Advanced strategies for mycotoxin detection and biocontrol in food and feed system.
| dc.contributor.author | BEDIRA SABAH GHIAT MERZAQA CHIKOUCHE NAZHAT EL ZAMAN En/ Dr. Yamina BEN MIRI | |
| dc.date.accessioned | 2025-07-01T12:39:59Z | |
| dc.date.available | 2025-07-01T12:39:59Z | |
| dc.date.issued | 2025-06 | |
| dc.description.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. | |
| dc.identifier.uri | https://repository.univ-msila.dz/handle/123456789/46553 | |
| dc.language.iso | en | |
| dc.publisher | UNIVERSITE MOHAMED BOUDIAF - M’SILA | |
| dc.subject | mycotoxins | |
| dc.subject | detection techniques | |
| dc.subject | biosensors | |
| dc.subject | artificial intelligence | |
| dc.subject | preventive strategies | |
| dc.subject | food safety. | |
| dc.title | Advanced strategies for mycotoxin detection and biocontrol in food and feed system. | |
| dc.type | Thesis |