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<p>This review aims to critically evaluate sustainable smart sensing technologies and AI-driven platforms for real-time mycotoxin detection, highlighting innovations, integration across the food supply chain, current limitations, and future directions for safer, data-driven food safety management. This systematic review followed PRISMA guidelines and covered studies published between 2015 and 2025. Literature searches were conducted in Scopus, Web of Science, PubMed, IEEE Xplore, and Google Scholar, yielding a total sample of 620 identified records. Peer-reviewed articles on smart sensors, biosensors, and AI-driven mycotoxin monitoring were included. After title, abstract, and full-text screening based on predefined eligibility criteria, approximately 160 studies were retained and formed the final sample for qualitative synthesis across the food supply chain. Sustainable smart sensing and AI-driven platforms are transforming real-time mycotoxin detection across the food supply chain by enabling rapid, sensitive, and decentralized monitoring from farm to fork. Emerging biosensors, optical sensors, and IoT-enabled devices integrated with machine learning improve early warning, traceability, and decision-making. However, key gaps remain, including limited sensor robustness under variable field conditions, high costs of advanced materials, energy demands, and scarcity of large, standardized datasets for AI training. Interoperability between sensing platforms and regulatory frameworks is also underdeveloped. Sustainability challenges involve balancing analytical performance with low-energy operation, sensor recyclability, and accessibility for low-resource settings. Future directions should prioritize biodegradable and reusable sensor materials, edge-AI and low-power electronics, federated data-sharing models, and climate-resilient deployment strategies. Integrating predictive analytics with risk assessment and policy alignment will be essential for scalable, sustainable mycotoxin management systems.</p> Graphical Abstract <p></p>

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Sustainable smart sensing and AI-driven platforms for real-time detection and monitoring of mycotoxins across the food supply chain

  • 期刊论文

  • 发表日期：

    2026年5月26日

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  • Blessing Rachael Adeyeye,
  • Samuel Ayofemi Olalekan Adeyeye

摘要

This review aims to critically evaluate sustainable smart sensing technologies and AI-driven platforms for real-time mycotoxin detection, highlighting innovations, integration across the food supply chain, current limitations, and future directions for safer, data-driven food safety management. This systematic review followed PRISMA guidelines and covered studies published between 2015 and 2025. Literature searches were conducted in Scopus, Web of Science, PubMed, IEEE Xplore, and Google Scholar, yielding a total sample of 620 identified records. Peer-reviewed articles on smart sensors, biosensors, and AI-driven mycotoxin monitoring were included. After title, abstract, and full-text screening based on predefined eligibility criteria, approximately 160 studies were retained and formed the final sample for qualitative synthesis across the food supply chain. Sustainable smart sensing and AI-driven platforms are transforming real-time mycotoxin detection across the food supply chain by enabling rapid, sensitive, and decentralized monitoring from farm to fork. Emerging biosensors, optical sensors, and IoT-enabled devices integrated with machine learning improve early warning, traceability, and decision-making. However, key gaps remain, including limited sensor robustness under variable field conditions, high costs of advanced materials, energy demands, and scarcity of large, standardized datasets for AI training. Interoperability between sensing platforms and regulatory frameworks is also underdeveloped. Sustainability challenges involve balancing analytical performance with low-energy operation, sensor recyclability, and accessibility for low-resource settings. Future directions should prioritize biodegradable and reusable sensor materials, edge-AI and low-power electronics, federated data-sharing models, and climate-resilient deployment strategies. Integrating predictive analytics with risk assessment and policy alignment will be essential for scalable, sustainable mycotoxin management systems.

Graphical Abstract