RIKILT-Institute of Food Safety, Wageningen UR, P.O. Box 230, NL-6700 AE, Wageningen, The Netherlands.
J Food Prot. 2010 Jun;73(6):1153-9. doi: 10.4315/0362-028x-73.6.1153.
This article provides an overview of available systems for management of Fusarium mycotoxins in the cereal grain supply chain, with an emphasis on the use of predictive mathematical modeling. From the state of the art, it proposes future developments in modeling and management and their challenges. Mycotoxin contamination in cereal grain-based feed and food products is currently managed and controlled by good agricultural practices, good manufacturing practices, hazard analysis critical control points, and by checking and more recently by notification systems and predictive mathematical models. Most of the predictive models for Fusarium mycotoxins in cereal grains focus on deoxynivalenol in wheat and aim to help growers make decisions about the application of fungicides during cultivation. Future developments in managing Fusarium mycotoxins should include the linkage between predictive mathematical models and geographical information systems, resulting into region-specific predictions for mycotoxin occurrence. The envisioned geographically oriented decision support system may incorporate various underlying models for specific users' demands and regions and various related databases to feed the particular models with (geographically oriented) input data. Depending on the user requirements, the system selects the best fitting model and available input information. Future research areas include organizing data management in the cereal grain supply chain, developing predictive models for other stakeholders (taking into account the period up to harvest), other Fusarium mycotoxins, and cereal grain types, and understanding the underlying effects of the regional component in the models.
本文概述了谷物供应链中真菌毒素管理的可用系统,重点介绍了预测数学模型的应用。从现有技术出发,提出了建模和管理方面的未来发展方向及其挑战。目前,基于谷物的饲料和食品产品中的真菌毒素污染是通过良好农业规范、良好生产规范、危害分析关键控制点、检查以及最近的通知系统和预测数学模型来管理和控制的。大多数谷物中镰刀菌毒素的预测模型主要集中在小麦中的脱氧雪腐镰刀菌烯醇上,旨在帮助种植者在种植过程中做出使用杀菌剂的决策。管理镰刀菌毒素的未来发展应包括预测数学模型和地理信息系统之间的联系,从而针对真菌毒素的发生进行特定地区的预测。设想中的面向地理的决策支持系统可以将各种特定用户需求和地区的基础模型以及各种相关数据库纳入其中,以便用(面向地理的)输入数据为特定模型提供信息。根据用户需求,系统会选择最合适的模型和可用的输入信息。未来的研究领域包括组织谷物供应链中的数据管理、为其他利益相关者(考虑到收获前的时间段)开发预测模型、其他镰刀菌毒素和谷物类型,并了解模型中区域成分的潜在影响。