Nowadays, primary mathematical models are widely accepted as a tool for quantitative food microbiology. Such models are being used in conjunction with curve-fitting software to evaluate food-associated microbial growth. The three most commonly used models are Baranyi, Gompertz, and three-phase linear models. However, most of these models are not mechanistically-based and do not take into account the underlying physiological events. The ultimate goal of this study is to develop models that is more directly based on microbial physiological behavior and to better describe the transition periods of both lag/exponential and exponential/stationary phases.

In the study of lag/exponential transition, by using standard deviations from the trials, traditional smooth sigmoidal growth curve was obtainable through three-phase linear model by Monte Carlo simulation. Moreover, by using nutritional-shift procedure, the time course of critical physiological events related to lactose metabolism were mapped.

While studying the transition period from exponential to stationary phase, both agitation rate and inoculum size were investigated for the potential impact of spatial nutrient depletion on the transition abruptness. While agitation rate had limited influence, inoculum size was proved to affect the shape of growth curve. Furthermore, combining the result of rpoS mRNA expression study, the time course of cell response to starvation was determined.