Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 7/7/2007
Publication Date: 7/16/2007
Citation: Juneja, V.K. 2007. Predictive models for use in thermally processed foods and the usda pathogen modeling program . Meeting Abstract. Interpretive Summary:
Technical Abstract: The use of heat to inactivate foodborne pathogens is a critical control point and the most common means of assuring the microbiological safety of processed foods. A key to optimization of the heating step is defining the heat resistance of target pathogens. Sufficient evidence exists to document that insufficient cooking, reheating and/or subsequent cooling of meat products are often contributing factors in food-poisoning outbreaks. Accordingly, our objectives were to determine the heat treatment required to achieve a specific lethality for foodborne pathogens (listed below), and to determine safe cooling rate for cooked meat. The effects of pH temperature and concentrations of sodium chloride, sodium pyrophosphate, and sodium lactate are among the variables that were considered when attempting to assess the heat inactivation kinetics of Escherichia coli O157:H7, Listeria monocytogenes, Salmonella spp. and spores of non-proteolytic Clostridium botulinum. Incorporation of these multiple barriers increased the sensitivity of these pathogens to heat, thereby reducing heating time/temperature requirements and ensuring the safety of ready-to-eat food products. Also, models to predict growth from surviving spores of Clostridium perfringens and proteolytic C. botulinum at temperatures applicable to the cooling of cooked meat were developed. Predictive inactivation kinetics (thermal death) and cooling deviation models for foodborne pathogens have been converted into an easy-to-use computer program (Pathogen Modeling Program) that is available on the USDA- Eastern Regional Research Center website. These models should aid processors and regulators in evaluating the safety of cooked products and are being used as building blocks for microbial risk assessment.