Ready-to-Eat Egg Products Formulated with Nisin and Organic Acids to Control Listeria monocytogenes.

Formulating ready-to-eat (RTE) products with growth inhibitors minimizes the risk of listeriosis. In part I, RTE egg products formulated with 6.25 ppm nisin were evaluated to control Listeria monocytogenes. Individual experimental units were surface inoculated with 2.5-log CFU/g of L. monocytogenes, packaged in pouches with a headspace gas of 20:80 CO2:NO2, and stored at 4.4°C for 8 weeks. Formulations with finished product pH of 6.29 ± 0.07 limited growth to <2-log for 4 weeks. Products at pH values of 7.42 ± 0.12 and 7.84 ± 0.11 were not different (p > 0.05) from the control without nisin at pH 7.34 ± 0.13, all supported 4-log growth by 4 weeks. In part II, a nisin bioassay test was performed to evaluate the stability of nisin in eggs as affected by the product pH (6.00 ± 0.03, 7.00 ± 0.00, 7.50 ± 0.03, and 8.00 ± 0.02) and cooking to an internal temperature of 73.9 or 85°C for 90 s. The nisin activity loss increased as the product pH or the cooking temperature increased (p < 0.05). Part III evaluated the effectiveness of 6.25 ppm nisin in combination with either an acetate-based antimicrobial used at 1.0% (w/w) in egg formulation (A1.0), propionate at 0.3% (P0.3), acetate-diacetate at 1.0% (AD1.0), acetate-diacetate at 0.6% (AD0.6), and lactate at 2.0% (L2.0) as a positive control. These formulations had a finished product pH, moisture, and salt contents of 5.97 ± 0.21, 72.4 ± 0.9%, and 0.67 ± 0.05%, respectively. L. monocytogenes did not grow in formulations A1.0 and AD1.0, whereas L2.0 and P0.3 supported 2-log growth by weeks 6 and 15, respectively and AD0.6 supported <1-log growth over 20 weeks at 4.4°C. Evaluation of uninoculated control units in parts I and III showed no changes (p > 0.05) in the CO2 and O2 headspace gas composition, generally no detection or growth of background microbes, and no changes (p > 0.05) in the pH of the formulations during storage, all assuring absence of uncontrolled interferences for the growth of L. monocytogenes.

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.