Influence of expertise on semantic categorization of wine odors

•Ninety-six terms of odors used in wine characterization were selected from the literature.•A free sorting task was conducted with 156 subjects on the 96 terms.•Each subject’s expertise was analyzed using a questionnaire.•Subjects were clustered by expertise and their sorting patterns were compared...

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Veröffentlicht in:Food quality and preference 2020-07, Vol.83, p.103923, Article 103923
Hauptverfasser: Koenig, L., Coulon-Leroy, C., Symoneaux, R., Cariou, V., Vigneau, E.
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container_issue
container_start_page 103923
container_title Food quality and preference
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creator Koenig, L.
Coulon-Leroy, C.
Symoneaux, R.
Cariou, V.
Vigneau, E.
description •Ninety-six terms of odors used in wine characterization were selected from the literature.•A free sorting task was conducted with 156 subjects on the 96 terms.•Each subject’s expertise was analyzed using a questionnaire.•Subjects were clustered by expertise and their sorting patterns were compared using consensus partitions and additive trees. Aromatic characterization is a key element of enhancing one’s knowledge of wine. While several studies have investigated the importance of wine expertise in the ability to perform odor-related sensory tasks, little attention has been paid to the influence of expertise on the semantic categorization of wine odors. To bridge this gap, this study aimed to explore the influence of a subject’s expertise on the semantic representation of wine odors by means of a free sorting task. For this purpose, 156 subjects were recruited. Their level of expertise was measured using a questionnaire and the data analysis revealed four clusters of subjects with a gradual level of expertise. Subjects also performed a sorting task on 96 odor terms. From the number and the size of odor groups formed, as well as the additive tree representation and the consensus partition between the terms for each expertise level, we observed that all subjects, regardless of their experience, had largely the same semantic categorization of wine-odor attributes, which was mainly shaped by the sources of the odorants. It appeared that level of wine expertise played a minor role in creating the semantic representation of wine odors, affecting mainly the knowledge of specialized terms.
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Aromatic characterization is a key element of enhancing one’s knowledge of wine. While several studies have investigated the importance of wine expertise in the ability to perform odor-related sensory tasks, little attention has been paid to the influence of expertise on the semantic categorization of wine odors. To bridge this gap, this study aimed to explore the influence of a subject’s expertise on the semantic representation of wine odors by means of a free sorting task. For this purpose, 156 subjects were recruited. Their level of expertise was measured using a questionnaire and the data analysis revealed four clusters of subjects with a gradual level of expertise. Subjects also performed a sorting task on 96 odor terms. From the number and the size of odor groups formed, as well as the additive tree representation and the consensus partition between the terms for each expertise level, we observed that all subjects, regardless of their experience, had largely the same semantic categorization of wine-odor attributes, which was mainly shaped by the sources of the odorants. 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Aromatic characterization is a key element of enhancing one’s knowledge of wine. While several studies have investigated the importance of wine expertise in the ability to perform odor-related sensory tasks, little attention has been paid to the influence of expertise on the semantic categorization of wine odors. To bridge this gap, this study aimed to explore the influence of a subject’s expertise on the semantic representation of wine odors by means of a free sorting task. For this purpose, 156 subjects were recruited. Their level of expertise was measured using a questionnaire and the data analysis revealed four clusters of subjects with a gradual level of expertise. Subjects also performed a sorting task on 96 odor terms. 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subjects Additive tree
Consensus partition
Food and Nutrition
Food engineering
Free sorting
Level of expertise
Life Sciences
Semantic odor categorization
title Influence of expertise on semantic categorization of wine odors
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