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Journal of Chinese Pharmaceutical Sciences ›› 2023, Vol. 32 ›› Issue (5): 406-416.DOI: 10.5246/jcps.2023.05.034

• Original articles • Previous Articles     Next Articles

Establishment of a variety identification system for Fritillaria Thunbergii Bulbus and Fritillaria Cirrhosae Bulbus based on nucleosides and nucleobases with multivariate analysis and pattern recognition

Jinghua Su1, Chao Zhang1,*(), Lei Sun2,*(), Shuangcheng Ma2, Yiwen Xing1   

  1. 1 Suzhou Institute for Drug Control, Suzhou 215104, Jiangsu, China
    2 Chemical Basic Laboratory, School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, China
  • Received:2022-10-27 Revised:2022-11-13 Accepted:2023-12-24 Online:2023-06-02 Published:2023-06-02
  • Contact: Chao Zhang, Lei Sun

Abstract:

Fritillaria Thunbergii Bulbus and Fritillaria Cirrhosae Bulbus have been used as traditional Chinese medicine for thousands of years due to their pharmacological activities. In the present study, multivariate analysis and pattern recognition were applied for the identification of Fritillaria Thunbergii Bulbus and Fritillaria Cirrhosae Bulbus by HPLC. A total of 49 samples from two varieties were collected, and 10 nucleosides and nucleobases were chosen for analysis. Multivariate analyses, such as hierarchical cluster analysis, principal component analysis, and partial least square regression analysis, were used to reveal the correlation between its components and varieties. Moreover, different algorithms in pattern recognition, such as k-nearest neighbor, partial least squares discrimination, soft independent modeling of class analogies, and support vector machine, were applied to identify the species of unknown samples. Results by pattern recognition suggested that the prediction accuracy was satisfactory. A combination of multivariate analysis and pattern recognition was more reasonable, improving the analytical accuracy of variety identification.

Key words: Fritillaria Thunbergii Bulbus, Fritillaria Cirrhosae Bulbus, Multivariate analysis, Pattern recognition, Nucleosides, Nucleobases

Supporting: