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dc.contributor.authorCzerniec-Michalik, Ewelinaen_US
dc.contributor.authorHsieh, Kai-Taen_US
dc.contributor.authorUrban, Pawel L.en_US
dc.date.accessioned2014-12-08T15:35:57Z-
dc.date.available2014-12-08T15:35:57Z-
dc.date.issued2014en_US
dc.identifier.issn1759-9660en_US
dc.identifier.urihttp://hdl.handle.net/11536/24321-
dc.identifier.urihttp://dx.doi.org/10.1039/c3ay42009den_US
dc.description.abstractIt is of great economical and practical significance to distinguish between different classes, brands, and places of origin of commercial tea. Herein, an analytical method has been developed to characterize samples of oriental teas (with an emphasis on Taiwanese teas). It is based on the implementation of liquid chromatography coupled with mass spectrometry along with chemometric data treatment. Prior to chemometric classification, datasets (for over 80 samples) were subjected to an exhaustive pretreatment procedure in order to select potential chemomarker signals according to their variability within pre-defined groups of samples. Statistical analysis further revealed differences in the composition of the teas originating from plantations in Taiwan and other countries as well as the teas belonging to the major classes defined by the degree of fermentation. The greatest differences relate to the content of caffeine and epi/catechin represented by the mass spectrometric signals at the m/z 195.0 and 291.0, respectively. The proposed analytical workflow provides a convenient tool to reveal differences in the chemical composition of multi-component real samples such as plant tissue extracts.en_US
dc.language.isoen_USen_US
dc.titleIn quest for chemomarkers to classify Taiwanese teasen_US
dc.typeArticleen_US
dc.identifier.doi10.1039/c3ay42009den_US
dc.identifier.journalANALYTICAL METHODSen_US
dc.citation.volume6en_US
dc.citation.issue9en_US
dc.citation.spage3013en_US
dc.citation.epage3018en_US
dc.contributor.department應用化學系zh_TW
dc.contributor.departmentDepartment of Applied Chemistryen_US
dc.identifier.wosnumberWOS:000334736500027-
dc.citation.woscount0-
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