Current practices, challenges and new advances in the collection and use of food composition data for Africa

dc.contributor.authorPretorius, Beulah
dc.contributor.authorMuka, Junior M.
dc.contributor.authorHulshof, Paul J.M.
dc.contributor.authorSchonfeldt, H.C. (Hettie Carina)
dc.contributor.emailbeulah.pretorius@up.ac.zaen_US
dc.date.accessioned2024-06-27T09:44:32Z
dc.date.available2024-06-27T09:44:32Z
dc.date.issued2023-07-25
dc.descriptionDATA AVAILABILITY STATEMENT : The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.en_US
dc.description.abstractHigh-quality food composition data are indispensable for improved decision-making in food security, health policy formulation, food labeling, diet formulation, agricultural policymaking, nutrition research, and many other nutrition-related activities. The optimisation of dietary patterns is a powerful tool to reduce the impact of malnutrition on a population’s health and well-being. Many countries in resource-poor settings lack a framework for developing and managing food composition data appropriate for these purposes. In the article, an overview of available food composition tables in Africa and the origin, use and limitations of theses tables are discussed. It is important that those working on any nutrition-related activity for resource-poor settings understand the limitations of current food composition data. Production of high-quality data requires the harmonization and adoption of international standards and guidelines across Africa. Moreover, continuity in the production, compilation and management of high-quality food composition data is challenged by suboptimal capacity building in terms of organizational, institutional and legal framework development. In this perspective article, the authors deliberate on challenges with a focus on Africa, while discussing new advances in food composition activities. Opportunities (such as the Internet of Things (IoT), wearable devices, natural language processing (NLP) and other machine learning techniques) to improve existing resources must be more actively explored and supported.en_US
dc.description.departmentAnimal and Wildlife Sciencesen_US
dc.description.librarianam2024en_US
dc.description.sdgSDG-02:Zero Hungeren_US
dc.description.sponsorshipThe Economic and Social Research Council under the ARUA-GCRF UKRI Partnership Program as part of the Capacity Building in Food Security (CaBFoodS-Africa) project and the Department of Science and Innovation (DSI)/National Research Foundation (NRF) South African Research Chairs Initiative (SARChl) in the National Development Plan Priority Area of Nutrition and Food Security.en_US
dc.description.urihttps://www.frontiersin.org/journals/sustainable-food-systemsen_US
dc.identifier.citationPretorius, B., Muka, J.M., Hulshof, P.J.M. & Schönfeldt, H.C. (2023) Current practices, challenges and new advances in the collection and use of food composition data for Africa. Frontiers in Sustainable Food Systems 7:1240734. DOI: 10.3389/fsufs.2023.1240734.en_US
dc.identifier.issn2571-581X (online)
dc.identifier.other10.3389/fsufs.2023.1240734
dc.identifier.urihttp://hdl.handle.net/2263/96699
dc.language.isoenen_US
dc.publisherFrontiers Mediaen_US
dc.rights© 2023 Pretorius, Muka, Hulshof and Schönfeldt. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).en_US
dc.subjectFood composition dataen_US
dc.subjectFood securityen_US
dc.subjectInformation and communication technology (ICT)en_US
dc.subjectMachine learningen_US
dc.subjectCapacity buildingen_US
dc.subjectSDG-02: Zero hungeren_US
dc.titleCurrent practices, challenges and new advances in the collection and use of food composition data for Africaen_US
dc.typeArticleen_US

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