Safe food and feed through an integrated toolbox for mycotoxin management: the MyToolBox approach

There is a pressing need to mobilise the wealth of knowledge from the international mycotoxin research conductedover the past 25-30 years, and to perform cutting-edge research where knowledge gaps still exist. This knowledgeneeds to be integrated into affordable and practical tools for farmers and food processors along the chain inorder to reduce the risk of mycotoxin contamination of crops, feed and food. This is the mission of MyToolBox – a four-year project which has received funding from the European Commission. It mobilises a multi-actorpartnership (academia, farmers, technology small and medium sized enterprises, food industry and policystakeholders) to develop novel interventions aimed at achieving a significant reduction in crop losses due tomycotoxin contamination. Besides a field-to-fork approach, MyToolBox also considers safe use options ofcontaminated batches, such as the efficient production of biofuels. Compared to previous efforts of mycotoxin reduction strategies, the distinguishing feature of MyToolBox is to provide the recommended measures to theend users along the food and feed chain in a web-based MyToolBox platform (e-toolbox). The project focuseson small grain cereals, maize, peanuts and dried figs, applicable to agricultural conditions in the EU and China. Crop losses using existing practices are being compared with crop losses after novel pre-harvest interventionsincluding investigation of genetic resistance to fungal infection, cultural control (e.g. minimum tillage or cropdebris treatment), the use of novel biopesticides suitable for organic farming, competitive biocontrol treatment and development of novel modelling approaches to predict mycotoxin contamination. Research into post-harvestmeasures includes real-time monitoring during storage, innovative sorting of crops using vision-technology, novelmilling technology and studying the effects of baking on mycotoxins at an industrial scale

Decision support system for integrated management of mycotoxins in feed and food supply chains

Mycotoxins present a global food safety threat of our feed and food. Mycotoxins are toxic metabolites of certain fungi in agricultural products that are harmful to animal and human health. The presence of mycotoxins in these products depends on a variety of management and environmental factors in the field, during storage and/or processing of feed and food commodities. To date, information on mycotoxin management is available, but is not easy to access by supply chain actors. This study aimed to design, build and test a Decision Support System (DSS) that can help decision making on mycotoxin management by various actors along the feed and food supply chains. As part of this, available knowledge and data on mycotoxin prevention and control were collected and synthesised into easy to understand guidelines and tools for various groups of end-users. The DSS consists of four different modules: (a) static information module and (b) scenario analysis module, (c) dynamic module for forecasting mycotoxins, and (d) dynamic module for real-time monitoring of moulds/mycotoxins in grain silos. Intended end-users are all end-user groups for modules (a) and (b); growers and collectors for module (c) and; post-harvest storage managers for module (d). The DSS is user-friendly and accessible through PCs, tablets and smartphones (see https://mytoolbox-platform.com/). In various phases of the DSS development, the tool has been demonstrated to groups of end-users, and their suggestions have been taken into account, whenever possible. Also, a near final version has been tested with individual farmers on the easiness to use the system. In this way we aimed to maximise the DSS uptake by actors along the chain. Ultimately, this DSS will improve decision making on mycotoxin management; it will assist in reducing mycotoxin contamination in the key crops of Europe, thereby reducing economic losses and improving animal and human health

Safe food and feed through an integrated toolbox for mycotoxin management: the MyToolBox approach

There is a pressing need to mobilise the wealth of knowledge from the international mycotoxin research conducted over the past 25-30 years, and to perform cutting-edge research where knowledge gaps still exist. This knowledge needs to be integrated into affordable and practical tools for farmers and food processors along the chain in order to reduce the risk of mycotoxin contamination of crops, feed and food. This is the mission of MyToolBox – a four-year project which has received funding from the European Commission. It mobilises a multi-actor partnership (academia, farmers, technology small and medium sized enterprises, food industry and policy stakeholders) to develop novel interventions aimed at achieving a significant reduction in crop losses due to mycotoxin contamination. Besides a field-to-fork approach, MyToolBox also considers safe use options of contaminated batches, such as the efficient production of biofuels. Compared to previous efforts of mycotoxin reduction strategies, the distinguishing feature of MyToolBox is to provide the recommended measures to the end users along the food and feed chain in a web-based MyToolBox platform (e-toolbox). The project focuses on small grain cereals, maize, peanuts and dried figs, applicable to agricultural conditions in the EU and China. Crop losses using existing practices are being compared with crop losses after novel pre-harvest interventions including investigation of genetic resistance to fungal infection, cultural control (e.g. minimum tillage or crop debris treatment), the use of novel biopesticides suitable for organic farming, competitive biocontrol treatment and development of novel modelling approaches to predict mycotoxin contamination. Research into post-harvest measures includes real-time monitoring during storage, innovative sorting of crops using vision-technology, novel milling technology and studying the effects of baking on mycotoxins at an industrial scale

A framework for integrated environmental health impact assessment of systemic risks

