Nondestructive identification of tea (Camellia sinensis L.) varieties using FT-NIR spectroscopy and pattern recognition

Quansheng Chen, Jiewen Zhao, Muhua Liu and Jianrong Cai
Additional contact information
Quansheng Chen: School of Food & Biological Engineering, Jiangsu University, Zhenjiang, P. R. China
Jiewen Zhao: School of Food & Biological Engineering, Jiangsu University, Zhenjiang, P. R. China
Muhua Liu: Engineering College, Jiangxi Agricultural University, Nanchang, P. R. China
Jianrong Cai: School of Food & Biological Engineering, Jiangsu University, Zhenjiang, P. R. China

Czech Journal of Food Sciences, 2008, vol. 26, issue 5, 360-367

Abstract: Due to more and more tea varieties in the current tea market, rapid and accurate identification of tea (Camellia sinensis L.) varieties is crucial to the tea quality control. Fourier Transform Near-Infrared (FT-NIR) spectroscopy coupled with the pattern recognition was used to identify individual tea varieties as a rapid and non-invasive analytical tool in this work. Seven varieties of Chinese tea were studied in the experiment. Linear Discriminant Analysis (LDA) and Artificial Neural Network (ANN) were compared to construct the identification models based on Principal Component Analysis (PCA). The number of principal components factors (PCs) was optimised in the constructing model. The experimental results showed that the performance of ANN model was better than LDA models. The optimal ANN model was achieved when four PCs were used, identification rates being all 100% in the training and prediction sets. The overall results demonstrated that FT-NIR spectroscopy technology with ANN pattern recognition method can be successfully applied as a rapid method to identify tea varieties.

Keywords: green tea; variety; identification; FT-NIR spectroscopy; pattern recognition (search for similar items in EconPapers)
Date: 2008
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://cjfs.agriculturejournals.cz/doi/10.17221/1125-CJFS.html (text/html)
http://cjfs.agriculturejournals.cz/doi/10.17221/1125-CJFS.pdf (application/pdf)
free of charge

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:caa:jnlcjf:v:26:y:2008:i:5:id:1125-cjfs

DOI: 10.17221/1125-CJFS

Access Statistics for this article

Czech Journal of Food Sciences is currently edited by Ing. Zdeňka Náglová Ph.D.

More articles in Czech Journal of Food Sciences from Czech Academy of Agricultural Sciences
Bibliographic data for series maintained by Ivo Andrle ().