Randomized trial explores AI methods for improving food safety and mycotoxin control, suggesting a shift in regulation.
AI-driven methods have been applied across mycotoxin research in detection, prediction, and control, offering high laboratory accuracy ( > 90%), robust forecasting (75–99%), and emerging mitigation strategies (80–86%). Integrating AI with multi-omics data, mixture toxicity modeling, and standardized protocols promises to enhance food safety, streamline regulatory decision-making, and reduce animal testing.
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Caloni et al. (2026) studied this question.
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