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Geographical Authentication of Gentiana Rigescens by High-Performance Liquid Chromatography and Infrared Spectroscopy

文献类型： 外文期刊

作者： Wang, Ye 1 ; Shen, Tao 3 ; Zhang, Ji 2 ; Huang, Heng-Yu 1 ; Wang, Yuan-Zhong 2 ;

作者机构： 1.Yunnan Univ Tradit Chinese Med, Coll Tradit Chinese Med, Kunming, Yunnan, Peoples R China

2.Yunnan Acad Agr Sci, Inst Med Plants, 2238 Beijing Rd, Kunming 650200, Yunnan, Peoples R China

3.Yuxi Normal Univ, Coll Resources & Environm, Yuxi, Peoples R China

关键词： Chemometrics; Gentiana rigescens; geographical authentication; high-performance liquid chromatography; infrared spectroscopy; partial least square discrimination analysis

期刊名称：ANALYTICAL LETTERS （ 影响因子：2.329； 五年影响因子：1.738 ）

ISSN： 0003-2719

年卷期： 2018 年 51 卷 14 期

页码：

收录情况： SCI

摘要： The chemical characteristics of Gentiana rigescens are extremely variable due to their geographical origins which should be determined to evaluate the quality of this species. Different with other herbs with official tissue for classification materials, the geographical characterization of raw herbal materials on the basis of nonmedicinal parts is rarely discussed. Chromatographic active components were used as references to characterize the chemical profiles of samples from various geographical origins. Based on spectra data matrix of different botanical parts, the chemometric methods of partial least square discrimination analysis and support vector machine discrimination analysis were used to develop mathematical models to classify samples from different geographical origins. In terms of six active components, we found that significant differences were present in the tissue of G. rigescens based on geographical origins. In addition, the region with higher content of gentiopicroside was selected to be the optimal cultivated location. Chemometric results indicated that leaves were the optimal material for geographical characterization of G. rigescens with 100% accuracy by support vector machine while the accuracies of roots, stems, and flowers were 90.91, 96.10, and 97.01%, respectively. Partial least square discrimination analysis showed that accuracy values for roots, stems, leaves, and flowers were 35.65, 67.53, 76.62, and 50.75%, respectively, which also indicated that leaves are the optimal material. In conclusion, northwest Yunnan Province with higher content of gentiopicroside was selected to be the optimal cultivation location. Furthermore, leaves should be used for the most accurate geographical authentication.

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