A novel method for classification of wine based on organic
acids

J 2019

A novel method for classification of wine based on organic acids

MILOVANOVIĆ, Miodrag, Jiří ŽERAVÍK, Michal OBOŘIL, Marta PELCOVÁ, Karel LACINA et. al.

Basic information

Original name

A novel method for classification of wine based on organic acids

Name in Czech

Nová metoda pro klasifikaci vína založená na organických kyselinách

Authors

MILOVANOVIĆ, Miodrag (688 Serbia, belonging to the institution), Jiří ŽERAVÍK (203 Czech Republic, belonging to the institution), Michal OBOŘIL (203 Czech Republic, belonging to the institution), Marta PELCOVÁ (203 Czech Republic, belonging to the institution), Karel LACINA (203 Czech Republic, belonging to the institution), Uros CAKAR (688 Serbia), Aleksandar PETROVIC (688 Serbia), Zdeněk GLATZ (203 Czech Republic, belonging to the institution) and Petr SKLÁDAL (203 Czech Republic, guarantor, belonging to the institution)

Edition

Food Chemistry, Elsevier Science, 2019, 0308-8146

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10406 Analytical chemistry

Country of publisher

Netherlands

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

web časopisu

Impact factor

Impact factor: 6.306

RIV identification code

RIV/00216224:14310/19:00113328

Organization unit

Faculty of Science

DOI

http://dx.doi.org/10.1016/j.foodchem.2019.01.113

UT WoS

000458119700038

Keywords (in Czech)

karboxylové kyseliny; kapilární elektroforesa; biosensor; analýza hlavních komponent; samoorganizovaná mapa

Keywords in English

Carboxylic acids; Capillary electrophoresis; Biosensor; Principal component analysis; Self-organizing map

Abstract

ORIG CZ

V originále

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.

In Czech

Bioelektronický jazyk spojený s chemometrickým zpracováním měřených hodnot, sloužící pro klasifikaci vín dle obsahu karboxylových kyselin.

Links

MUNI/A/1100/2017, interní kód MU

Name: Podpora biochemického výzkumu v roce 2018

Investor: Masaryk University, Category A

90043, large research infrastructures

Name: CIISB

Citovat

MILOVANOVIĆ, Miodrag, Jiří ŽERAVÍK, Michal OBOŘIL, Marta PELCOVÁ, Karel LACINA, Uros CAKAR, Aleksandar PETROVIC, Zdeněk GLATZ and Petr SKLÁDAL. A novel method for classification of wine based on organic acids. Food Chemistry. Elsevier Science, 2019, vol. 284, June, p. 296-302. ISSN 0308-8146. Available from: https://dx.doi.org/10.1016/j.foodchem.2019.01.113.

@article{1637437,
   author = {Milovanović, Miodrag and Žeravík, Jiří and Obořil, Michal and Pelcová, Marta and Lacina, Karel and Cakar, Uros and Petrovic, Aleksandar and Glatz, Zdeněk and Skládal, Petr},
   article_number = {June},
   doi = {http://dx.doi.org/10.1016/j.foodchem.2019.01.113},
   keywords = {Carboxylic acids; Capillary electrophoresis; Biosensor; Principal component analysis; Self-organizing map},
   language = {eng},
   issn = {0308-8146},
   journal = {Food Chemistry},
   title = {A novel method for classification of wine based on organic acids},
   url = {https://www.sciencedirect.com/science/article/pii/S0308814619301815},
   volume = {284},
   year = {2019}
}

TY  - JOUR
ID  - 1637437
AU  - Milovanović, Miodrag - Žeravík, Jiří - Obořil, Michal - Pelcová, Marta - Lacina, Karel - Cakar, Uros - Petrovic, Aleksandar - Glatz, Zdeněk - Skládal, Petr
PY  - 2019
TI  - A novel method for classification of wine based on organic acids
JF  - Food Chemistry
VL  - 284
IS  - June
SP  - 296-302
EP  - 296-302
PB  - Elsevier Science
SN  - 03088146
KW  - Carboxylic acids
KW  - Capillary electrophoresis
KW  - Biosensor
KW  - Principal component analysis
KW  - Self-organizing map
UR  - https://www.sciencedirect.com/science/article/pii/S0308814619301815
L2  - https://www.sciencedirect.com/science/article/pii/S0308814619301815
N2  - 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.
ER  -

MILOVANOVI$\backslash$'C, Miodrag, Jiří ŽERAVÍK, Michal OBOŘIL, Marta PELCOVÁ, Karel LACINA, Uros CAKAR, Aleksandar PETROVIC, Zdeněk GLATZ and Petr SKLÁDAL. A novel method for classification of wine based on organic acids. \textit{Food Chemistry}. Elsevier Science, 2019, vol.~284, June, p.~296-302. ISSN~0308-8146. Available from: https://dx.doi.org/10.1016/j.foodchem.2019.01.113.

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