European food production systems have become very efficient in terms of high yield, quality and safety. However, these production systems are not sustainable since, amongst other reasons, a significant proportion of the production is wasted or lost in the supply chain. One of the strategies of the European Union is to achieve climate neutrality by moving towards a circular economy with better waste management. This includes, reducing food waste and losses, and reusing or recycling by-products of the food and feed production systems. A circular economy would greatly improve the sustainability of the European food systems, but attention must be paid to the emergence of (new) food safety hazards. New or not well-known hazards can occur because by-products are reintroduced into the system or new processing steps are used for recycling, and/or known hazards can accumulate in the food production chain due to the reuse of (by-)products. This review addresses food safety hazards in the circular biobased economy, covering the domains of plant production, animal production, aquaculture, and packaging. Instead of an exhaustive list of all potential hazards, example cases of circular food production systems are given, highlighting the known and potential emerging food safety hazards. Current literature covering emerging food safety hazards in the circular economy shows to be limited. Therefore, more research is needed to identify food safety hazards, to measure the accumulation and the distribution of such hazards in the food and feed production systems, and to develop control and mitigation strategies. We advocate a food safety by design approach.

The climate is changing in Europe: average temperatures are increasing, and so is the frequency of extreme weather events. Climate change has a severe impact on areas suitable for growing certain crops and on food safety, for example, affecting the occurrence of the aflatoxin contamination of maize. The aim of this study was to obtain insights into the impact of climate change on possible changes in land use in Europe, particularly in areas suitable for maize cultivation, and on the probability of the mycotoxin contamination of maize in order to give directions for long-term adaptation to climate change. By combining a land use model and a mycotoxin prediction model, the suitability of land for maize cultivation and the probability of aflatoxin contamination were estimated for suitable areas in Europe, comparing the current climate with the 2050 scenario. In 2050, the occurrence of aflatoxin contamination in Europe is predicted to severely increase, especially in Central and Southern Europe. More northern regions, presently unsuitable for maize cultivation, will become suitable for maize cultivation in 2050. In the baseline scenario, most regions suitable for maize cultivation have a low probability of aflatoxin contamination, whereas in 2050, about half of the regions suitable for maize cultivation have a medium to high probability of aflatoxin contamination. Regions for safely growing maize for human consumption will shift from the southern to the northern half of Europe.

The management of mycotoxin contamination in the supply chain is continuously evolving in response to growing knowledge about mycotoxins, shifting factors that influence mycotoxin occurrence, and ongoing technological developments. One of the technological developments is the potential for using artificial intelligence (AI) in mycotoxin management. AI can be used in various fields of mycotoxin management, including for predictive modelling of mycotoxins and for analytical detection and analyses. This review aimed to investigate the state-of-the-art of the use of AI for mycotoxin management. This review focuses on (1) predictive models for the presence of mycotoxins in commodities at both pre-harvest and post-harvest levels and (2) the detection of mycotoxins in samples by processing large datasets resulting from imaging data or chemical analyses of the sample. A systematic review was conducted, resulting in a total of 70 relevant references, including 15 references focusing on mycotoxin prediction models and 54 references focusing on mycotoxin detection, ranging from imaging to chemical analysis, and including relevant reviews. The AI applications and the most popular AI algorithms are presented. As shown by this review, AI is able to improve mycotoxin prediction models both at pre- and post-harvest levels and makes the emergence of non-invasive and fast detection methods such as imaging detection or electronic noses possible. A major challenge remains in the applicability and scalability of AI models to practical settings.

The Swedish risk management case of Baltic fatty fishes, in which dioxin levels may be too high, is a typical multidimensional food safety decision problem involving public health, economic, environmental and socio-cultural aspects. To effectively address the dioxin food safety problem, the multiple dimensions and conflicting interests of stakeholders have to be considered systematically when evaluating competing risk management options. The objectives of this study were to illustrate the applicability of the Multi-Criteria Decision Analysis (MCDA) method for multidimensional food safety risk management problems, and to evaluate the Swedish dioxin risk management using MCDA. The results show that the MCDA method is indeed a relevant tool for modelling the multifactorial Swedish dioxin problem and for initiating discussions amongst stakeholders to increase the acceptance of chosen strategies. Abolishing the derogation from the European Commission’s maximum limits for the presence of dioxins in Swedish fish is the dominant strategy for risk assessors, whereas the preferences provided by the other stakeholders would suggest a continuation of the derogation without providing consumer information. However, the preferences of female consumers match with the 2011 decision of the Swedish government to ask for a derogation in combination with consumer information. The conclusion drawn from our MCDA analysis is comparable to the government’s decision that—given the gradual reduction in dioxin concentrations in Baltic fish—the decision to continue providing consumer information or not mainly depends on how risk managers balance the preferences of the different stakeholders.

The presence of mycotoxins in cereals has led to large economic losses in Europe. In the course of the European project MyToolBox, prevention and control measures to reduce mycotoxin contamination in cereals were developed. This study aimed to estimate the impact of these prevention and control measures on both the reduction in crop losses and the increased volume of crops suitable for food and/or feed. It focused on the following measures: the use of fungicides during wheat cultivation, the use of resistant maize cultivars and/or biocontrol during maize cultivation, the use of real time sensors in storage silos, the use of innovative milling strategies during the pasta making process, and the employment of degrading enzymes during the process of bioethanol and Dried Distillers Grains with Solubles (DDGS) production. The impact assessment was based on the annual volume of cereals produced, the annual levels of mycotoxin contamination, and experimental data on the prevention and control measures collected in the course of the MyToolBox project. Results are expressed in terms of reduced volumes of cereals lost, or as additional volumes of cereals available for food meeting the current European legal limits. Results showed that a reduction in crop losses as well as an increase in the volume of crops suitable as food and/or feed is feasible with each proposed prevention or control measure along the supply chain. The impact was the largest in areas and in years with the highest mycotoxin contamination levels but would have less impact in years with low mycotoxin levels. In further research, the impact assessment may be validated using future data from more years and European sites. Decision makers in the food and feed supply chain can use this impact assessment to decide on the relevant prevention and control strategies to apply.

In order to minimise food waste, side streams from feed and food production are increasingly being (re-) used in food supply chains. Such reuse contributes to the desire to implement circularity in food and agricultural systems. However, the reuse of side products in circular food systems may impact food safety, for instance, contaminant residues present at low levels in biomass may accumulate when reusing streams. In order to assess potential food safety issues related to circular food systems, a framework has been developed in this study. Based on this framework, appropriate actions can be taken to prevent from human health risks. The framework consists of three steps: 1. Describing the changes in the food supply chain as a result of the circularity transition; 2. Identifying potential food safety hazards related to the change; and 3. Prioritising food safety hazards related to the circularity transition. For the prioritisation, both the presence of the hazards in final foods and the effects of the hazards on human health need to be assessed. Persistence of the hazard in the environment and potential transfer from the environment to the final food product are relevant elements to include. The framework was tested in three case studies, showing that it allows for a prioritisation between hazards. Based on the case study results, circularity not so much influences the health effects of the hazards, but rather their presence depending on the persistence and transfer of food safety hazards in a circular system.