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Leveraging artificial intelligence for mycotoxin management in food systems
Francesca Caloni1, Thomas Hartung2,3
1Department of Environmental Science and Policy (ESP), Università degli Studi di Milano, Milan, Italy.
Abstract:
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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