Traditional methods of risk assessment have provided good service in support of policy, mainly in relation to standard setting and regulation of hazardous chemicals or practices. In recent years, however, it has become apparent that many of the risks facing society are systemic in nature – complex risks, set within wider social, economic and environmental contexts. Reflecting this, policy-making too has become more wide-ranging in scope, more collaborative and more precautionary in approach. In order to inform such policies, more integrated methods of assessment are needed. Based on work undertaken in two large EU-funded projects (INTARESE and HEIMTSA), this paper reviews the range of approaches to assessment now in used, proposes a framework for integrated environmental health impact assessment (both as a basis for bringing together and choosing between different methods of assessment, and extending these to more complex problems), and discusses some of the challenges involved in conducting integrated assessments to support policy

Financial Impact of a Dioxin Incident in the Dutch Dairy Chain

The aim of this study was to quantify the financial consequences of a milk-dioxin crisis on the stages of the dairy chain involved. The milk dioxin contamination impact model was designed for this purpose and also was used to estimate the net costs of control measures limiting the impact. Results obtained based on the assumption of the worst-case scenario in which the entire daily production of each business unit from feed supplier to milk processor is contaminated suggested that the financial impact of one dioxin incident would be J141.2 million. Another assumption was that the dioxin contamination started at one feed processing plant and was detected 2 weeks after initial contamination (the high-risk period), which would result in the involvement of 714 dairy farms, 26 milk processors, and 2,664 retailers. The stages of the chain that contributed most to the total net costs were the milk processor (76.9%) and the dairy farm (20.5%). If the high-risk period were shorter, i.e., 3 days, the estimated total financial impact decreases to J10.9 million. Thus, early detection of the contamination is crucial for decreasing the number of food businesses involved and lowering the total financial impact. The most influential inputs of the model were the sale price of milk at the processing stage, the daily amount of milk processed per processing plant, the farm-blocking period, and the daily amount of milk produced per farm. However, the effect of these inputs on the total financial impact was less than 10.0%. These results can be used to establish priorities in the application of control measures to limit the financial and public health impacts of a possible food safety inciden

Financial Impact of a Dioxin Incident in the Dutch Dairy Chain

The aim of this study was to quantify the financial consequences of a milk-dioxin crisis on the stages of the dairy chain involved. The milk dioxin contamination impact model was designed for this purpose and also was used to estimate the net costs of control measures limiting the impact. Results obtained based on the assumption of the worst-case scenario in which the entire daily production of each business unit from feed supplier to milk processor is contaminated suggested that the financial impact of one dioxin incident would be J141.2 million. Another assumption was that the dioxin contamination started at one feed processing plant and was detected 2 weeks after initial contamination (the high-risk period), which would result in the involvement of 714 dairy farms, 26 milk processors, and 2,664 retailers. The stages of the chain that contributed most to the total net costs were the milk processor (76.9%) and the dairy farm (20.5%). If the high-risk period were shorter, i.e., 3 days, the estimated total financial impact decreases to J10.9 million. Thus, early detection of the contamination is crucial for decreasing the number of food businesses involved and lowering the total financial impact. The most influential inputs of the model were the sale price of milk at the processing stage, the daily amount of milk processed per processing plant, the farm-blocking period, and the daily amount of milk produced per farm. However, the effect of these inputs on the total financial impact was less than 10.0%. These results can be used to establish priorities in the application of control measures to limit the financial and public health impacts of a possible food safety inciden

Optimizing bulk milk dioxin monitoring based on costs and effectiveness

Dioxins are environmental pollutants, potentially present in milk products, which have negative consequences for human health and for the firms and farms involved in the dairy chain. Dioxin monitoring in feed and food has been implemented to detect their presence and estimate their levels in food chains. However, the costs and effectiveness of such programs have not been evaluated. In this study, the costs and effectiveness of bulk milk dioxin monitoring in milk trucks were estimated to optimize the sampling and pooling monitoring strategies aimed at detecting at least 1 contaminated dairy farm out of 20,000 at a target dioxin concentration level. Incidents of different proportions, in terms of the number of contaminated farms, and concentrations were simulated. A combined testing strategy, consisting of screening and confirmatory methods, was assumed as well as testing of pooled samples. Two optimization models were built using linear programming. The first model aimed to minimize monitoring costs subject to a minimum required effectiveness of finding an incident, whereas the second model aimed to maximize the effectiveness for a given monitoring budget. Our results show that a high level of effectiveness is possible, but at high costs. Given specific assumptions, monitoring with 95% effectiveness to detect an incident of 1 contaminated farm at a dioxin concentration of 2 pg of toxic equivalents/g of fat [European Commission's (EC) action level] costs €2.6 million per month. At the same level of effectiveness, a 73% cost reduction is possible when aiming to detect an incident where 2 farms are contaminated at a dioxin concentration of 3 pg of toxic equivalents/g of fat (EC maximum level). With a fixed budget of €40,000 per month, the probability of detecting an incident with a single contaminated farm at a dioxin concentration equal to the EC action level is 4.4%. This probability almost doubled (8.0%) when aiming to detect the same incident but with a dioxin concentration equal to the EC maximum level. This study shows that the effectiveness of finding an incident depends not only on the ratio at which, for testing, collected truck samples are mixed into a pooled sample (aiming at detecting certain concentration), but also the number of collected truck samples. In conclusion, the optimal cost-effective monitoring depends on the number of contaminated farms and the concentration aimed at detection. The models and study results offer quantitative support to risk managers of food industries and food safety authoritie