Discrimination of Chinese green tea according to varieties and grade levels using artificial nose and tongue based on colorimetric sensor arrays

Abstract

Colorimetric artificial tongue and nose were used to discriminate nine Chinese green teas from different geographical origins and grade levels. Printing nanoporous porphyrin, dimeric metalloporphyrins, metallosalophen complexes and chemically responsive dyes on a hydrophobic membrane, the developed sensor array of artificial tongue and nose showed a unique pattern of colorimetric change upon exposure to green tea liquids or gases. All green tea samples, both in liquid and gas analysis, gave distinct patterns according to geographical origin and grade level, thus resulting in their facile identification. The good reproducibility of colorimetric artificial tongue and nose was proved. Data analysis was performed by chemometric techniques: hierarchical cluster analysis (HCA), and principal component analysis (PCA). Chinese green tea from the same geographical origin could cluster together in PCA score plot. No errors in classification by HCA were observed in 90 trials. The colorimetric artificial tongue and nose can be used to discriminate Chinese green tea according to geographical origin and grade level.