Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/92367
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Title: Rapid differentiation of Ganoderma species by direct ionization mass spectrometry
Authors: Wong, HY 
Wong, MYM 
Hu, B 
So, PK 
Chan, CO 
Mok, DKW 
Yao, ZP 
Issue Date: Jan-2018
Source: Analytica chimica acta, 25 Jan. 2018, v. 999, p. 99-106
Abstract: In this study, direct ionization mass spectrometry (DI-MS) has been developed for rapid differentiation of Ganoderma (known as Lingzhi in Chinese), a very popular and valuable herbal medicine. Characteristic mass spectra can be generated by DI-MS directly from the raw herbal medicines with the application of a high voltage and solvents. Rapid differentiation of the Ganoderma species that are officially stated in the Chinese pharmacopoeia from easily confused Ganoderma species could be achieved based on this method, as the acquired DI-MS spectra showed that ganoderic acids, the major active components of Ganoderma, could be found only in the official Ganoderma species but not in the confused Ganoderma species. In addition, classification of wild and cultivated Ganoderma and potential differentiation of Ganoderma from different geographical locations could be accomplished based on principal component analysis (PCA) or hierarchical clustering analysis (HCA). The method is rapid, simple and reproducible, and can be further extended to analysis of other herbal medicines.
Keywords: Active components
Differentiation
Direct ionization
Ganoderma
Mass spectrometry
Publisher: Elsevier
Journal: Analytica chimica acta 
ISSN: 0003-2670
DOI: 10.1016/j.aca.2017.11.006
Rights: © 2017 Elsevier B.V. All rights reserved.
© 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
The following publication Wong, H. Y., Wong, M. Y. M., Hu, B., So, P. K., Chan, C. O., Mok, D. K. W., & Yao, Z. P. (2018). Rapid differentiation of Ganoderma species by direct ionization mass spectrometry. Analytica chimica acta, 999, 99-106 is available at https://dx.doi.org/10.1016/j.aca.2017.11.006
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