Discrimination of teas based on total luminescence spectroscopy and pattern recognition  

Hdl Handle:
http://hdl.handle.net/10149/58375
Title:
Discrimination of teas based on total luminescence spectroscopy and pattern recognition  
Authors:
Seetohul, L. N. (Nitin); Islam, M. (Meezanul); O'Hare, W. T. (Liam); Ali, Z. (Zulfiqur)
Affiliation:
University of Teesside. School of Science and Technology.
Citation:
Seetohul, L. N. et al. (2006) 'Discrimination of teas based on total luminescence spectroscopy and pattern recognition', Journal of the Science of Food and Agriculture, 86 (13), pp.2092-2098.
Publisher:
Wiley Blackwell
Journal:
Journal of the Science of Food and Agriculture
Issue Date:
Jul-2006
URI:
http://hdl.handle.net/10149/58375
DOI:
10.1002/jsfa.2578
Abstract:
This paper reports on the application of total luminescence spectroscopy to discriminate between seven different types of tea: four bottled liquid Japanese teas (oolong, green, houji and black teas) and three leaf teas (Kenya, Assam and Ceylon teas). Total luminescence spectra were recorded by measuring the emission spectra in the range 300–700nm at excitation wavelengths from 250 to 590 nm. Discrimination of teas based on their spectral data was performed by principal component analysis, a common chemometric method used for data reduction and visualisation. The results demonstrate the ability of fluorescence techniques to differentiate between green tea (unfermented), black tea (fermented) and oolong tea (partially fermented).
Type:
Article
Keywords:
total luminescence; tea classification; green tea; oolong tea; black tea; houji tea; Japanese tea; leaf tea; pattern recognition; spectroscopy
ISSN:
1097-0010
Rights:
Subject to restrictions, author can archive post-print (ie final draft post-refereeing). For full details see http://www.sherpa.ac.uk/romeo/ [Accessed 18/12/09]
Citation Count:
6 [Scopus, 18/12/09]

Full metadata record

DC FieldValue Language
dc.contributor.authorSeetohul, L. N. (Nitin)-
dc.contributor.authorIslam, M. (Meezanul)-
dc.contributor.authorO'Hare, W. T. (Liam)-
dc.contributor.authorAli, Z. (Zulfiqur)-
dc.date.accessioned2009-04-01T10:50:26Z-
dc.date.available2009-04-01T10:50:26Z-
dc.date.issued2006-07-
dc.identifier.citationJournal of the Science of Food and Agriculture; 86 (13): 2092-2098-
dc.identifier.issn1097-0010-
dc.identifier.doi10.1002/jsfa.2578-
dc.identifier.urihttp://hdl.handle.net/10149/58375-
dc.description.abstractThis paper reports on the application of total luminescence spectroscopy to discriminate between seven different types of tea: four bottled liquid Japanese teas (oolong, green, houji and black teas) and three leaf teas (Kenya, Assam and Ceylon teas). Total luminescence spectra were recorded by measuring the emission spectra in the range 300–700nm at excitation wavelengths from 250 to 590 nm. Discrimination of teas based on their spectral data was performed by principal component analysis, a common chemometric method used for data reduction and visualisation. The results demonstrate the ability of fluorescence techniques to differentiate between green tea (unfermented), black tea (fermented) and oolong tea (partially fermented).-
dc.publisherWiley Blackwell-
dc.rightsSubject to restrictions, author can archive post-print (ie final draft post-refereeing). For full details see http://www.sherpa.ac.uk/romeo/ [Accessed 18/12/09]-
dc.subjecttotal luminescence-
dc.subjecttea classification-
dc.subjectgreen tea-
dc.subjectoolong tea-
dc.subjectblack tea-
dc.subjecthouji tea-
dc.subjectJapanese tea-
dc.subjectleaf tea-
dc.subjectpattern recognition-
dc.subjectspectroscopy-
dc.titleDiscrimination of teas based on total luminescence spectroscopy and pattern recognition  -
dc.typeArticle-
dc.contributor.departmentUniversity of Teesside. School of Science and Technology.-
dc.identifier.journalJournal of the Science of Food and Agriculture-
ref.assessmentRAE 2008-
ref.citationcount6 [Scopus, 18/12/09]-
or.citation.harvardSeetohul, L. N. et al. (2006) 'Discrimination of teas based on total luminescence spectroscopy and pattern recognition', Journal of the Science of Food and Agriculture, 86 (13), pp.2092-2098.-
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