Advanced strategies for mycotoxin detection and biocontrol in food and feed system.
Loading...
Date
2025-06
Journal Title
Journal ISSN
Volume Title
Publisher
UNIVERSITE MOHAMED BOUDIAF - M’SILA
Abstract
Mycotoxins are toxic secondary metabolites produced by specific fungal species that pose
significant risks to human and animal health and cause substantial economic losses in the agrifood industry. This review provides a comprehensive overview of current strategies for the
detection and prevention of mycotoxins in food and feed. Traditional laboratory techniques, such
as high-performance liquid chromatography (HPLC), gas chromatography (GC), liquid
chromatography-tandem mass spectrometry (LC-MS/MS), and enzyme-linked immune
sorbentassays (ELISA), remain widely used for accurate mycotoxin quantification. In parallel,
emerging technologies such as biosensors, fluorescence spectroscopy, hyperspectral imaging,
and nanotechnology-based assays are gaining attention for their potential in rapid and on-site
detection. Recent advancements also highlight the integration of artificial intelligence (AI),
including machine learning algorithms and computer vision systems, to enhance the accuracy,
speed, and automation of detection processes, particularly in image-based and spectral analysis.
In terms of prevention, the study emphasizes good agricultural practices, post-harvest
management, physical and chemical detoxification techniques, and regulatory measures
implemented to mitigate mycotoxin contamination. By combining traditional expertise with
innovative technologies, including AI, this work aims to support the advancement of food safety
systems and the protection of public health.
Description
Keywords
mycotoxins, detection techniques, biosensors, artificial intelligence, preventive strategies, food safety.