Influence of expertise on semantic categorization of wine odors

Koenig, L.; Coulon‐Leroy, Cécile; Symoneaux, Ronan; Cariou, Véronique; Vigneau, Évelyne

doi:10.1016/j.foodqual.2020.103923

Cited by 14 publications

(11 citation statements)

References 42 publications

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“…Should a single subject be required to 63 group these together? 64 65Two closely related alternatives have been suggested for the simple free-sorting task that address 66 these issues: free multiple-sorts (Blanchard & Banerji, 2016;Dehlholm, 2015; Dehlholm et al, 67 2012) and hierarchical free-sorts (Koenig et al, 2020(Koenig et al, , 2021. The former modification asks 68 subjects, after they have completed a simple free-sorting task, to repeat the task until they feel 69 they have exhausted all possible grouping configurations (Dehlholm, 2015); the latter asks 70 subjects, once they completed a simple free-sorting task, to continue making groups of groups 71 until they cannot proceed further (Koenig et al, 2021).…”

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confidence: 99%

“…73 However, neither approach solves both problems, and they both introduce problems of panelist 74 motivation, in that they require a much more extensive data-collection procedure that will be 75 discouraging for some subjects. This is a more major problem when a large number of samples 76 is used, as in Koenig et al (2020), but difficulty and motivation problems are reported with as 77 few as 18 complex samples sorted by taste (Kessinger et al, 2020). In addition, the data 78 collection for both methods is much more complicated and more poorly supported in practical 79 data-management programs (based on the authors' personal communications with major sensory 80 and survey software providers in pursuit of these methods), which appears to have limited the 81 adoption of either approach in academia and industry in favor of the simple free-sorting task.…”

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confidence: 99%

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The free-linking task: A graph-inspired method for generating non-disjoint similarity data with food products

Lahne

Phetxumphou

Tejedor-Romero

et al. 2022

Food Quality and Preference

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confidence: 99%

mentioning

confidence: 99%

The free-linking task: A graph-inspired method for generating non-disjoint similarity data with food products

Lahne

Phetxumphou

Tejedor-Romero

et al. 2022

Food Quality and Preference

View full text Add to dashboard Cite

“…Sixty-six subjects (41 wine consumers, 13 students in viticulture and oenology, and 12 professionals from the wine sector) were recruited for the HRATA experiment. All subjects possessed a minimum level of wine knowledge, which was evaluated using a questionnaire similar to that presented by Koenig et al (2020). Subjects with an objective knowledge score greater than or equal to 8/14 were retained for the experiment.…”

Section: Subjectsmentioning

confidence: 99%

Development of a Hierarchical Rate-All-That-Apply (HRATA) methodology for the aromatic characterisation of wine

Koenig

Symoneaux

Pouzalgues³

et al. 2023

OENO One

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Wine aromatic characterisation is generally a complex task, even for well-trained assessors. To facilitate such characterisation, aroma terms are typically arranged in some sort of hierarchical structure, such as aroma wheels. However, information about this structure is lost with existing data acquisition and treatment methods. To fill this gap, we propose a new approach, Hierarchical-Rate-All-That-Apply (HRATA), for the characterisation of products. It combines the Rate-All-That-Apply (RATA) methodology with a hierarchical structuring of general and specific attributes. The aim is first to facilitate data acquisition and, secondly, to account for the hierarchical links among attributes during data analysis. We applied an HRATA approach to the characterisation of five rosé wines by 66 subjects based on 118 hierarchically structured aromatic attributes. Using monadic evaluation, assessors were asked to select all the attributes that characterised each wine and to rate their intensity on a three-point scale. For the data analysis, an initial coding step was carried out to represent the hierarchical structure of the attributes, which also made it possible to manage a large amount of non-evaluated data. After that, statistical tests and multivariate analyses were tailored for both the identification of discriminating attributes and the determination of a product map. Finally, the characterisation obtained with HRATA was compared to the results obtained from a descriptive analysis (DA) conducted by a trained panel. HRATA represents an interesting alternative for obtaining aromatic characterisation using a panel of subjects without collective common training or with diverse skill sets.

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Section: Introductionmentioning

confidence: 99%

“…The idea that past consumer experiences impact product perception has been extensively studied (Borgogno et al, 2015; Giacalone & Jaeger, 2021; Torrico et al, 2019; Zhou & Nakamoto, 2007), with much of the research focusing on the wine product category (Hopfer & Heymann, 2014; Koenig et al, 2020; Parr et al, 2011; Solomon, 1990). According to Balester et al, a greater focus on sensory perception by expert consumers, compared to naive consumers (often referenced using the term “familiarity” outside of the wine space), could be caused by experts having a deeper knowledge of wine styles (Ballester et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Do consumer perceptions of a product category relate to their sensory properties? A case study on energy bars with consumers of high and low familiarity

Schoonbrood,

Delarue

2024

Journal of Sensory Studies

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Goods in a market are typically presented in discrete categories so that consumers can easily find their way among the myriad of products available. However, sub‐categorical distinctions are often less clear. This study aimed to explore how consumer perceptions of products within a category relate to their sensory properties. By analyzing how consumers sorted energy bars and the vocabulary used to describe the resulting clusters, we found that consumers generally agree on how they perceive bars high in protein. However, energy bar consumers with high familiarity demonstrated greater levels of differentiation between clusters compared to energy bar consumers with low familiarity. They were also more consensual in their sorting. Furthermore, sensory properties were found to play a larger role in determining product clusters for consumers with high familiarity than with low familiarity. These findings shed light on the factors influencing consumer perception of energy bars. Additionally, this approach offers a simple way to investigate consumer perception of a product category and could be useful to marketers and product developers who wish to refine their offerings to better meet consumer expectations.Practical ApplicationsThe method for category appraisal described in this paper emphasizes consumer perception of products and factors, such as sensory properties and nutrition facts, that influence these perceptions. It departs from traditional approaches that focus on individual product descriptions and instead focuses on product groupings perceived by consumers. This approach allows for deeper insights to be obtained about product categories as a whole, which can inform effective marketing strategies and efficient product development.

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Influence of expertise on semantic categorization of wine odors

Cited by 14 publications

References 42 publications

The free-linking task: A graph-inspired method for generating non-disjoint similarity data with food products

The free-linking task: A graph-inspired method for generating non-disjoint similarity data with food products

Development of a Hierarchical Rate-All-That-Apply (HRATA) methodology for the aromatic characterisation of wine

Do consumer perceptions of a product category relate to their sensory properties? A case study on energy bars with consumers of high and low familiarity

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