Toward a Deeper Understanding of the Seaweed Sensory Space Through Consumer‐Evoked Associations Across Ireland, Norway, Spain, and Turkey

ABSTRACT Understanding the sensory space of a product category is a valuable tool in New Product Development, particularly for emerging food categories such as seaweed, where consumer familiarity remains limited in many markets. The current work explored the sensory associations of consumers willing to try seaweed products across four European countries (Ireland, Norway, Spain, and Turkey) through a cross‐cultural online survey. Participants assessed five organoleptic dimensions (color, visual appearance, flavor, basic tastes, and texture‐mouthfeel) as positive or negative factors and Check‐All‐That‐Apply (CATA) methodology to understand what individual sensory attributes participants associate with seaweed. Besides country of origin, participants' answers were split into perceptuals (those who had previously eaten seaweed products) and conceptuals (those who had not). Results from two‐way ANOVA, Multiple Factor Analysis, and Agglomerative Hierarchical Clustering showed that both country of origin and previous exposure to seaweed products significantly influenced sensory associations across all dimensions. Polarity analysis identified “metallic”, “chewy”, and “sticky” as attributes associated with negative perception, whereas “creamy”, “soft”, and “seafood‐like” showed positive valence across countries. These findings contribute novel and practical insights for product developers targeting the increase in seaweed consumption among European consumers.

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Publication Details

Journal
Food Science & Nutrition
Published
2026-10-26
DOI
https://doi.org/10.1002/fsn3.72508
Primary Topic
Sensory Analysis and Statistical Methods
Type
article
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article

Toward a Deeper Understanding of the Seaweed Sensory Space Through Consumer‐Evoked Associations Across Ireland, Norway, Spain, and Turkey

Hanne Dalsvåg, Marta Martínez‐Sanz, Guro Møen Tveit, Solveig Uglem et al.
Food Science & Nutrition
Sensory Analysis and Statistical Methods
article

Toward a Deeper Understanding of the Seaweed Sensory Space Through Consumer‐Evoked Associations Across Ireland, Norway, Spain, and Turkey

Hanne Dalsvåg, Marta Martínez‐Sanz, Guro Møen Tveit, Solveig Uglem, Gonzalo Garrido‐Bañuelos, Patricia López-Sánchez
article en

Abstract

ABSTRACT Understanding the sensory space of a product category is a valuable tool in New Product Development, particularly for emerging food categories such as seaweed, where consumer familiarity remains limited in many markets. The current work explored the sensory associations of consumers willing to try seaweed products across four European countries (Ireland, Norway, Spain, and Turkey) through a cross‐cultural online survey. Participants assessed five organoleptic dimensions (color, visual appearance, flavor, basic tastes, and texture‐mouthfeel) as positive or negative factors and Check‐All‐That‐Apply (CATA) methodology to understand what individual sensory attributes participants associate with seaweed. Besides country of origin, participants' answers were split into perceptuals (those who had previously eaten seaweed products) and conceptuals (those who had not). Results from two‐way ANOVA, Multiple Factor Analysis, and Agglomerative Hierarchical Clustering showed that both country of origin and previous exposure to seaweed products significantly influenced sensory associations across all dimensions. Polarity analysis identified “metallic”, “chewy”, and “sticky” as attributes associated with negative perception, whereas “creamy”, “soft”, and “seafood‐like” showed positive valence across countries. These findings contribute novel and practical insights for product developers targeting the increase in seaweed consumption among European consumers.

Food Science & NutritionVol. 14(11)
Stellenbosch University (ZA), SINTEF Ocean (NO), Instituto de Investigacións Mariñas (ES), Instituto de Investigación en Ciencias de la Alimentación (ES)
Openalex Percentile: Top 15%
Sensory Analysis and Statistical Methods
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