Food safety and quality

Tools to detect food safety issues before they arise


Together with Wageningen University, FAO held a workshop on 16 December 2022 about early warning tools and systems that can be used to manage imminent and emerging food safety issues. In attendance were food safety competent authorities, research and academia from 31 countries. The two virtual sessions were an opportunity to present a draft technical report that outlines various early warning tools and systems in food safety; gather feedback on the feasibility to apply the solutions proposed in the paper, such as Artificial Intelligence (AI) and Big Data in low- and medium-income countries; and identify matters of operational or strategic interest for further research or normative work in the area of early warning for food safety.

Identifying emerging food safety risks and having early warning signals have become vital as they allow for food safety managers to apply a proactive approach and avoid food safety incidents in the first place. Using real-time data and digital tools, such as AI, would take the approach a step further, workshop participants heard.

The technical report, currently being drafted by FAO and Wageningen University food safety experts, is aimed at:

  • Enhancing awareness and understanding of early warning and emerging risk identification tools and systems in food safety;
  • Encouraging the application of Big Data and AI in food safety early warning systems;
  • Considering prospective and innovative ways to implement food safety early warning tools in low- and middle-income countries (LMIC); and
  • Providing examples of open-access tools to support early warning of food safety issues.

Three systems to support food safety early warning and emerging issues identification have been presented in the workshop, namely:

  • the MediSys (Medical Information System of the European Media Monitor – a 24/7 media monitoring system based on event surveillance;
  • the MediSys-Food Fraud (MedISys-FF) – a media monitoring system providing event-based surveillance to rapidly identify potential public health threats using information from media reports; and
  • the SGS DIGICOMPLY, a data-driven platform for food risk prediction and compliance intelligence.

A practical session demonstrated how to create dedicated search queries based on user’s areas of interest that may relate to incidents, regulations, policy news, scientific publications or social news, choosing as well among topics, such as policies and laws, labeling, additives, official controls or standards.

“The timely availability of and accessibility to updated diverse sources and various types of food safety information is critical both for food safety early warning, for getting insights into emerging risks and for supporting the informed and faster risk management decision-making,” said Eleonora Dupouy, FAO Food Safety Officer.

“One of the conclusions from the study and this workshop is that the identification of early warning signals for risks in food and feed is considered important but is not always prioritized, therefore awareness needs to be further enhanced together with developing capability for the application of early warning digital tools,” she added.

Related links:

FAO. 2022. Thinking about the future of food safety – A foresight report. Rome. 

Digitalization, Food Safety and Trade. International Forum on Food Safety and Trade, Geneva, 23-24 April 2019 

FAO, WHO, WTO, AU. 2019. Science, Innovation and Digital Transformation at the service of food safety 

Ningjing Liu , Yamine Bouzembrak , Leonieke M. van den Bulk , Anand Gavai , Lukas J. van den Heuvel , Hans J.P. Marvin Automated food safety early warning system in the dairy supply chain using machine learning. Food Control 136 (2022) 108872


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