Literature DB >> 30744861

A novel method for classification of wine based on organic acids.

Miodrag Milovanovic1, Jiří Žeravík1, Michal Obořil1, Marta Pelcová1, Karel Lacina2, Uros Cakar3, Aleksandar Petrovic4, Zdeněk Glatz1, Petr Skládal5.   

Abstract

Bio-electronic tongue was linked to artificial intelligence processing unit and used for classification of wines based on carboxylic acids levels, which were indirectly related to malolactic fermentation. The system employed amperometric biosensors with lactate oxidase, sarcosine oxidase, and fumarase/sarcosine oxidase in the three sensing channels. The results were processed using two statistical methods - principal component analysis (PCA) and self-organized maps (SOM) in order to classify 31 wine samples from the South Moravia region in the Czech Republic. Reference assays were carried out using the capillary electrophoresis (CE). The PCA patterns for both CE and biosensor data provided good correspondence in the clusters of samples. The SOM treatment provided a better resolution of the generated patterns of samples compared to PCA, the SOM derived clusters corresponded with the PCA classification only partially. The biosensor/SOM combination offers a novel procedure of wine classification.
Copyright © 2019 Elsevier Ltd. All rights reserved.

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Keywords:  Acetic acid (PubChem CID: 176); Biosensor; Capillary electrophoresis; Carboxylic acids; Citric acid (PubChem CID: 311); Oxaloacetic acid (PubChem CID: 970); Principal component analysis; Self-organizing map; Succinic acid (PubChem CID: 1110); l-Lactic acid (PubChem CID: 107689); l-Malic acid (PubChem CID: 222656); l-Tartaric acid (PubChem CID: 444305)

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Year:  2019        PMID: 30744861     DOI: 10.1016/j.foodchem.2019.01.113

Source DB:  PubMed          Journal:  Food Chem        ISSN: 0308-8146            Impact factor:   7.514


  1 in total

1.  Fuzzy Evaluation Output of Taste Information for Liquor Using Electronic Tongue Based on Cloud Model.

Authors:  Jingjing Liu; Mingxu Zuo; Sze Shin Low; Ning Xu; Zhiqing Chen; Chuang Lv; Ying Cui; Yan Shi; Hong Men
Journal:  Sensors (Basel)       Date:  2020-01-27       Impact factor: 3.576

  1 in total

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