The application of mathematical modeling to study and characterize lactic acid bacterial strains with pro-technological and functional features has gained attention in recent years to solve the problems relevant to the variabilities of the fermentation processes of sourdough. Since the key factors contributing to the sourdough quality are relevant to the starter strain growth and its metabolic activity, in this study, the cardinal growth parameters for pH, temperature (T), water activity (aw), and undissociated lactic acid of the sourdough strain Lactiplantibacillus plantarum ITM21B, were determined. The strain growth, pH, organic acids (lactic, acetic, phenyllactic, and hydroxy-phenyllactic), total free amino acids, and proteins were monitored during fermentation of a liquid sourdough based on wheat flour and gluten (Bio21B) after changing the starting T, pH, and inoculum load. Results demonstrated that the different fermentation conditions affected the strain growth and metabolite pattern. The organic acid production and growth performance were modeled in Bio21B, and the resulting predictive model allowed us to simulate in silico the strain performances in liquid sourdough under different scenarios. This mathematical predictive approach can be useful to optimize the fermentation conditions needed to obtain the suitable nutritional and technological characteristics of the L. plantarum ITM21B liquid sourdough.
Keywords: fermented flour; growth models; in silico simulations; organic acid modeling; protein profile.