Work

Leveraging artificial intelligence for mycotoxin management in food systems

Year: 2026

Type: article

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.

Source: npj Science of Food

DOI: 10.1038/s41538-026-01005-0

Authors: Francesca Caloni, Thomas Hartung

Institutions: University of Milan, Johns Hopkins University, University of Konstanz

Language: English

Topic: Mycotoxins in Agriculture and Food

Subfield: Plant Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDGs: Zero hunger, Good health and well-being

Open Access status: gold

Estimated APC paid: $2,790