Developing the culturally-valid food image dataset (CV-FID): Protocol and application to hedonic food images

Food images are widely used as a virtual substitute for real food in ingestive behavior research. Ensuring scientific rigor requires high-quality, standardized, and culturally valid food image datasets (CV-FID) that account for cross-cultural differences in food recognition and preferences. This study presents a protocol for developing a CV-FID and demonstrates its application in creating the Hedonic Food dataset tailored to the Israeli adult population. The CV-FID standardized protocol follows a five-stage process: (1) an expert focus group to select culturally-relevant food items; (2) comprehensive nutritional analysis; (3) standardized professional food photography; (4) a normative rating survey administered to a representative Israeli adult sample; and (5) integration of food images, nutritional data, and normative ratings into a designated database. This protocol is illustrated through the development of a Hedonic Food Image Dataset (HFID). The final HFID included 45 culturally-relevant food items, which were captured with high-resolution images, detailed nutritional information, and comprehensive normative ratings from 157 adults (mean age: 41.9 ± 15.1 years; mean BMI: 26.5 ± 6.0 kg/m 2 ). The survey covered recognition rates, frequency of consumption, perceived healthiness, sensory attributes, and hedonic response, with internal validity confirmed with descriptive trends and correlational analyses. The CV-FID protocol provides a structured framework for developing a culturally valid, high-quality food image dataset. By adopting this protocol, researchers can ensure greater consistency and applicability when developing future food image databases across diverse settings. The HFID illustrates the protocol's application and serves as a valuable resource for nutrition-related research. • A standardized protocol for culturally valid food image datasets is presented. • The protocol includes five development stages. • The protocol is applied in the Hedonic Food Image Dataset (HFID) for Israeli adults. • The HFID includes images, nutrition data, and normative ratings. • The protocol and HFID support research on food preferences and cues.

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Publication Details

Journal
Food Quality and Preference
Published
2026-01-30
DOI
https://doi.org/10.1016/j.foodqual.2026.105868
Primary Topic
Nutritional Studies and Diet
Type
article
Field-Weighted Citation Impact
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article

Developing the culturally-valid food image dataset (CV-FID): Protocol and application to hedonic food images

Shiri Sherf‐Dagan, Roni Aviram-Friedman, Graham Finlayson
Food Quality and Preference
Nutritional Studies and Diet
article

Developing the culturally-valid food image dataset (CV-FID): Protocol and application to hedonic food images

Shiri Sherf‐Dagan, Roni Aviram-Friedman, Graham Finlayson
article en

Abstract

Food images are widely used as a virtual substitute for real food in ingestive behavior research. Ensuring scientific rigor requires high-quality, standardized, and culturally valid food image datasets (CV-FID) that account for cross-cultural differences in food recognition and preferences. This study presents a protocol for developing a CV-FID and demonstrates its application in creating the Hedonic Food dataset tailored to the Israeli adult population. The CV-FID standardized protocol follows a five-stage process: (1) an expert focus group to select culturally-relevant food items; (2) comprehensive nutritional analysis; (3) standardized professional food photography; (4) a normative rating survey administered to a representative Israeli adult sample; and (5) integration of food images, nutritional data, and normative ratings into a designated database. This protocol is illustrated through the development of a Hedonic Food Image Dataset (HFID). The final HFID included 45 culturally-relevant food items, which were captured with high-resolution images, detailed nutritional information, and comprehensive normative ratings from 157 adults (mean age: 41.9 ± 15.1 years; mean BMI: 26.5 ± 6.0 kg/m 2 ). The survey covered recognition rates, frequency of consumption, perceived healthiness, sensory attributes, and hedonic response, with internal validity confirmed with descriptive trends and correlational analyses. The CV-FID protocol provides a structured framework for developing a culturally valid, high-quality food image dataset. By adopting this protocol, researchers can ensure greater consistency and applicability when developing future food image databases across diverse settings. The HFID illustrates the protocol's application and serves as a valuable resource for nutrition-related research. • A standardized protocol for culturally valid food image datasets is presented. • The protocol includes five development stages. • The protocol is applied in the Hedonic Food Image Dataset (HFID) for Israeli adults. • The HFID includes images, nutrition data, and normative ratings. • The protocol and HFID support research on food preferences and cues.

Food Quality and PreferenceVol. 141
University of Leeds (GB), Assuta Medical Center (IL), Ariel University (IL)
Zero hunger
Openalex Percentile: Top 74%
Nutritional Studies and Diet
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