Probabilistic modeling of the growth of Listeria monocytogenes: effect of nisin, temperature, and strain in the presence of potassium chloride or potassium sorbate

Abstract

ABSTRACTThe effects of temperature and nisin with either potassium chloride (KCl) or potassium sorbate on growth boundaries of three different Listeria monocytogenes strains in broth were studied. One ATCC7644 strain and two ready-to-eat food (RTE) isolates at different temperatures (4, 20, and 37°C) and nisin (0, 50, 100, 200, and 400 μg/mL) levels with either KCl (0, 1, 2, 3, and 4% w/v) or potassium sorbate (0, 0.05, 0.10, 0.15, and 0.20% w/v) were used. Highest and lowest growth probabilities were obtained for ATTC7644 and 120 (meat-based RTE isolate) strains, respectively with KCl and strain 137 (vegetable-based RTE isolate) was in between. However, the growth probabilities of the strains were just the opposite with the use of sorbate: strain 120 had the highest, whereas ATCC7644 strain had the lowest growth probability. Our results showed that nisin in combination with other preservatives may lead to diverse growth responses for different strains of L. monocytogenes. Validation studies performed in UHT whole milk and meat broth at 8 and 12°C and nisin levels of 25, 75, 150, and 250 μg/mL with either KCl (1.5%) or sorbate (0.125%) indicated 46% and 73% accurate predictions for milk and meat broth, respectively. Although a quick growth estimate was possible with the use of broth, we concluded that a model developed in a laboratory medium should not be extended in real food systems.

Keywords

• Logistic regression
• foodborne pathogen
• predictive microbiology
• strain variation