Big data analytics have shown great potential to improve decision-making in health, including disease surveillance and healthcare delivery. This scoping review explores how big data supports decision-making in large-scale food fortification (LSFF) and biofortification across the food value chain. Following PRISMA guidelines, we analyzed open-access peer-reviewed literature and gray literature from 2012 to 2022. Given the limited literature, we broadened our search to include big data applications in agriculture and nutrition, aiming to draw relevant insights for LSFF and biofortification. Of 1678 records, 28 mentioned LSFF or biofortification, all published between 2018 and 2022. Overall, most records focused on production (60%) and inputs (19.5%). Notably, 16.7% (n = 7) of records mentioning LSFF or biofortification addressed public health monitoring, compared to 2.3% (n = 45) of those without a mention. Use case examples include blockchain and Internet of Things (IoT) for fortified product traceability, machine learning to predict fortification gaps, and artificial intelligence to analyze anemia prevalence, highlighting opportunities to enhance both production and public health monitoring. Despite this potential, big data use in LSFF and biofortification remains limited. Expanding its use in underexplored areas, such as distribution and regulation, could enhance decision-making, efficiency, and sustainability in LSFF and biofortification.
Keywords: artificial intelligence; big data analytics; biofortification; food value chain; large‐scale food fortification; machine learning; nutrition.
© 2025 The Author(s). Annals of the New York Academy of Sciences published by Wiley Periodicals LLC on behalf of The New York Academy of Sciences.