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Article: Ultra-performance LC/TOF MS analysis of medicinal Panax herbs for metabolomic research

TitleUltra-performance LC/TOF MS analysis of medicinal Panax herbs for metabolomic research
Authors
KeywordsMetabolite profiling
Multivariate statistical analysis
Panax
Saponin
UPLC-TOFMS
Issue Date2008
Citation
Journal of Separation Science, 2008, v. 31, n. 6-7, p. 1015-1026 How to Cite?
AbstractIn this study, metabolite profiling of five medicinal Panax herbs including Panax ginseng (Chinese ginseng), Panax notoginseng (Sanchi), Panax japonicus (Rhizoma Panacis Majoris), Panax quinquefolium L. (American ginseng), and P. ginseng (Korean ginseng) were performed using ultra-performance LC-quadrupole TOF MS (UPLC-QTOFMS) and multivariate statistical analysis technique. Principal component analysis (PCA) of the analytical data showed that the five Panax herbs could be separated into five different groups of phytochemicals. The chemical markers such as ginsenoside Rf, 20(S)-pseudoginsenoside F11, malonyl gisenoside Rb1, and gisenoside Rb2 accountable for such variations were identified through the loadings plot of PCA, and were identified tentatively by the accurate mass of TOFMS and partially verified by the available reference standards. Results from this study indicate that the proposed method is reliable for the rapid analysis of a group of metabolites present in herbal medicines and other natural products and applicable in the differentiation of complex samples that share similar chemical ingredients. © 2008 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Persistent Identifierhttp://hdl.handle.net/10722/342229
ISSN
2021 Impact Factor: 3.614
2020 SCImago Journal Rankings: 0.720
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXie, Guoxiang-
dc.contributor.authorPlumb, Robert-
dc.contributor.authorSu, Mingming-
dc.contributor.authorXu, Zhaohui-
dc.contributor.authorZhao, Aihua-
dc.contributor.authorQiu, Mingfeng-
dc.contributor.authorLong, Xiangbao-
dc.contributor.authorLiu, Zhong-
dc.contributor.authorJia, We-
dc.date.accessioned2024-04-17T07:02:11Z-
dc.date.available2024-04-17T07:02:11Z-
dc.date.issued2008-
dc.identifier.citationJournal of Separation Science, 2008, v. 31, n. 6-7, p. 1015-1026-
dc.identifier.issn1615-9306-
dc.identifier.urihttp://hdl.handle.net/10722/342229-
dc.description.abstractIn this study, metabolite profiling of five medicinal Panax herbs including Panax ginseng (Chinese ginseng), Panax notoginseng (Sanchi), Panax japonicus (Rhizoma Panacis Majoris), Panax quinquefolium L. (American ginseng), and P. ginseng (Korean ginseng) were performed using ultra-performance LC-quadrupole TOF MS (UPLC-QTOFMS) and multivariate statistical analysis technique. Principal component analysis (PCA) of the analytical data showed that the five Panax herbs could be separated into five different groups of phytochemicals. The chemical markers such as ginsenoside Rf, 20(S)-pseudoginsenoside F11, malonyl gisenoside Rb1, and gisenoside Rb2 accountable for such variations were identified through the loadings plot of PCA, and were identified tentatively by the accurate mass of TOFMS and partially verified by the available reference standards. Results from this study indicate that the proposed method is reliable for the rapid analysis of a group of metabolites present in herbal medicines and other natural products and applicable in the differentiation of complex samples that share similar chemical ingredients. © 2008 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.-
dc.languageeng-
dc.relation.ispartofJournal of Separation Science-
dc.subjectMetabolite profiling-
dc.subjectMultivariate statistical analysis-
dc.subjectPanax-
dc.subjectSaponin-
dc.subjectUPLC-TOFMS-
dc.titleUltra-performance LC/TOF MS analysis of medicinal Panax herbs for metabolomic research-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/jssc.200700650-
dc.identifier.pmid18338405-
dc.identifier.scopuseid_2-s2.0-43249119417-
dc.identifier.volume31-
dc.identifier.issue6-7-
dc.identifier.spage1015-
dc.identifier.epage1026-
dc.identifier.eissn1615-9314-
dc.identifier.isiWOS:000255613800014-

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