Development of an open-access food atlas with nutrient composition and recipes in Argentina: The Smart24Food Atlas
4 affiliations
- 1Interdisciplinary Center for Research in Health and Behavioral Sciences, School of Medicine (CIICSAC), Universidad Adventista del Plata, Libertador San Martín, Argentina
- 2Faculty of Engineering, Universidad Nacional de Entre Ríos, Oro Verde, Argentina
- 3National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- 4Faculty of Exact and Natural Sciences and Surveying, National University of NorthEast (UNNE), Corrientes, Argentina
Abstract
Introduction: Accurate dietary intake assessment remains challenging, particularly for portion-size estimation, and context-specific photographic aids remain limited in Argentina. This study aimed to develop an open-access digital atlas of foods and recipes consumed in Argentina, integrating portion-size photographs and nutrient-composition data, and to describe its performance for food and recipe retrieval and visual portion-size matching under controlled direct-observation conditions. Methods: The Smart24Food atlas was developed as a digital resource integrating food photographs, standardized recipes, and nutrient-composition information. A controlled direct-observation study in a university setting included 108 participants, mostly young adults, completing 20 tasks: seven packaged-product selection tasks and 13 visual portion-matching tasks. Exact matching was analyzed using cross-classified logistic mixed-effects models, while weight-based performance was assessed using linear mixed-effects models and repeated-measures Bland–Altman analysis. Results: The atlas contains 3,273 photographs representing 998 distinct foods through 1,052 presentation-specific items, with nutrient-composition information for up to 53 components. Food or recipe retrieval was successful in 99.81% of tasks (2,156/2,160), and overall exact matching was 86.5% (1,869/2,160). Food-level heterogeneity was greater than participant-level heterogeneity, whereas food category and task type were not significantly associated with exact matching. Across 1,404 visual portion-matching observations, mean signed error was −1.34 g (95% CI: −4.68 to 2.00; p = 0.447), with no evidence that signed error varied systematically with served portion weight across the evaluated foods (B=−0.011 g/g; p = 0.703). The 95% Bland–Altman limits of agreement ranged from −33.44 to 30.76 g. Conclusions: The Smart24Food atlas is an open-access resource integrating photographic portion references with nutrient-composition information for foods and recipes consumed in Argentina. Under controlled direct-observation conditions, participants showed high retrieval and exact-match performance, with no evidence of systematic mean bias in visual portion matching. Further studies in more diverse populations and routine dietary-assessment contexts are needed.
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BibTeX
@article{contrerasguillen2026development,
title = {{Development of an open-access food atlas with nutrient composition and recipes in Argentina: The Smart24Food Atlas}},
author = {Ismael Alejandro Contreras-Guillén and Sara Leeson and Rocio Victoria Gili and Belén Carlino and Emanuel Irrazabal and Sandaly Oliveira da Silva Pacheco and Fabio Juliano Pacheco},
journal = {PLOS One},
year = {2026},
month = sep,
doi = {10.1371/journal.pone.0359331},
url = {https://doi.org/10.1371/journal.pone.0359331},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Development of an open-access food atlas with nutrient composition and recipes in Argentina: The Smart24Food Atlas
AU - Ismael Alejandro Contreras-Guillén
AU - Sara Leeson
AU - Rocio Victoria Gili
AU - Belén Carlino
AU - Emanuel Irrazabal
AU - Sandaly Oliveira da Silva Pacheco
AU - Fabio Juliano Pacheco
PY - 2026
DA - 2026/09/25
JO - PLOS One
DO - 10.1371/journal.pone.0359331
UR - https://doi.org/10.1371/journal.pone.0359331
AB - Introduction: Accurate dietary intake assessment remains challenging, particularly for portion-size estimation, and context-specific photographic aids remain limited in Argentina. This study aimed to develop an open-access digital atlas of foods and recipes consumed in Argentina, integrating portion-size photographs and nutrient-composition data, and to describe its performance for food and recipe retrieval and visual portion-size matching under controlled direct-observation conditions. Methods: The Smart24Food atlas was developed as a digital resource integrating food photographs, standardized recipes, and nutrient-composition information. A controlled direct-observation study in a university setting included 108 participants, mostly young adults, completing 20 tasks: seven packaged-product selection tasks and 13 visual portion-matching tasks. Exact matching was analyzed using cross-classified logistic mixed-effects models, while weight-based performance was assessed using linear mixed-effects models and repeated-measures Bland–Altman analysis. Results: The atlas contains 3,273 photographs representing 998 distinct foods through 1,052 presentation-specific items, with nutrient-composition information for up to 53 components. Food or recipe retrieval was successful in 99.81% of tasks (2,156/2,160), and overall exact matching was 86.5% (1,869/2,160). Food-level heterogeneity was greater than participant-level heterogeneity, whereas food category and task type were not significantly associated with exact matching. Across 1,404 visual portion-matching observations, mean signed error was −1.34 g (95% CI: −4.68 to 2.00; p = 0.447), with no evidence that signed error varied systematically with served portion weight across the evaluated foods (B=−0.011 g/g; p = 0.703). The 95% Bland–Altman limits of agreement ranged from −33.44 to 30.76 g. Conclusions: The Smart24Food atlas is an open-access resource integrating photographic portion references with nutrient-composition information for foods and recipes consumed in Argentina. Under controlled direct-observation conditions, participants showed high retrieval and exact-match performance, with no evidence of systematic mean bias in visual portion matching. Further studies in more diverse populations and routine dietary-assessment contexts are needed.
SN - 1932-6203
ER -