Purpose: This study was designed to model the growth of single cells and cell populations from P. aeruginosa, and two factors, inoculum size and temperature shift, were considered.
Methods: A single cell growth image system was used to study the growth of P. aeruginosa single cells. A stochastic growth simulation method was developed to connect the growth of P. aeruginosa single cells and cell populations. And the lag time distributions with different inoculum sizes were obtained as a result of the simulation’s repetitive executions. In addition, the growth of P. aeruginosa single cells under different temperature shifts was investigated.
Results: The lag time decreased as the inoculum sizes increased. Integrated by an Individual-based Modelling (IbM) process, the parameters of the growth of P. aeruginosa single cells were then introduced into the reduced Baranyi & Roberts model to fit for stochastic growth simulations of P. aeruginosa. Moreover, the growth of P. aeruginosa showed a determinate tendency as the inoculum sizes increased. The stochastic growth of P. aeruginosa single cell under different temperature shifts was simulated using an IbM process, and it showed that an aggravated variability of the growth of P. aeruginosa was more affected by bigger temperature shifts.
Significance: It was deduced that studying the microbial dynamics at the single cell level, which take into account the growth viability and uncertainty of bacterial single cells, could help to establish a more reliable set of microbe-influenced food shelf life and food safety criteria.