Tea classification and quality assessment using laser-induced fluorescence and chemometric evaluation
(2012) In Applied Optics 51(7). p.803-811- Abstract
- Laser-induced fluorescence was used to evaluate the classification and quality of Chinese oolong teas and jasmine teas. The fluorescence of four different types of Chinese oolong teas-Guangdong oolong, North Fujian oolong, South Fujian oolong, and Taiwan oolong was recorded and singular value decomposition was used to describe the autofluoresence of the tea samples. Linear discriminant analysis was used to train a predictive chemometric model and a leave-one-out methodology was used to classify the types and evaluate the quality of the tea samples. The predicted classification of the oolong teas and the grade of the jasmine teas were estimated using this method. The agreement between the grades evaluated by the tea experts and by the... (More)
- Laser-induced fluorescence was used to evaluate the classification and quality of Chinese oolong teas and jasmine teas. The fluorescence of four different types of Chinese oolong teas-Guangdong oolong, North Fujian oolong, South Fujian oolong, and Taiwan oolong was recorded and singular value decomposition was used to describe the autofluoresence of the tea samples. Linear discriminant analysis was used to train a predictive chemometric model and a leave-one-out methodology was used to classify the types and evaluate the quality of the tea samples. The predicted classification of the oolong teas and the grade of the jasmine teas were estimated using this method. The agreement between the grades evaluated by the tea experts and by the chemometric model shows the potential of this technique to be used for practical assessment of tea grades. (C) 2012 Optical Society of America (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2515597
- author
- Mei, Liang LU ; Lundin, Patrik LU ; Brydegaard, Mikkel LU ; Gong, Shuying ; Tang, Desong ; Somesfalean, Gabriel LU ; He, Sailing and Svanberg, Sune LU
- organization
- publishing date
- 2012
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Applied Optics
- volume
- 51
- issue
- 7
- pages
- 803 - 811
- publisher
- Optical Society of America
- external identifiers
-
- wos:000301190000032
- scopus:84857802800
- ISSN
- 2155-3165
- DOI
- 10.1364/AO.51.000803
- language
- English
- LU publication?
- yes
- id
- 810a6043-e6de-422f-8edd-d356870ffd1d (old id 2515597)
- date added to LUP
- 2016-04-01 09:50:07
- date last changed
- 2022-02-17 03:44:15
@article{810a6043-e6de-422f-8edd-d356870ffd1d, abstract = {{Laser-induced fluorescence was used to evaluate the classification and quality of Chinese oolong teas and jasmine teas. The fluorescence of four different types of Chinese oolong teas-Guangdong oolong, North Fujian oolong, South Fujian oolong, and Taiwan oolong was recorded and singular value decomposition was used to describe the autofluoresence of the tea samples. Linear discriminant analysis was used to train a predictive chemometric model and a leave-one-out methodology was used to classify the types and evaluate the quality of the tea samples. The predicted classification of the oolong teas and the grade of the jasmine teas were estimated using this method. The agreement between the grades evaluated by the tea experts and by the chemometric model shows the potential of this technique to be used for practical assessment of tea grades. (C) 2012 Optical Society of America}}, author = {{Mei, Liang and Lundin, Patrik and Brydegaard, Mikkel and Gong, Shuying and Tang, Desong and Somesfalean, Gabriel and He, Sailing and Svanberg, Sune}}, issn = {{2155-3165}}, language = {{eng}}, number = {{7}}, pages = {{803--811}}, publisher = {{Optical Society of America}}, series = {{Applied Optics}}, title = {{Tea classification and quality assessment using laser-induced fluorescence and chemometric evaluation}}, url = {{https://lup.lub.lu.se/search/files/1301996/2969411.pdf}}, doi = {{10.1364/AO.51.000803}}, volume = {{51}}, year = {{2012}}, }