Colorimetric artificial nose for identification of Chinese liquor with different geographic origins

Abstract

Colorimetric artificial nose was used to characterize and identify Chinese liquors from six different geographic origins. Using chemical dyes as the sensing elements, the developed colorimetric artificial nose showed a unique pattern of color changes upon its exposure to Chinese liquors. Data analysis was performed by chemometric techniques: Hierarchical cluster analysis (HCA), principal component analysis (PCA) and linear discriminant analysis (LDA). Each category of Chinese liquor could cluster together in PCA score plot. No errors in classification by HCA were observed in 45 trials. LDA model showed a 100% of prediction ability for Chinese liquor. The results demonstrated that colorimetric artificial nose was able to classify Chinese liquors from different geographic origins.