Abstract
Food biodiversity is vital for human health and the development of sustainable food systems. However, research on neglected and underutilized species is limited by funding, uneven research capacity, and the challenge of balancing ecological, cultural, and public health considerations, requiring innovative prioritization approaches. Using Brazil as a model, this study inventories 369 neglected food species across algae, aquatic fauna, wild terrestrial vertebrates, insects, mushrooms, and plants. A mixed-methods approach, combining expert knowledge and explainable AI (LightGBM and SHAP value analysis), identified key factors for prioritizing species for food composition and consumption studies. The inventory is dominated by plants (29.5%) and wild vertebrates (24.4%), with significant gaps in nutritional data, particularly for algae, insects, and wild vertebrates. Over 36,000 recipes using neglected species were identified. In both food composition (R2: 0.677) and consumption studies (R2: 0.782), recipe number and species occurrence across different states were the most influential features in predicting prioritization. These findings emphasize the role of cultural uses and local accessibility in shaping nutritional research priorities. We urge increased research on neglected species to bridge data gaps and integrate them into food systems, promoting sustainable diets in Brazil and other tropical regions.
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Data availability
The database and analysis scripts are available at this link https://github.com/eliasjacob/paper_bionut.
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Funding
This research was supported by the High-Performance Computing Center at UFRN (NPAD/UFRN) and the ‘Conselho Nacional de Desenvolvimento Científico e Tecnológico’ (CNPq) through a research grant to MCMJ (402334/2021–3) and AMC (444588/2023–0). The authors also thank CNPq for the research productivity scholarships awarded to EJMN (302582/2023–1), MCMJ (306755/2021–1), NMJ (314236/2021–0), and PFML (302365/2022–2). PFML acknowledges the funding from the Romanian Ministry of Research, Innovation and Digitalization for project JUST4MPA (760054, within the framework of PNRR-III-C9-2022—I8). AMC, MPD, and NMJ acknowledge the support of the Sao Paulo Research Foundation – FAPESP by, respectively, the following grants: 2022/03091–6, 2017/25754–9, and 2018/15677–0. HREB was supported by USAID agreement with CIFOR-ICRAF. CBBC also acknowledges the support from CNPq (306891/2021–2) and from the ‘Coordenação de Aperfeiçoamento de Pessoal de Nível Superior’ (CAPES) – Finance Code 001. The study received a contribution from the INCT Ethnobiology, Bioprospecting, and Nature Conservation, certified by CNPq, with financial support from the Foundation for Support to Science and Technology of the State of Pernambuco as a grant [Grant Number: APQ-0562–2.01/17] given to UPA.
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MCMJ led the project with responsibilities in Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Project administration, Validation, Visualization, and Writing (original draft and review & editing). UPA provided Conceptualization, Supervision, and Writing (review & editing). EJMN contributed to Conceptualization, Formal analysis, Methodology, Visualization, and Writing (review & editing). DT, DVBO, FOP, GFM, JKMS, LJGS, MPD, NMJ, PFML, JVMS, SCGS and RRVS contributed to Data Curation, Conceptualization and Writing (review & editing). AMC, SMG, and DMLM contributed to Conceptualization and Writing (review & editing). AGB, AFSJ, AAFC, CMMM, CBBC, EBG, HREB, IWLB, JSA, JS, JAT, LZOC, MAO, MEGO, MMN, RRNA, SCVCL, TQM contributed to Validation and Writing (review & editing). All authors have reviewed and approved the final manuscript and agree to be accountable for all aspects of the work.
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Jacob, M.C.M., de Carvalho, A.M., Batista, Â.G. et al. Prioritizing neglected food species in nutritional studies using expert-knowledge and explainable AI. Sci Rep (2026). https://doi.org/10.1038/s41598-026-39484-6
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DOI: https://doi.org/10.1038/s41598-026-39484-6
