Comparison of sensory evaluation techniques for Hungarian wines

Abstract

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.

The role of expert judgments in wine quality assessment: the mismatch between chemical, sensorial and extrinsic cues

“…, 2010). Different ANOVA models have been previously applied regarding the evaluation and characterization of wine quality, the most important of which are those of Guld et al. (2020), Budić-Leto et al.…”

“…The statistical analysis is based on a one-factor ANOVA, because the dependent variables are metric variables (laboratory score, expert rating and GQS) whose means will be contrasted with respect to the categories of the independent variables, or qualitative factors including the intrinsic and extrinsic variables (Hair et al, 2010). Different ANOVA models have been previously applied regarding the evaluation and characterization of wine quality, the most important of which are those of Guld et al (2020) (2011). By employing the F test in the single factor ANOVA, the statistical dependence or independence between the dependent and independent variables is assessed.…”

“…ANOVA models have been previously applied regarding the evaluation and characterization of wine quality, the most important of which are those ofGuld et al (2020), Budić-Leto et al(2017), Ruiz-Moreno (2017),Saénz-Navajas et al (2016a) andDall´Asta et al (2011). By employing the F test in the single factor ANOVA, the statistical dependence or independence…”

Lab-on-a-chip technologies for food safety, processing, and packaging applications: a review

“…The technology offers promise to overcome the challenges faced by various sensory experts and participants for analysis and study for different foods. For instance, a sensory evaluation technique involved 12 sensory panelists for the effective assessment of wine (Guld et al 2020 ). Similar sensory and consumer studies were done for different foods namely soy sauce, olive oils, and soups (Yang and Lee 2019 ).…”

Occurrence of Marine Ingredients in Fragrance: Update on the State of Knowledge

“…However, retronasal thresholds are generally lower than orthonasal thresholds [56]. Thus, the odors' evaluation is usually performed by flavor profile analysis (FPA) according to the methods reported in the literature [57][58][59]. In the liquid phase, the threshold is determined in water, ethanol or in a 46% (v/v) hydroalcoholic solution (sometimes in a 12% (v/v) water-ethanol mixture), with a slight modification, depending on the polarity of the compounds, and is then calculated using the methods reported in the literature [60].…”