Abstract
One of the pillars on which food traceability systems are based is the unique identification and recording of products and batches along the supply chain. Patterns of these identification codes in time and place may provide useful information on emerging food frauds. The scanning of codes on food packaging by users results in interesting spatial-temporal datasets. The analysis of these data using artificial intelligence could advance current food fraud detection approaches. Spatial-temporal patterns of the scanned codes could reveal emerging anomalies in supply chains as a result of food fraud in the chain. These patterns have not been studied yet, but in other areas, such as biology, medicine, credit card fraud, etc., parallel approaches have been developed, and are discussed in this paper. This paper projects these approaches for transfer and implementation in food supply chains in view of future applications for early warning of emerging food frauds.
Subject
Plant Science,Health Professions (miscellaneous),Health (social science),Microbiology,Food Science
Reference36 articles.
1. Food fraud vulnerability and its key factors;Huisman;Trends Food Sci. Technol.,2017
2. Economically motivated adulteration (EMA) of food: Common characteristics of EMA incidents;Everstine;J. Food Prot.,2013
3. International survery of food fraud and related termi-nology: Preliminary results and discussion;Spink;J. Food Sci.,2019
4. Defining the Public Health Threat of Food Fraud;Spink;J. Food Sci.,2011
5. WHO (2022, July 01). Toxicological and Health Aspects of Melamine and Cyanuric Acid: Report of a WHO Expert Meeting. Health Canada, Ottawa, Canada, 1–4 December 2008. Available online: https://apps.who.int/iris/handle/10665/44106.
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献