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@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 a Josef HAVEL. Classification of Slovak white wines using artificial neural networks and discriminant techniques. \textit{Food Chemistry}. 2008 Elsevier Ltd, 2009, roč.~112, č.~4, 7 s. ISSN~0308-8146.
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