Mateo Fernando, Mateo Eva María, Tarazona Andrea, García-Esparza María Ángeles, Soria José Miguel, Jiménez Misericordia
Department of Electronic Engineering, ETSE, (UV), Burjassot, 46100 Valencia, Spain.
Department of Microbiology and Ecology, Faculty of Medicine and Odontology, University of Valencia (UV), 46010 Valencia, Spain.
Toxins (Basel). 2025 May 7;17(5):231. doi: 10.3390/toxins17050231.
The proliferation of toxigenic fungi in food and the subsequent production of mycotoxins constitute a significant concern in the fields of public health and consumer protection. This review highlights recent strategies and emerging methods aimed at preventing fungal growth and mycotoxin contamination in food matrices as opposed to traditional approaches such as chemical fungicides, which may leave toxic residues and pose risks to human and animal health as well as the environment. The novel methodologies discussed include the use of plant-derived compounds such as essential oils, classified as Generally Recognized as Safe (GRAS), polyphenols, lactic acid bacteria, cold plasma technologies, nanoparticles (particularly metal nanoparticles such as silver or zinc nanoparticles), magnetic materials, and ionizing radiation. Among these, essential oils, polyphenols, and lactic acid bacteria offer eco-friendly and non-toxic alternatives to conventional fungicides while demonstrating strong antimicrobial and antifungal properties; essential oils and polyphenols also possess antioxidant activity. Cold plasma and ionizing radiation enable rapid, non-thermal, and chemical-free decontamination processes. Nanoparticles and magnetic materials contribute advantages such as enhanced stability, controlled release, and ease of separation. Furthermore, this review explores recent advancements in the application of artificial intelligence, particularly machine learning methods, for the identification and classification of fungal species as well as for predicting the growth of toxigenic fungi and subsequent mycotoxin production in food products and culture media.
产毒真菌在食品中的增殖以及随后霉菌毒素的产生，是公共卫生和消费者保护领域的一个重大问题。本综述重点介绍了近期旨在防止食品基质中真菌生长和霉菌毒素污染的策略和新兴方法，这与传统方法如化学杀菌剂不同，化学杀菌剂可能会留下有毒残留物，并对人类、动物健康以及环境构成风险。所讨论的新方法包括使用植物源化合物，如被归类为一般认为安全（GRAS）的精油、多酚、乳酸菌、冷等离子体技术、纳米颗粒（特别是金属纳米颗粒，如银或锌纳米颗粒）、磁性材料和电离辐射。其中，精油、多酚和乳酸菌为传统杀菌剂提供了环保且无毒的替代品，同时展现出强大的抗菌和抗真菌特性；精油和多酚还具有抗氧化活性。冷等离子体和电离辐射能够实现快速、非热且无化学残留的去污过程。纳米颗粒和磁性材料具有稳定性增强、控释和易于分离等优点。此外，本综述还探讨了人工智能，特别是机器学习方法在真菌物种鉴定和分类以及预测食品和培养基中产毒真菌生长及随后霉菌毒素产生方面的最新进展。
