title: Prediction of Japanese green tea ranking by fourier transform near-infrared reflectance spectroscopy.
abstract: A rapid and easy determination method of green tea's quality was developed by using Fourier transform near-infrared (FT-NIR) reflectance spectroscopy and metabolomics techniques. The method is applied to an online measurement and an online prediction of green tea's quality. FT-NIR was employed to measure green tea metabolites' alteration affected by green tea varieties and manufacturing processes. A set of ranked green tea samples from a Japanese commercial tea contest was analyzed to create a reliable quality-prediction model. As multivariate analyses, principal component analysis (PCA) and partial least-squares projections to latent structures (PLS) were used. It was indicated that the wavenumber region from 5500 to 5200 cm(-1) had high correlation with the quality of the tea. In this study, a reliable quality-prediction model of green tea has been achieved.
authors.affiliation: Department of Biotechnology, Osaka University, Japan.
authors.forename: Tatsuhiko
authors.initials: T
authors.lastname: Ikeda
authors.forename: Shigehiko
authors.initials: S
authors.lastname: Kanaya
authors.forename: Tsutomu
authors.initials: T
authors.lastname: Yonetani
authors.forename: Akio
authors.initials: A
authors.lastname: Kobayashi
authors.forename: Eiichiro
authors.initials: E
authors.lastname: Fukusaki
mesh_terms: D006801:Humans; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D025341:Principal Component Analysis; D011786:Quality Control; D012680:Sensitivity and Specificity; D017550:Spectroscopy, Fourier Transform Infrared / Q000379:methods*; D013662:Tea / Q000737:chemistry* / Q000592:standards*
chemical_list: D013662:Tea