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Protected Geographical Indication Identification of a Chinese Green Tea (Anji-White) by Near-Infrared Spectroscopy and Chemometric Class Modeling Techniques
Joint Authors
Yu, Xiao-Ping
Fu, Xian-Shu
Cai, Chen-Bo
Xu, Lu
Cui, Hai-Feng
Shi, Peng-Tao
Ye, Zi-Hong
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-10-16
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
This paper reports a rapid identification method for a Chinese green tea with PGI, Anji-white tea, by class modeling techniques and NIR spectroscopy.
167 real and representative Anji-white tea samples were collected from 8 tea plantations in their original producing areas for model training.
Another 81 non-Anji-white tea samples of similar appearance were collected from 7 important tea producing areas and used for validation of model specificity.
Diffuse NIR spectra were measured with finely ground tea powders.
OCPLS and SIMCA were used to describe the distribution of representative Anji-white tea objects and predict the authenticity of new objects.
For data preprocessing, smoothing, derivatives, and SNV were applied to improve the raw spectra and classification performance.
It is demonstrated that taking derivatives and SNV can improve classification accuracy and reduce the complexity of class models by removing spectral background and baseline.
For the best models, the sensitivity and specificity were 0.886 and 0.951 for OCPLS, 0.886 and 0.938 for SIMCA with SNV spectra, respectively.
Although it is difficult to perform an exhaustive analysis of all types of potential false objects, the proposed method can detect most of the important non-Anji-white teas in the Chinese market.
American Psychological Association (APA)
Xu, Lu& Shi, Peng-Tao& Fu, Xian-Shu& Cui, Hai-Feng& Ye, Zi-Hong& Cai, Chen-Bo…[et al.]. 2012. Protected Geographical Indication Identification of a Chinese Green Tea (Anji-White) by Near-Infrared Spectroscopy and Chemometric Class Modeling Techniques. Journal of Spectroscopy،Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-476638
Modern Language Association (MLA)
Xu, Lu…[et al.]. Protected Geographical Indication Identification of a Chinese Green Tea (Anji-White) by Near-Infrared Spectroscopy and Chemometric Class Modeling Techniques. Journal of Spectroscopy No. 2013 (2013), pp.1-8.
https://search.emarefa.net/detail/BIM-476638
American Medical Association (AMA)
Xu, Lu& Shi, Peng-Tao& Fu, Xian-Shu& Cui, Hai-Feng& Ye, Zi-Hong& Cai, Chen-Bo…[et al.]. Protected Geographical Indication Identification of a Chinese Green Tea (Anji-White) by Near-Infrared Spectroscopy and Chemometric Class Modeling Techniques. Journal of Spectroscopy. 2012. Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-476638
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-476638