A Predictive Growth Model for Pro-technological and Probiotic Strains Fermenting White Cabbage.

Bacterial strains belonging to species are generally used as starters in food fermentations and/or as probiotics. In the current study, the growth cardinal parameters of four strains (IMPC2.1, IMPC4.1, P40 and P101), isolated from table olives or human source, were determined. Strains were grown in liquid medium and incubated at several temperatures (10 values from 5.5°C-40°C) and pH (15 values from 3.2 to 9.1) along the growth range. The cardinal temperature model was used to describe temperature effects on the maximum specific growth rate of whereas new equations were developed for the effect of pH. The estimated values ranged between -0.97°C and 1.95°C and were lower than 0°C for strains IMPC4.1 and P101. Strain P40 was able to grow in the most restricted range of temperature (from 1.95°C to 37.46°C), while strain IMPC4.1 was estimated to survive at extreme conditions showing the lowest . Maximum specific growth rates of IMPC2.1 in white cabbage ( var. ) were used to calculate the correction factor ( ) defined as the bias between the bacterial maximum specific growth rate in broth and in the food matrix. A simple bi-linear model was also developed for the effect of temperature on the maximum population density reached in white cabbage. This information was further used to simulate the growth of strains in cabbage and predict the time to reach the targeted probiotic level (7 log CFU/g) using simulations. This study demonstrates the potential of the predictive microbiology to predict the growth of beneficial and pro-technological strains in foods in order to optimize the fermentative process.