Dynamics of low (1-4 cells) vs high populations of Listeria monocytogenes and Salmonella Typhimurium in fresh-cut salads and their sterile liquid or solidified extracts

The growth variability of low or high populations of Listeria monocytogenes and Salmonella Typhimurium in fresh-cut lettuce and cabbage was studied. The salads were inoculated with a few (1-4) or 1000 cells/sample of the above organisms and stored at 8 °C. Their liquid or solidified sterile extracts were also inoculated with the same cell numbers to evaluate the behavior of pathogens in the presence or absence of the epiphytic flora and illustrate the effect of the micro-environment structure, where growth may occur. The sterile extracts were stored at 8-10 °C simulating marginal temperature fluctuations. Inoculum of 1000 cells/sample increased with limited variation (SD < 0.5 log CFU/g) on vegetable salads, as opposed to the great variability (<0.7-3.4 log CFU/g) in the growth from 1 to 4 cells/sample. Total logarithmic increase of 1000 cells/sample of the pathogens on the salads ranged from 1.8 to 2.1 log CFU/g, contrary to 1-4 cells/sample, which exhibited higher increase (2.7-3.4 log CFU/g). The latter suggests that “fail-dangerous” implications may derive from challenge tests with unrealistic high inocula. Different batches of vegetables used for preparation of sterile extracts, introduced high variability in the growth of 1-4 cells/sample, suggesting nutrient-dependent effect on growth of pathogens. Low inoculum of L. monocytogenes did not increase in sterile cabbage extracts, whereas they increased from 1 to 3.5 logs in cabbage salad, probably due to the stimulatory effect of indigenous flora. In contrast, 1-4 cells/sample of S. Typhimurium grew only on the solidified extract of cabbage but not on the salad, indicating competitive activity of the indigenous microflora against the pathogen. Salmonella showed no growth at 8 °C but increased 4 logs at 10 °C, illustrating the impact of boundary storage conditions. Monte Carlo simulation of bacterial growth based on broth data overestimated growth of L. monocytogenes on lettuce, while remarkably underestimated the actual increase in cabbage. Significant deviation between model and data is likely when extrapolating broth-based simulations of growth from low populations in foods, due to the various factors affecting the microbial growth on a real food, which are (inevitably) ignored by broth-based models.