Joël Grabulos

Modeling Lactic Fermentation of Gowé Using Lactobacillus Starter Culture

A global model of the lactic fermentation step of gowé was developed by assembling blocks hosting models for bacterial growth, lactic acid production, and the drop of pH during fermentation. Commercial strains of Lactobacillus brevis and of Lactobacillus plantarum were used; their growth was modeled using Rosso’s primary model and the gamma concept as a secondary model. The optimum values of pH and temperature were 8.3 ± 0.3, 44.6 ± 1.2 °C and 8.3 ± 0.3, 3.2 ± 37.1 °C with μmax values of 1.8 ± 0.2 and 1.4 ± 0.1 for L. brevis and L. plantarum respectively. The minimum inhibitory concentration of undissociated lactic acid was 23.7 mM and 35.6 mM for L. brevis and L. plantarum, respectively. The yield of lactic acid was five times higher for L. plantarum than for L. brevis, with a yield of glucose conversion to lactic acid close to 2.0 for the former and 0.8 for the latter. A model was developed to predict the pH drop during gowé fermentation. The global model was partially validated during manufacturing of gowé. The global model could be a tool to aid in the choice of suitable starters and to determine the conditions for the use of the starter.

Modeling cereal starch hydrolysis during simultaneous saccharification and lactic acid fermentation; case of a sorghum-based fermented beverage, gowé

Gowé is an acidic beverage obtained after simultaneous saccharification and fermentation (SSF) of sorghum. A previous paper focused on modeling the growth of lactic acid bacteria during gowé processing. This paper focuses on modeling starch amylolysis to build an aggregated SSF model. The activity of α-amylase was modeled as a function of temperature and pH, and the hydrolysis rates of both native and soluble starch were modeled via a Michaelis-Menten equation taking into account the maltose and glucose inhibition constants. The robustness of the parameter estimators was ensured by step by step identification in sets of experiments conducted with different proportions of native and gelatinized starch by modifying the pre-cooking temperature. The aggregated model was validated on experimental data and showed that both the pre-cooking and fermentation parameters, particularly temperature, are significant levers for controlling not only acid and sugar contents but also the expected viscosity of the final product. This generic approach could be used as a tool to optimize the sanitary and sensory quality of fermentation of other starchy products.