Predicting the growth of Listeria monocytogenes in cooked sliced deli turkey breast as function of clean label antimicrobial, pH, moisture and salt

Abstract

The use of antimicrobials in formulations of ready-to-eat meat and poultry products has been identified as a major strategy to control Listeria monocytogenes . The USDA-FSIS recommends no more than 2-logs of Listeria outgrowth over the stated shelf life if antimicrobials are used as a control measure for a product with post-lethality environmental exposure. This study was designed to understand the efficacy of a clean label antimicrobial against the growth of L. monocytogenes as affected by the product attributes. A response surface method-central composite design was used to investigate the effects of product pH, moisture, salt content, and a commercial “clean-label” antimicrobial on the growth of L. monocytogenes in a model turkey deli meat formulation. Thirty treatment combinations of pH (6.3, 6.5, and 6.7), moisture (72, 75, and 78%), salt (1.0, 1.5, and 2.0%), and antimicrobial (0.75, 1.375, and 2.0%) with six replicated center points and eight design star points were evaluated. Treatments were surface inoculated with a 3 log 10 CFU/g target of a five-strain L. monocytogenes cocktail, vacuum packaged, and stored at 5°C for up to 16 weeks. Populations of L. monocytogenes were enumerated from triplicate samples every week until the stationary growth phase was reached. The enumeration data was fitted to a Baranyi and Roberts growth curve to calculate the lag time and maximum growth rate for each treatment.  Linear least-squares regression of the lag-time and growth-rate against the full quadratic, including the second order interaction terms, design matrix was performed. Both lag time and maximum growth rate were significantly affected ( p <0.01) by the antimicrobial concentration and product pH. Product moisture and salt content affected ( p <0.05) lag phase and maximum growth rate, respectively. The availability of a validated growth model assists meat scientists and processors with faster product development and commercialization.