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ORIGINAL ARTICLE
Year : 2021  |  Volume : 7  |  Issue : 1  |  Page : 104-110

Discrimination of five species of Panax genus and their geographical origin using electronic tongue combined with chemometrics


1 Engineering Research Center of Chinese Medicine Resource, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
2 College of Science, Sichuan Agricultural University, Yaan, Sichuan, China
3 Centre for Biotechnology and Microbiology, University of Peshawar, Pakistan

Correspondence Address:
Prof. Lin-Fang Huang
Institute of Medicinal Plant Development, No. 151 Malianwa North Road, Haidian District, Beijing 100193
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/wjtcm.wjtcm_80_20

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Objective: Authentication is vital to the reduction of the misuse of Panax species due to their extensive array of uses and similarities between species. However, the current authentication approach is time-consuming, laborious, and costly. The aim of this study is to discriminate the botanical origins of five species in Panax genus by a rapid and simple approach. Methods: Here, an electronic tongue (E-tongue) was applied to discriminate the botanical origins of five species of Panax, i.e., Panax quinquefolius, Panax japonicus, P. japonicus var. major, Panax zingiberensis, and Panax notoginseng (representative high-, middle-, and low-latitude plants), and the four geographical origins of P.japonicus and P. japonicus var. major plants. Data preprocessing methods, including principal component analysis (PCA), hierarchical cluster analysis (HCA), and linear discriminant analysis (LDA), were used. Results: Three models can discriminate five species of Panax genus and four plants of P. japonicus and P. japonicus var. major from different geographical origins. LDA was superior to PCA and HCA in terms of satisfactory classification. Conclusion: The findings confirmed the potential of the E-tongue for performing rapid, simple, and cost-effective discrimination via LDA.


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