NATURAL PRODUCT RESEARCH AND DEVELOPMENT ›› 2019, Vol. 31 ›› Issue (10): 1675-1681. doi: 10.16333/j.1001-6880.2019.10.002

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The study of HPLC fingerprint and chemical pattern recognition of Lycii fructus

LIU Xu-xia1,2,PEI Dong3,LIU Jian-fei1,GONG Yuan1,WANG Mao-he1,2,DI Duo-long1*,GUO Mei2*   

  1. 1Key Laboratory of Chemistry of Northwestern Plant Resources and Key Laboratory for Natural Medicine of Gansu Province,Lanzhou Institute of Chemical Physics,Chinese Academy of Sciences;2School of Pharmacy,Gansu Uiniversity of Traditional Chinese Medicine,Provincial Key Laboratory of Medicinal Chemistry and Quality Research in Gansu Province,Lanzhou 730000,China;3Qingdao Center of Resource Chemistry & New Materials,Qingdao 266000,China;

  • Online:2019-10-28 Published:2019-11-11

Abstract: The aim of this work is to establish a HPLC fingerprint and region identification model of Lycii fructus,and to providie reference for prediction of samples production areas.The analysis was performed on an Elite Sepherisorb ODS C18 (250 mm × 4.6 mm,5 μm) column.The mobile phase was consisted of water containing 0.3% glacial acetic acid and acetonitrile.The column temperature was set as 25 ℃.The flow rate was 1.0 mL/min and the detection wavelength was 310 nm.The similarities of Lycii fructus samples (34 batches collected from five different production areas) were evaluated by the software of "Similarity Evaluation System for Chromatographic Fingerprint of TCMs (2012 version)".The cluster analysis (CA),principal component analysis (PCA) and orthogonal partial least squares (OPLS) analysis were performed by the SIMCA 14.1 software.In this study,28 common peaks in the HPLC fingerprints were determined.The similarity evaluation results indicated that the Lycii fructus samples of different origins have significant differences due to the variously geographical and ecological environment of the production areas.The results of cluster analysis showed that Lycii fructus samples from the same production area can be well clustered into one class.Principal component analysis determined that P12,P23 and P26 were the differential compounds of samples from different areas.The discrimination model of the production areas was established by orthogonal partial least squares method.The model discrimination rate was 89.0%,and the Lycii fructus samples of nine production areas were accurately predicted.This method is simple,stable and reliable.And it can be used for prediction of Lycii fructus from different production area.

Key words: Lycii fructus, fingerprint, principal component analysis, orthogonal partial least squares analysis, production areas

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