Representational and sensory cues as drivers of individual differences in expert quality assessment of red wines
| Autor: | André F. Caissie, Laurent Riquier, Sophie Tempere, Gilles de Revel |
|---|---|
| Přispěvatelé: | Unité de Recherche Oenologie [Villenave d'Ornon], Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Vocabulary
030309 nutrition & dietetics media_common.quotation_subject Aroma of wine Sensory system Mental imagery Wine color 03 medical and health sciences 0404 agricultural biotechnology Sensory cue media_common Wine 0303 health sciences Nutrition and Dietetics food and beverages 04 agricultural and veterinary sciences 040401 food science Wine tasting Quality decisions [SDE]Environmental Sciences Perception Psychology Food Science Mental image Cognitive psychology |
| Zdroj: | Food Quality and Preference Food Quality and Preference, Elsevier, 2021, 87, pp.1-13. ⟨10.1016/j.foodqual.2020.104032⟩ |
| ISSN: | 0950-3293 |
| DOI: | 10.1016/j.foodqual.2020.104032⟩ |
| Popis: | The aim of this study was to model decisional consensus in expert red wine tastings, using an integrated competency framework. Wine assessment responses on both technical and emotional scales were collated for two wine categories (Premium vs. Secondary) under several different sensory conditions: six global tastings (all senses involved), three unimodal tastings (visual, smell, and taste), and three bimodal tastings (visual-smell, visual–taste, and taste–smell). Psychological predictors also included vocabulary and vividness of mental imagery associated with the various senses involved, together with professional experience indicators (age and tasting frequency). Principal component analyses revealed a greater response consensus with unimodal vision cues compared to all other sensory conditions (at least equal to global conditions). On average, a greater consensus was observed among technical quality scale responses under all sensory conditions, compared to emotional scale responses. The quality responses were used to build a 4-factor prediction model: age, wine imagery, vocabulary, and smell consensus. The image responses were used to build a two-factor prediction model: visual words (semantic knowledge) and visual-smell consensus. This indicated that the quality decisional consensus was based on smell information (wine aroma), combined with longevity/knowledge. In contrast, the image decisional consensus was based on visual information (wine color), combined with visual knowledge (and smell as a subordinate factor). Taken together, our results revealed previously uncharted individual differences in wine tasting and decision-making, concomitant with similarly weighted predictions based on sensory and psychological factors. |
| Databáze: | OpenAIRE |
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