An official website of the United States government.

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Eliminating Listeria Monocytogenes from Ready-to-eat Products


The overall objective of this project is to help the industry implement inplant heat pasteurization of packaged fully cooked poultry and meat products to eliminate the human pathogen Listeria monocytogenes.
The specific objectives are:
<li> To validate a predictive model of heat and mass transfer with pathogen kinetics to predict pathogen kill as a function of time, moisture, and temperature, and </li>
<li> To design treatment schedules to achieve the targeted pathogen log reduction on various sizes and shapes of poultry products that are processed in different commercial steam or hot water cookers followed by cooling.</li></ol>

More information

APPROACH: In-package pasteurization of fully cooked chicken strips and bologna slices (to represent the worst scenario due to the high potential pathogen contaminations on the exposed surfaces) in various sizes and shapes of commercial packages will be used. Product temperature, cooking time, water purge (amount of water driven from the product by heating), and thermal kill of L. monocytogenes will be validated using a steam cooker, hot water cooker, and a flash cooker (under pressurized steam), respectively. </P>
The study will be conducted at the Further Processing facilities at the University of Arkansas. The conditions for post-cook pasteurization can be controlled to simulate the actual conditions in commercial processes. The effort will be conducted in two steps to validate the model for accurately predicting pathogen log reduction, time, and product temperature and moisture changes during pasteurization and cooling. The predictions within 95% confidence level of actual measurements will be considered sufficient. </P>
The models will be integrated into the ARS Pathogen Modeling Program, and the data sets will be archived in ComBase, a relational database of predictive microbiology information available through the Internet. </p>
A journal article will be submitted summarizing the results of the studies. A yearly and final report will be submitted to ARS-NPS and NAFS.</P>

Tamplin, Mark
University of Arkansas
Start date
End date
Project number
Accession number