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Mid-Infrared Spectroscopy for Coffee Variety Identification: Comparison of Pattern Recognition Methods
Joint Authors
He, Yong
Zhang, Chu
Wang, Chang
Liu, Fei
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-01-20
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
The potential of using mid-infrared transmittance spectroscopy combined with pattern recognition algorithm to identify coffee variety was investigated.
Four coffee varieties in China were studied, including Typica Arabica coffee from Yunnan Province, Catimor Arabica coffee from Yunnan Province, Fushan Robusta coffee from Hainan Province, and Xinglong Robusta coffee from Hainan Province.
Ten different pattern recognition methods were applied on the optimal wavenumbers selected by principal component analysis loadings.
These methods were classified as highly effective methods (soft independent modelling of class analogy, support vector machine, back propagation neural network, radial basis function neural network, extreme learning machine, and relevance vector machine), methods of medium effectiveness (partial least squares-discrimination analysis, K nearest neighbors, and random forest), and methods of low effectiveness (Naive Bayes classifier) according to the classification accuracy for coffee variety identification.
American Psychological Association (APA)
Zhang, Chu& Wang, Chang& Liu, Fei& He, Yong. 2016. Mid-Infrared Spectroscopy for Coffee Variety Identification: Comparison of Pattern Recognition Methods. Journal of Spectroscopy،Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1110802
Modern Language Association (MLA)
Zhang, Chu…[et al.]. Mid-Infrared Spectroscopy for Coffee Variety Identification: Comparison of Pattern Recognition Methods. Journal of Spectroscopy No. 2016 (2016), pp.1-7.
https://search.emarefa.net/detail/BIM-1110802
American Medical Association (AMA)
Zhang, Chu& Wang, Chang& Liu, Fei& He, Yong. Mid-Infrared Spectroscopy for Coffee Variety Identification: Comparison of Pattern Recognition Methods. Journal of Spectroscopy. 2016. Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1110802
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1110802