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

Abstract

Bacterial strains belonging to <i>Lacticaseibacillus paracasei</i> species are generally used as starters in food fermentations and/or as probiotics. In the current study, the growth cardinal parameters of four <i>L. paracasei</i> 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 <i>L. paracasei</i> whereas new equations were developed for the effect of pH. The estimated <i>T_min</i> 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 <i>pH_min</i> . Maximum specific growth rates of <i>L. paracasei</i> IMPC2.1 in white cabbage (<i>Brassica oleracea</i> var. <i>capitata</i>) were used to calculate the correction factor (<i>C_f</i> ) 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 <i>L. paracasei</i> strains in cabbage and predict the time to reach the targeted probiotic level (7 log₁₀ CFU/g) using <i>in silico</i> 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.