Classification of Slovak white wines using artificial neural networks and discriminant techniques |
| |
Authors: | Dasa Kruzlicova Jan Mocak Branko Balla Jan Petka Marta Farkova Josef Havel |
| |
Affiliation: | 1. Institute of Analytical Chemistry, Faculty of Chemical and Food Technology, Slovak University of Technology, Radlinskeho 9, SK-81237 Bratislava, Slovakia;2. Department of Chemistry, Faculty of Natural Sciences, University of Ss. Cyril and Methodius, Nam. J. Herdu 2, SK-91701 Trnava, Slovakia;3. Food Research Institute, Priemyselna 4, SK-82475, Bratislava;4. Department of Analytical Chemistry, Faculty of Science, Masaryk University, Kotlarska 2, CZ-611 37 Brno, Czech Republic |
| |
Abstract: | 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. |
| |
Keywords: | Wine classification Wine authentication Artificial neural networks Feature selection ANOVA |
本文献已被 ScienceDirect 等数据库收录! |
|