Modeling food spoilage in microbial risk assessment.

In this study, I describe a systematic approach for modeling food spoilage in microbial risk assessment that is based on the incorporation of kinetic spoilage modeling in exposure assessment by combining data and models for the specific spoilage organisms (SSO: fraction of the total microflora responsible for spoilage) with those for pathogens. The structure of the approach is presented through an exposure assessment application for Escherichia coli O157:H7 in ground beef. The proposed approach allows for identifying spoiled products at the time of consumption by comparing the estimated level of SSO (pseudomonads) with the spoilage level (level of SSO at which spoilage is observed). The results of the application indicate that ignoring spoilage in risk assessment could lead to significant overestimations of risk.