Modeling food spoilage in microbial risk assessment.

Konstantinos Koutsoumanis
Author Information
  1. Konstantinos Koutsoumanis: Aristotle University of Thessaloniki, Faculty of Agriculture, Department of Food Science and Technology, Laboratory of Food Hygiene and Microbiology, 54124 Thessaloniki, Greece. kkoutsou@agro.auth.gr

Abstract

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.

MeSH Term

Animals
Cattle
Colony Count, Microbial
Consumer Product Safety
Escherichia coli O157
Food Contamination
Food Handling
Food Microbiology
Humans
Kinetics
Meat Products
Models, Biological
Risk Assessment
Temperature
Time Factors

Word Cloud

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