Abstract

In biotracing systems, downstream chain information and model-based approaches are used to trace the sources of microbial contamination in a food chain. This article includes the results of a biotracing model for Salmonella in the pork slaughter process chain. A Bayesian belief network model was used in which information on the Salmonella level at different locations in the slaughterhouse were used in combination with prior knowledge about the dynamics of Salmonella throughout the slaughter line. Data collected in a Dutch slaughterhouse were used to specify prior beliefs about the model inputs and to iteratively refine the distributions of the parameters in the model to obtain an optimal description of that specific slaughterhouse. The primary purpose of the model is to trace the sources of contamination for individual Salmonella-positive carcasses at the end of the slaughter line. The model results indicated that house flora on or in the carcass splitter was the source of contamination for many carcasses, especially for those that carried contamination on the cutting side. The results also indicated that the parameter values of the model may be subject to temporal variation and can be used as a tool to provide estimates of such trends. This model illustrates the concept of biotracing, gives insight into the dynamics of Salmonella in the slaughter line, and indicates the sites in the line where data collection is most effective for biotracing. This biotracing model was implemented as an interactive computer application, which is a step in the process toward an operational biotracing system by which a stakeholder can initiate immediate responses to Salmonella contamination and other hazards in the pork slaughterhouse.

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