Classification of Slovak white wines using artificial neural
networks and discriminant techniques

J 2009

Classification of Slovak white wines using artificial neural networks and discriminant techniques

KRUZLICOVA, Dasa, Jan MOCÁK, Branko BALLA, Jan PETKA, Marta FARKOVÁ et. al.

Basic information

Original name

Classification of Slovak white wines using artificial neural networks and discriminant techniques

Name in Czech

Klasifikace slovenských vín použitím umělých neuronových sítí a diskriminantních technik

Authors

KRUZLICOVA, Dasa (203 Czech Republic), Jan MOCÁK (703 Slovakia), Branko BALLA (703 Slovakia), Jan PETKA (703 Slovakia), Marta FARKOVÁ (203 Czech Republic, belonging to the institution) and Josef HAVEL (203 Czech Republic, guarantor, belonging to the institution)

Edition

Food Chemistry, 2008 Elsevier Ltd, 2009, 0308-8146

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10406 Analytical chemistry

Country of publisher

United Kingdom of Great Britain and Northern Ireland

Confidentiality degree

není předmětem státního či obchodního tajemství

Impact factor

Impact factor: 3.146

RIV identification code

RIV/00216224:14310/09:00036167

Organization unit

Faculty of Science

UT WoS

000259893600046

Keywords in English

Artificial neural networks; wine; classification

Abstract

ORIG CZ

V originále

This work demonstrates the possibility to use artificial neural networks (ANN) for the classification of white varietal wines. A multilayer perceptron technique using quick propagation and quasi-Newton propagation algorithms was the most successful. The developed methodology was applied to classify Slovak white wines of different variety, year of production and from different producers. The wine samples were analysed by the GC-MS technique taking into consideration mainly volatile species, which highly influence the wine aroma (terpenes, esters, alcohols). The analytical data were evaluated by means of the ANN and the classification results were compared with the analysis of variance (ANOVA). A good agreement amongst the applied computational methods has been observed and, in addition, further special information on the importance of the volatile compounds for the wine classification has been provided.

In Czech

Tato práce umožňuje klasifikaci vín umělými neuronovými sítěmi

Citovat

KRUZLICOVA, Dasa, Jan MOCÁK, Branko BALLA, Jan PETKA, Marta FARKOVÁ and Josef HAVEL. Classification of Slovak white wines using artificial neural networks and discriminant techniques. Food Chemistry. 2008 Elsevier Ltd, 2009, vol. 112, No 4, 7 pp. ISSN 0308-8146.

@article{839692,
   author = {Kruzlicova, Dasa and Mocák, Jan and Balla, Branko and Petka, Jan and Farková, Marta and Havel, Josef and D, Kružlicová and J, Mocák},
   article_number = {4},
   keywords = {Artificial neural networks; wine; classification},
   language = {eng},
   issn = {0308-8146},
   journal = {Food Chemistry},
   title = {Classification of Slovak white wines using artificial neural networks and discriminant techniques},
   volume = {112},
   year = {2009}
}

TY  - JOUR
ID  - 839692
AU  - Kruzlicova, Dasa - Mocák, Jan - Balla, Branko - Petka, Jan - Farková, Marta - Havel, Josef - D, Kružlicová - J, Mocák
PY  - 2009
TI  - Classification of Slovak white wines using artificial neural networks and discriminant techniques
JF  - Food Chemistry
VL  - 112
IS  - 4
PB  - 2008 Elsevier Ltd
SN  - 03088146
KW  - Artificial neural networks
KW  - wine
KW  - classification
N2  - This work demonstrates the possibility to use artificial neural networks (ANN) for the classification of white varietal wines. A multilayer perceptron technique using quick propagation and quasi-Newton propagation algorithms was the most successful. The developed methodology was applied to classify Slovak white wines of different variety, year of production and from different producers. The wine samples were analysed by the GC-MS technique taking into consideration mainly volatile species, which highly influence the wine aroma (terpenes, esters, alcohols). The analytical data were evaluated by means of the ANN and the classification results were compared with the analysis of variance (ANOVA). A good agreement amongst the applied computational methods has been observed and, in addition, further special information on the importance of the volatile compounds for the wine classification has been provided.
ER  -

KRUZLICOVA, Dasa, Jan MOCÁK, Branko BALLA, Jan PETKA, Marta FARKOVÁ and Josef HAVEL. Classification of Slovak white wines using artificial neural networks and discriminant techniques. \textit{Food Chemistry}. 2008 Elsevier Ltd, 2009, vol.~112, No~4, 7 pp. ISSN~0308-8146.

Detailed Information on Publication Record