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

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-T...

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Autores principales: Ao, Ling, Guo, Kai, Dai, Xinran, Dong, Wei, Sun, Xiaotao, Sun, Baoguo, Sun, Jinyuan, Liu, Guoying, Li, Anjun, Li, Hehe, Zheng, Fuping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9512042/
https://www.ncbi.nlm.nih.gov/pubmed/36172528
http://dx.doi.org/10.3389/fnut.2022.977929
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author Ao, Ling
Guo, Kai
Dai, Xinran
Dong, Wei
Sun, Xiaotao
Sun, Baoguo
Sun, Jinyuan
Liu, Guoying
Li, Anjun
Li, Hehe
Zheng, Fuping
author_facet Ao, Ling
Guo, Kai
Dai, Xinran
Dong, Wei
Sun, Xiaotao
Sun, Baoguo
Sun, Jinyuan
Liu, Guoying
Li, Anjun
Li, Hehe
Zheng, Fuping
author_sort Ao, Ling
collection PubMed
description 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.
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spelling pubmed-95120422022-09-27 Quick classification of strong-aroma types of base Baijiu using potentiometric and voltammetric electronic tongue combined with chemometric techniques Ao, Ling Guo, Kai Dai, Xinran Dong, Wei Sun, Xiaotao Sun, Baoguo Sun, Jinyuan Liu, Guoying Li, Anjun Li, Hehe Zheng, Fuping Front Nutr Nutrition 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. Frontiers Media S.A. 2022-09-12 /pmc/articles/PMC9512042/ /pubmed/36172528 http://dx.doi.org/10.3389/fnut.2022.977929 Text en Copyright © 2022 Ao, Guo, Dai, Dong, Sun, Sun, Sun, Liu, Li, Li and Zheng. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Nutrition
Ao, Ling
Guo, Kai
Dai, Xinran
Dong, Wei
Sun, Xiaotao
Sun, Baoguo
Sun, Jinyuan
Liu, Guoying
Li, Anjun
Li, Hehe
Zheng, Fuping
Quick classification of strong-aroma types of base Baijiu using potentiometric and voltammetric electronic tongue combined with chemometric techniques
title Quick classification of strong-aroma types of base Baijiu using potentiometric and voltammetric electronic tongue combined with chemometric techniques
title_full Quick classification of strong-aroma types of base Baijiu using potentiometric and voltammetric electronic tongue combined with chemometric techniques
title_fullStr Quick classification of strong-aroma types of base Baijiu using potentiometric and voltammetric electronic tongue combined with chemometric techniques
title_full_unstemmed Quick classification of strong-aroma types of base Baijiu using potentiometric and voltammetric electronic tongue combined with chemometric techniques
title_short Quick classification of strong-aroma types of base Baijiu using potentiometric and voltammetric electronic tongue combined with chemometric techniques
title_sort quick classification of strong-aroma types of base baijiu using potentiometric and voltammetric electronic tongue combined with chemometric techniques
topic Nutrition
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9512042/
https://www.ncbi.nlm.nih.gov/pubmed/36172528
http://dx.doi.org/10.3389/fnut.2022.977929
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