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. 2022 Sep 12:9:977929.
doi: 10.3389/fnut.2022.977929. eCollection 2022.

Quick classification of strong-aroma types of base Baijiu using potentiometric and voltammetric electronic tongue combined with chemometric techniques

Affiliations

Quick classification of strong-aroma types of base Baijiu using potentiometric and voltammetric electronic tongue combined with chemometric techniques

Ling Ao et al. Front Nutr. .

Abstract

Nowadays, the classification of strong-aroma types of base Baijiu (base SAB) is mainly achieved by human sensory evaluation. However, prolonged tasting brings difficulties for sommeliers in guaranteeing the consistency of results, and may even cause health problems. Herein, an electronic tongue (E-Tongue) combined with a gas chromatography-mass spectrometry (GC-MS) method was successfully developed to grade high-alcoholic base SAB. The E-tongue was capable of identifying base SAB samples into four grades by a discriminant function analysis (DFA) model based on human sensory evaluation results. More importantly, it could effectively and rapidly predict the quality grade of unknown base SAB with an average accuracy up to 95%. The differences of chemical components between base SAB samples were studied by the GC-MS analysis and 52 aroma compounds were identified. The qualitative and quantitative results showed that with the increase of base SAB grade, the varieties and contents of aroma compounds increased. Overall, the comprehensive analysis of E-tongue data and GC-MS results could be in good agreement with human sensory evaluation results, which also proved that the newly developed method has a potential to be a useful alternative to the overall quality grading of base Baijiu.

Keywords: GC-MS; discriminant function analysis; electronic tongue; principal component analysis; strong-aroma types of base Baijiu.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Multivariate statistical analysis based on the result of the Smartongue analysis: loading plot of (A) principal component analysis (PCA) and (B) discriminant function analysis (DFA) for the classification of 120 strong-aroma types of base Baijiu (base SAB) samples from four different grades.
FIGURE 2
FIGURE 2
The established DFA model map was verified by 20 real SAB samples.

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