@article{LIN2023, 
author = {Xianli LIN and Xiaojuan ZHANG and Chen LI and Lijuan CHAI and Zhenming LU and Hongyu XU and Songtao WANG and Suyi ZHANG and Caihong SHEN and Jingsong SHI and Zhenghong XU},
title = {Discriminant Analysis of Jiang-Flavor Baijiu of Different Grades by Gas Chromatography-Mass Spectrometry and Electronic Tongue},
year = {2023},
journal = {Food Science},
volume = {44},
number = {24},
pages = {329-338},
keywords = {Jiang-flavor baijiu, gas chromatography-mass spectrometry, electronic tongue, chemometrics, discriminant models},
url = {https://www.sciopen.com/article/10.7506/spkx1002-6630-20230115-117},
doi = {10.7506/spkx1002-6630-20230115-117},
abstract = {Gas chromatography-mass spectrometry (GC-MS) and electronic tongue were used to quantitatively determine the volatile compounds and taste indices of 21 Jiang-flavor baijiu samples of different grades. These samples were differentiated by chemometrics, and key differential compounds among grades were identified. Finally, a discriminant model was established by machine learning. The results showed that there were differences in the contents of volatile compounds in Jiang-flavor baijiu of three grades, indicating the feasibility of further discriminant analysis. The total content of flavor compounds in second-grade baijiu (4908 mg/L) was significantly lower than that in premium-grade (6583 mg/L) and first-grade baijiu (8254 mg/L), while the proportion of several esters responsible for floral and fruity aromas in total esters showed a decreasing trend as the grade decreased. Partial least squares-discriminant analysis (PLS-DA) identified 16 key differential compounds represented by ethyl palmitate and acetic acid. The results of electronic tongue showed that the taste indexes of premium-grade baijiu were more consistent, with lower bitterness and astringency aftertaste. The taste indexes of second-grade baijiu showed significant intersample differences. Principal component analysis (PCA) showed clear discrimination of Jiang-flavor baijiu of different grades according to their taste indexes. The above results provide a basis for the establishment of Jiang-flavor baijiu quality system. Four discriminant models were established based on 25 differential compounds and taste indexes identified. The accuracy of all models was higher than 90%, and the support vector machine (SVM) model performed best, with an accuracy of 100%.}
}