Ikeda Tatsuhiko, Kanaya Shigehiko, Yonetani Tsutomu, Kobayashi Akio, Fukusaki Eiichiro
Department of Biotechnology, Osaka University, Japan.
J Agric Food Chem. 2007 Nov 28;55(24):9908-12. doi: 10.1021/jf0717642. Epub 2007 Nov 1.
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.
利用傅里叶变换近红外（FT-NIR）反射光谱和代谢组学技术，开发了一种快速简便的绿茶品质测定方法。该方法应用于绿茶品质的在线测量和在线预测。采用FT-NIR测量受绿茶品种和加工工艺影响的绿茶代谢产物变化。分析了一组来自日本商业茶比赛的排名绿茶样品，以创建可靠的品质预测模型。作为多元分析，使用了主成分分析（PCA）和偏最小二乘判别分析（PLS）。结果表明，5500至5200 cm(-1)的波数区域与茶叶品质具有高度相关性。在本研究中，已建立了可靠的绿茶品质预测模型。
