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Comparison of sensory evaluation techniques for Hungarian wines
Author(s) -
Guld Zsuzsanna,
Nyitrainé Sárdy Diána,
Gere Attila,
Rácz Anita
Publication year - 2020
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.3219
Subject(s) - quantitative descriptive analysis , mathematics , partial least squares regression , principal component analysis , sensory analysis , linear discriminant analysis , wine , sensory system , statistics , analysis of variance , quadratic classifier , chemometrics , pattern recognition (psychology) , artificial intelligence , food science , machine learning , computer science , chemistry , psychology , classifier (uml) , cognitive psychology
The aim of this study was to compare different Hungarian Kadarka, Kékfrankos, and Cabernet franc wines produced and aged by the same methods and to compare two types of sensory analysis methods as well: the 100‐point OIV system and quantitative descriptive analysis (QDA). Both tests were conducted by 12 assessors of the University of Pécs, Institute for Regional Development, Faculty of Horticulture and Oenology. This study provides conclusions about the use of sensory analysis methods, highlighting the advantages and disadvantages of QDA and the OIV system. Principal component analysis, analysis of variance (ANOVA), multiple factor analysis, and partial least squares dicriminant analysis were used for the evaluation of the data. Our results showed that the sensory panel was able to discriminate the samples by both sensory methods; however, the information provided by them was significantly different. ANOVA clearly showed that the two methods have different sensitivity when comparing wines (commercial and produced wine samples) and QDA proved to be the more sensitive, as well as more detailed, method. Partial least squares discriminant analysis augmented the findings in the classification part of the different type of wine samples. In general, OIV is able to show the general quality of the wines, while QDA coupled with proper chemometric methods is able to describe why the given samples received good or bad OIV scores.