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Model predicts L. monocytogenes survival in cooked chicken during post-packaging pasteurization.

Researchers at the University of Arkansas and elsewhere set out to develop a predictive model that could assess the thermal inactivation of L. monocytogenes in chicken drum products during post-package hot water pasteurization.

Their work indicates that post-package hot water pasteurization can be an effective microbial intervention against L. monocytogenes in ready-to-eat (RTE) poultry products. In addition, they found that the Weibull model can be used to predict the thermal inactivation of L. monocytogenes in poultry products.

The prevalence of L. monocytogenes in fully cooked ready-to-eat poultry products poses a potential risk of infection. For this reason, much attention has been focused on the post-package pasteurization of fully cooked poultry products.

Fully cooked chicken drums were surface-inoculated with 7 log CFU per gram of Listeria innocua, a non-pathogenic surrogate of L. monocytogenes. Inoculated samples were vacuum-packaged and treated in a hot water bath at 60 C, 70 C, 80 C and 90 C for pre-determined intervals. Reductions in bacteria levels, in terms of log CFU per gram as determined by the standard plate count method, reached 4.30 after 30 minutes, 4.08 after 10 minutes, 3.54 after 6 minutes and 3.14 after 4.5 minutes at 60 C, 70 C, 80 C and 90 C, respectively. The elimination of 7 log CFU per gram of L. innocua occurred at 54, 28, 18 and 10 minutes of treatment at 60 C, 70 C, 80 C and 90 C, respectively.

Scientists used the Weibull model to predict the survival curve of L. innocua at each heating temperature. The root mean square errors of the fitted model, and the plot of predicted-versus-observed bacterial loads, were measures that indicated the predictive model was a good fit.

The model was further validated by predicting a new set of data that had been generated during the pilot plant test at the same temperatures for different heating intervals. The validation showed that the values determined with the new data fell inside the 95% prediction intervals of the values determined with the original data.

Further information. Yanbin Li, Department of Biological and Agricultural Engineering, University of Arkansas, Engineering 230, POSC O-411, Fayetteville, AR 72701; phone: 479-575-2881; fax: 479-575-2846; email: yanbinli@uark.edu.
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Publication:Emerging Food R&D Report
Date:Dec 1, 2013
Words:367
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