Environment, Data, and Advanced Materials for Mycotoxin Management: Emerging Strategies for Detection, Prediction, and Sustainable Control

Abstract

Mycotoxin contamination remains a persistent challenge across agricultural and food systems because toxin formation is governed by interconnected environmental, biological, storage, and processing conditions. Temperature, moisture, relative humidity, water activity, pH, substrate composition, fungal species, and storage duration can collectively influence fungal growth and toxin production, making conventional endpoint monitoring insufficient for proactive risk management. At the same time, advances in functional materials and analytical technologies are creating new opportunities for sensitive detection and targeted removal of mycotoxins. This review connects three increasingly important dimensions of mycotoxin management: environmental conditions, data-driven assessment, and advanced materials. Particular attention is given to carbon-based materials, including graphene, graphene oxide, carbon nanotubes, carbon dots, and related nanocomposites, together with quantum dots and magnetic nanomaterials used for sensing, adsorption, and detoxification. Their physicochemical, optical, electrochemical, and surface properties enable sensitive recognition of toxins such as aflatoxin B1 while also providing opportunities for contaminant capture and removal. Emerging control strategies involving cold atmospheric plasma, polyphenols, natural essential oils, and functional nanomaterials are further evaluated from efficacy and sustainability perspectives. Building on these developments, the review discusses how environmental monitoring data, material-performance information, and sensing outputs could be integrated through data-driven models to support contamination prediction, material selection, and timely intervention. Rather than treating detection and remediation as independent processes, an integrated environment–data–materials framework is proposed for moving toward predictive and adaptive mycotoxin management. Remaining challenges include matrix effects, material safety, scalability, data quality, sensor reproducibility, and validation under real food and agricultural conditions.

Keywords: Mycotoxins; Environmental Monitoring; Data-Driven Prediction; Graphene-Based Materials; Sustainable Remediation

How to cite

Singh R, Parthasarathy S, Potti DK. (2026). Environment, Data, and Advanced Materials for Mycotoxin Management: Emerging Strategies for Detection, Prediction, and Sustainable Control. American Journal of Sustainable Science and Technology, 1(1), Article 5. https://aasrtresearch.org/articles/ajsst-2026-005.html

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