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Characterisation and classification of Citri Reticulatae Pericarpium varieties based on UHPLC-Q-TOF-MS/MS combined with multivariate statistical analyses.

PHYTOCHEMICAL ANALYSIS(2019)

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Abstract
Introduction Citri Reticulatae Pericarpium (CRP), comprising dried pericarps of Citrus reticulata Blanco and its cultivars, is popularly used for its great medicinal and dietary values. Generally, the pericarps from C. reticulate "Chachi" ("Guangchenpi" in Chinese, GCP) is considered to have superior qualities and merit premium price compared with CRP derived from other cultivars (collectively called "Chenpi" in Chinese, CP). Since its multiple origins and derived economic adulteration, it is significant to systematically compare the chemical profiles of different CRP varieties. Objective The main objective of this work was to identify the chemical profiles of CRP from different varieties and find out potential chemical markers for differentiating GCP and CP. Methods In the present study, a total of 42 CRP samples from 10 varieties (including GCP and CP) were analysed by ultra-high performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry (UHPLC-Q-TOF-MS/MS) for chemical profiling. Obtained MS/MS data were further employed in multivariate statistical methods to screen the main compounds which contributed to the characterisation and classification of CRP. Results As a result, 73 compounds (mainly flavonoids) were identified or tentatively characterised in these CRP samples. Based on the obtained chemical profiles data, GCP and CP samples could be easily discriminated from each other by statistical analyses. Moreover, seven compounds were selected as having the most discriminating features which contributed to the classification of CRP. Conclusion This work obtains a better understanding of the chemical profiles of different CRP varieties and provides a practical strategy for the authentication of GCP and CP.
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Key words
Citri Reticulatae Pericarpium,multivariate statistical analyses,UHPLC-Q-TOF-MS,MS
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