Dai L, Yang L, Li Y, Li S, Yang D, Li Y, He D. Origin differentiation based on volatile constituents of genuine medicinal materials Quisqualis indica L. via HS-GC-MS, response surface methodology, and chemometrics.
PHYTOCHEMICAL ANALYSIS : PCA 2024;
35:567-578. [PMID:
38191129 DOI:
10.1002/pca.3313]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 11/27/2023] [Accepted: 11/28/2023] [Indexed: 01/10/2024]
Abstract
INTRODUCTION
Quisqualis indica L. (QIL) has a long history as a traditional Chinese herb in China, but the study of volatile components in QIL from different geographical sources has been relatively rare.
OBJECTIVES
To establish an optimal headspace gas chromatography-mass spectrometry (HS-GC-MS) method to comprehensively analyse the volatile component profile and screen quality markers of QIL from different origins.
METHODS
Response surface methodology (RSM) was used to optimise the conditions for headspace analysis. The volatile components of QIL from four main origins of southwest China were analysed and identified by HS-GC-MS. The similarity of all samples of QIL was evaluated by fingerprint. The differences of the volatile components in QIL from different origins were distinguished by chemometrics.
RESULTS
According to the optimal conditions of RSM, a total of 31 volatile components were identified, including fatty acids, aldehydes, alcohols, alkyl pyrazines, and other volatile components. Similarity evaluation presented that there were 26 common volatile components with different contents in all samples. Principal component analysis (PCA) showed that QIL from four different origins could be roughly divided into four categories. Hierarchical cluster analysis (HCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) indicated that QIL from different origins had obvious regional characteristics.
CONCLUSION
The optimised HS-GC-MS method provided a strategy to rapidly, effectively, and accurately elucidate the volatile component profile of QIL from different origins, and seven important differential components were screened for quality evaluation and origin traceability.
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