Mycotoxins are secondary fungal metabolites produced by certain types of filamentous fungi or molds, such as Aspergillus, Fusarium, Penicillium, and Alternaria spp. Mycotoxins are natural contaminants of agricultural commodities, and their prevalence may increase due to global warming. According to the Food and Agriculture Organization of the United Nations, approximately 25% of the world's food crops are annually contaminated with mycotoxins. Mycotoxin‐contaminated food and feed pose a high risk to both human and animal health. For instance, they possess carcinogenic, immunosuppressive, hepatotoxic, nephrotoxic, and neurotoxic effects. Hence, various approaches have been used to assess and control mycotoxin contamination. Significant challenges still exist because of the complex heterogeneous nature of food and feed composition. The potential of antigen‐based approaches, such as enzyme‐linked immunosorbent assay, flow injection immunoassay, chemiluminescence immunoassay, lateral flow immunoassay, and flow‐through immunoassay, would contribute to our understanding about mycotoxins' rapid identification, their isolation, and the basic principles of the detection technologies. Additionally, we address other emerging technologies of potential application in the detection of mycotoxins. The data included in this review focus on basic principles and results of the detection technologies and would be useful as benchmark information for future research. © 2019 Society of Chemical Industry
Mycotoxins are toxic secondary fungal metabolites produced by certain types of filamentous fungi, such as Aspergillus, Fusarium, and Penicillium spp. Mycotoxigenic fungi and their produced mycotoxins are considered to be an important issue in food and feed safety due to their toxic effects like carcinogenicity, immunosuppression, neurotoxicity, nephrotoxicity, and hepatotoxicity on humans and animals. To boost the safety level of food and feedstuff, detection and identification of toxins are essential at critical control points across food and feed chains. Zero-tolerance policies by the European Union and other organizations about the extreme low level of tolerance of mycotoxins contamination in food and feed matrices have led to an increasing interest to design more sensitive, specific, rapid, cost-effective, and safer to use mycotoxigenic fungi detection technologies. Hence, many mycotoxigenic fungi detection technologies have been applied to measure and control toxins contamination in food and feed substrates. PCR-based mycotoxigenic fungi detection technologies, such as conventional PCR, real-time PCR, nested PCR, reverse transcriptase (RT)-PCR, loop-mediated isothermal amplification (LAMP), in situ PCR, polymerase chain reaction-denaturing gradient gel electrophoresis (PCR DGGE), co-operational PCR, multiplex PCR, DNA arrays, magnetic capture-hybridization (MCH)-PCR and restriction fragment length polymorphism (RFLP), would contribute to our understanding about different mycotoxigenic fungi detection approaches and will enhance our capability about mycotoxigenic fungi identification, isolation and characterization at critical control points across food and feed chains. We have assessed the principles, results, the limit of detection, and application of these PCR-based detection technologies to alleviate mycotoxins contamination problem in complex food and feed substrates. The potential application of these detection technologies can reduce mycotoxins in complex food and feed matrices.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.