This review (open access) analyses trends in reported food fraud incidents over the past 5 years and trends in detection technologies, particularly the integration of AI and digital traceability and detection systems with analytical testing. The authors base their analysis on the EC Joint Research Centre monthly collation of food fraud media reports.
The authors highlight that food fraud is a worldwide issue, but its incidence is unevenly distributed across countries. A few countries account for a disproportionate share of reported cases. Notably, Italy has the highest number of food fraud incidents, with over 300 cases. India, and Pakistan also rank in the highest quintile, each reporting well over 150 cases. These three countries alone represent the upper 20 % bracket of fraud occurrence globally. A second tier of countries, including Spain, Brazil, Bolivia, Malaysia, Colombia, and Argentina, report a few dozen cases each. This skewed distribution suggests that detections of food fraud are concentrated where high-risk products, and active enforcement intersect.
The authors conclude that igrating AI-based predictive analytics with traditional and emerging lab methods significantly improves fraud detection, while blockchain and Internet of Things (IoT) innovations enable secure, real-time tracking of food authenticity. These technologies collectively strengthen the ability to uncover fraud
The paper emphasizes the need for interdisciplinary collaboration, harmonization, and updated regulatory frameworks to support the adoption of these multi-disciplinary approaches.
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