减少食品中产毒真菌和真菌毒素的新策略和人工智能方法。

IF 3.9 3区 医学 Q2 FOOD SCIENCE & TECHNOLOGY
Toxins Pub Date : 2025-05-07 DOI:10.3390/toxins17050231
Fernando Mateo, Eva María Mateo, Andrea Tarazona, María Ángeles García-Esparza, José Miguel Soria, Misericordia Jiménez
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引用次数: 0

摘要

在公共卫生和消费者保护领域,产毒真菌在食品中的增殖和随后产生的真菌毒素是一个重大问题。本综述重点介绍了旨在防止食物基质中真菌生长和霉菌毒素污染的最新策略和新方法,而不是化学杀菌剂等可能留下有毒残留物并对人类和动物健康以及环境构成风险的传统方法。讨论的新方法包括植物衍生化合物的使用,如精油,被归类为一般公认安全(GRAS),多酚,乳酸菌,冷等离子体技术,纳米粒子(特别是金属纳米粒子,如银或锌纳米粒子),磁性材料和电离辐射。其中,精油、多酚和乳酸菌是传统杀菌剂的环保无毒替代品,同时具有很强的抗菌和抗真菌性能;精油和多酚也具有抗氧化活性。冷等离子体和电离辐射能够实现快速、非热和无化学物质的去污过程。纳米粒子和磁性材料具有稳定性强、释放可控、易于分离等优点。此外,本文还探讨了人工智能(特别是机器学习方法)在真菌种类鉴定和分类以及产毒真菌生长和随后在食品和培养基中产生霉菌毒素方面的应用的最新进展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New Strategies and Artificial Intelligence Methods for the Mitigation of Toxigenic Fungi and Mycotoxins in Foods.

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.

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来源期刊
Toxins
Toxins TOXICOLOGY-
CiteScore
7.50
自引率
16.70%
发文量
765
审稿时长
16.24 days
期刊介绍: Toxins (ISSN 2072-6651) is an international, peer-reviewed open access journal which provides an advanced forum for studies related to toxins and toxinology. It publishes reviews, regular research papers and short communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.
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