Development of a Colorimetric Sensor Array for the Discrimination of Chinese Liquors Based on Selected Volatile Markers Determined by GC-MS

A new colorimetric sensor array was developed for the discrimination of 12 high-alcoholic Chinese base liquors from Luzhou Co., Ltd., and 15 commercial Chinese liquor of different brands as well as flavor types. Seventeen volatile compounds within four chemical groups were determined as markers in t...

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Bibliographic Details
Published in:Journal of agricultural and food chemistry 2014-10, Vol.62 (43), p.10422-10430
Main Authors: Li, Jun-Jie, Song, Chun-Xia, Hou, Chang-Jun, Huo, Dan-Qun, Shen, Cai-Hong, Luo, Xiao-Gang, Yang, Mei, Fa, Huan-Bao
Format: Article
Language:English
Subjects:
acids
aldehydes
chemometrics
cluster analysis
Color
colorimetry
Colorimetry - methods
Discriminant Analysis
esters
factor analysis
flavor
flavor compounds
gas chromatography-mass spectrometry
Gas Chromatography-Mass Spectrometry - methods
principal component analysis
volatile compounds
Volatile Organic Compounds - chemistry
Wine - analysis
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Summary:A new colorimetric sensor array was developed for the discrimination of 12 high-alcoholic Chinese base liquors from Luzhou Co., Ltd., and 15 commercial Chinese liquor of different brands as well as flavor types. Seventeen volatile compounds within four chemical groups were determined as markers in the base liquor by GC-MS analysis and factor analysis method (FAM). A specialized colorimetric sensor array composed of 20 sensitive dots was fabricated accordingly to obtain sensitive interaction with different types of volatile markers. Discrimination of the liquor samples was subsequently performed using chemometric and statistical methods, including principal component analysis (PCA) and hierarchical clustering analysis (HCA). The results suggested that facile identification of either base liquors with high-alcoholic volume or commercial liquors of the same flavor types could be achieved by analysis of the color change profiles. The response of the sensor improved significantly in comparison with those that rely on nonspecific interactions, and no misclassification was observed for both liquor samples using two chemometric methods. Besides, it was also found that the discrimination is closely related to the characteristic flavor compounds (esters, aldehydes, and acids) and alcoholic strength in liquors, and its performance was even comparable with that of GC-MS.
ISSN:0021-8561
1520-5118
DOI:10.1021/jf503345z