Specialists ponder on leveraging technology to enable early detection of food safety threats

U.S – The United Nations’ Food and Agriculture Organization (FAO) and Wageningen University have recently co-hosted a workshop on early warning tools and systems that can be used to handle impending and developing food safety risks.

Food safety experts, researchers, and academics from 31 nations attended the webinar, which was held on December 16, 2022.

A draft technical paper outlining potential early warning systems and technologies for food safety was presented throughout the two virtual meetings.

Aside from that, the webinar sought opinions on the viability of implementing the solutions suggested in the paper, such as artificial intelligence (AI) and big data, in low- and middle-income nations (LMICs).

During the event, issues of operational or strategic significance for more study or normative work in the field of food safety early alerts were also recognized.

As it enables food safety managers to take a proactive approach and stop food safety events before they happen, recognizing emerging food safety hazards and having early warning signals have become essential.

Utilizing real-time data and digital tools like AI can improve a proactive approach to food safety.

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.

It also aims to encourage the application of Big Data and AI in food safety early warning systems and the consideration of prospective and innovative ways to implement food safety early warning tools LMICs.

Moreover, the technical report aims to provide 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 were presented in the virtual workshop including the Medical Information System of the European Media Monitor (MedISys), MediSys-Food Fraud (MedISys-FF), and SGS DIGICOMPLY.

MedISys is a 24/7 media monitoring system based on event surveillance while MedISys-FF is a media monitoring system providing event-based surveillance to rapidly identify potential public health threats using information from media reports.

Meanwhile, SGS DIGICOMPLY is a data-driven platform for food risk prediction and compliance intelligence.

Using themes like rules and regulations, labels, additives, official controls, or standards, a practical session showed how to develop specialized search queries based on users’ areas of interest that may relate to incidents, policy news, scientific papers, or social news.

Early warning systems for food safety, gaining insight into emerging, and facilitating faster and more informed risk management decision-making all depend on rapid availability and accessibility to updated information from a variety of sources and formats.

One of the findings from the study and workshop is that while identifying early warning signs of risks in food and feed is vital, it is not always given priority. As a result, awareness must be raised further along with the development of capability for the use of early warning digital technologies.

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