To enhance the resilience of food systems to food safety risks, it is vitally important for national authorities and international organizations to be able to identify emerging food safety risks and to provide early warning signals in a timely manner. This review provides an overview of existing and experimental applications of artificial intelligence (AI), big data, and internet of things as part of early warning and emerging risk identification tools and methods in the food safety domain. There is an ongoing rapid development of systems fed by numerous, real‐time, and diverse data with the aim of early warning and identification of emerging food safety risks. The suitability of big data and AI to support such systems is illustrated by two cases in which climate change drives the emergence of risks, namely, harmful algal blooms affecting seafood and fungal growth and mycotoxin formation in crops. Automation and machine learning are crucial for the development of future real‐time food safety risk early warning systems. Although these developments increase the feasibility and effectiveness of prospective early warning and emerging risk identification tools, their implementation may prove challenging, particularly for low‐ and middle‐income countries due to low connectivity and data availability. It is advocated to overcome these challenges by improving the capability and capacity of national authorities, as well as by enhancing their collaboration with the private sector and international organizations.

Mobile applications (apps) have become popular among consumers to facilitate their existing food practices like cooking, shopping, and dining out. However, the feasibility of using mobile apps to facilitate sustainability transitions in food consumption is not well researched. In this study, we, therefore, propose a conceptual framework to illustrate how mobile apps can be developed in linking everyday food practices with sustainability transitions. Through the case study of dining out and with the help of focus group discussions, we seek to illustrate that practice theory might serve as a useful starting point for understanding the dynamics of food practices, their relevant sustainability dimensions, and the ways in which mobile apps can be used for changing current food practices into more sustainable ones. Among our main results are the findings that consumers prefer the sustainability food app to be integrated with dominant or mainstream apps, which are already used by consumers in the context of dining out. Besides being simple, functional, flexible, and rewarding, the information provided by the app should be reliable and trustworthy. Moreover, both science-based and practice-based information is necessary to provide sufficient guidance to consumers on how changes in food practice can be operationalized and implemented.

Salmonellaspp. control in pork supply chains has always been a challenging issue and insufficient control can lead to high social and economic consequences. Conventional risk management and risk management approaches and models are not sufficient to address potential food safety shocks caused bySalmonellaspp., as they mainly focus on assessing measures to reduceSalmonellaspp. risks instead of developing the resilience capability (e.g., flexibility to adapt to sudden changes in the risks). Our study is the first that incorporated the resilience concept to the quantitative modeling ofSalmonellaspp. spread in the pork supply chain. The objective of this study was to explore the resilience performance of the pork supply chain under different food safety shocks caused bySalmonellaspp., and to investigate the effectiveness of interventions on reducing the impact of these shocks on the resilience performance of the chain. Scenario analysis indicated that the effectiveness of the investigated resilience strategies or interventions depended on the risk profile (i.e., default, minimum, maximum level ofSalmonellaspp. contamination) of the pork supply chain. For pork supply chains with minimum and default risk profiles, more attention should be paid to increasing resilience of pigs towardsSalmonellaspp. infection. For supply chains with maximum risk profile, the focus should be on improving the performance of the slaughterhouse, such as careful evisceration, logistic slaughtering. To conclude, enhancing resilience performance of the pork supply chain can contribute to a safe pork supply.