Predicting the Growth of Listeria monocytogenes in Cooked, Sliced Deli Turkey Breast as a Function of Clean-Label Antimicrobials, pH, Moisture, and Salt

Abstract

The use of antimicrobials in formulated ready-to-eat meat and poultry products has been identified as a major strategy to control Listeria monocytogenes. The U.S. Department of Agriculture's Food Safety and Inspection Service recommends no more than 2 log of Listeria outgrowth over the stated shelf life if antimicrobials are used as a control measure for a product with postlethality environmental exposure. This study was designed to understand the efficacy of a clean-label antimicrobial agents 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 agent 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 antimicrobials (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 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.