别方法是一种有效的红景天品种分类和鉴别方法,为红景天属药用植物的品种鉴别和品质评价奠定基础。
[Key word]
[Abstract]
Objective A method for classification and identification of Rhodiola quadrifida and Rhodiola crenulata was established based on nuclear magnetic resonance 1H-NMR fingerprints-chemical pattern recognition technique. Methods Using high resolution (600 MHz) NMR fingerprints pattern technique, the total component information 1H-NMR fingerprint of R. quadrifida and R. crenulata was determinated, combined with the similarity analysis, hierarchical cluster analysis, principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA) methods for chemical pattern recognition analysis. Results 1H-NMR fingerprints techniques combined with chemical pattern recognition analysis was an effective method to discriminate and identify R. quadrifida and R. crenulata. The difference of the 1H-NMR fingerprint of R. quadrifida and R. crenulata was obvious, which truly and comprehensively reflected the characteristic components and internal qualities of Rhodiola. The main different components of R. quadrifida and R. crenulata were terpenoids and flavonoids, in particular, crenulatin of the terpenoid was a characteristic ingredient in the identification of R. quadrifida and R. crenulata, which can be used as the identification and classification index of R. quadrifida and R. crenulata. Conclusion 1H-NMR fingerprints techniques combined with chemical pattern recognition analysis method is an effective method for classification and identification of Rhodiola, which lays the foundation for variety identification and quality evaluation of medicinal plants of Rhodiola.
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[基金项目]
成都市科学技术局科技惠民技术研发项目(2016-HM01-00339-SF);四川省科学技术厅应用基础研究计划项目(2016JY0247)