Representational and sensory cues as drivers of individual differences in expert quality assessment of red wines
| dc.rights.license | open | en_US |
| hal.structure.identifier | Unité de Recherche Oenologie [Villenave d'Ornon] [OENO] | |
| dc.contributor.author | CAISSIE, Andre F. | |
| hal.structure.identifier | Unité de Recherche Oenologie [Villenave d'Ornon] [OENO] | |
| dc.contributor.author | RIQUIER, Laurent | |
| hal.structure.identifier | Unité de Recherche Oenologie [Villenave d'Ornon] [OENO] | |
| dc.contributor.author | DE REVEL, Gilles | |
| hal.structure.identifier | Unité de Recherche Oenologie [Villenave d'Ornon] [OENO] | |
| dc.contributor.author | TEMPERE, Sophie
IDREF: 154752258 | |
| dc.date.accessioned | 2022-03-21T14:40:53Z | |
| dc.date.available | 2022-03-21T14:40:53Z | |
| dc.date.issued | 2021 | |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/136504 | |
| dc.description.abstractEn | 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. | |
| dc.language.iso | EN | en_US |
| dc.rights | Attribution-NonCommercial 3.0 United States | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc/3.0/us/ | |
| dc.subject.en | Wine tasting | |
| dc.subject.en | Quality decisions | |
| dc.subject.en | Perception | |
| dc.subject.en | Vocabulary | |
| dc.subject.en | Mental imagery | |
| dc.title.en | Representational and sensory cues as drivers of individual differences in expert quality assessment of red wines | |
| dc.type | Article de revue | en_US |
| dc.identifier.doi | 10.1016/j.foodqual.2020.104032 | en_US |
| dc.subject.hal | Sciences du Vivant [q-bio]/Biologie végétale | en_US |
| bordeaux.journal | Food Quality and Preference | en_US |
| bordeaux.volume | 87 | en_US |
| bordeaux.hal.laboratories | Unité de Recherche Oenologie - EA 4577 | en_US |
| bordeaux.institution | Université de Bordeaux | en_US |
| bordeaux.institution | Bordeaux INP | en_US |
| bordeaux.institution | INRAE | en_US |
| bordeaux.peerReviewed | oui | en_US |
| bordeaux.inpress | non | en_US |
| hal.export | false | |
| dc.rights.cc | Pas de Licence CC | en_US |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Food%20Quality%20and%20Preference&rft.date=2021&rft.volume=87&rft.au=CAISSIE,%20Andre%20F.&RIQUIER,%20Laurent&DE%20REVEL,%20Gilles&TEMPERE,%20Sophie&rft.genre=article |
