This paper proposes an innovative method based on AI, to reinforce traceability systems in detecting possible counterfeiting by product substitution. It is an item-based mass balance method that analyses the agreement of the traceability data flows not by using explicit (even stochastic) rules, but by exploiting the learning capabilities of a neural network. The system can then detect suspect information in a traceability data flow. The AI-based method was applied to a pork slaughtering and meat cutting chain case study, and used the weights of different cuts of a pork carcase as the training phase of AI. Any analogous carcase information along the supply line might indicate substitution or modification of the pork carcase cuts. 

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