Lactic Acid Production by ILactiplantibacillus plantarum/I AC 11S—Kinetics and Modeling

• Published in: Microorganisms (Basel) 2024-04, Vol.12 (4)
• Main Authors: Popova-Krumova, Petya, Danova, Svetla, Atanasova, Nikoleta, Yankov, Dragomir
• Format: Article
• Language: English
• Subjects: Lactic acid; Lactobacillus; Physiological aspects; Production processes
• ISSN: 2076-2607; 2076-2607
• DOI: 10.3390/microorganisms12040739

Lactic acid is a versatile chemical with wide application in many industries. It can be produced by the fermentation of different sugars by various lactobacilli and investigations on lactic acid production from different substrates and by different strains are still in progress. The present study aimed to study lactic acid production from lactose by Lactiplantibacillus plantarum AC 11S and to choose a mathematical model describing in the best way the experimental data obtained. The influence of initial substrate concentration was investigated, and optimal pH and temperature were determined. An unstructured mathematical model was developed comprising equations for bacterial growth, substrate consumption, and product formation. The model was solved with different terms for specific growth rates considering substrate and/or product inhibition. The best bacterial growth and lactic acid production were achieved at pH = 6.5 and 30 °C. Production of lactic acid was mainly growth-associated, and at initial substrate concentration over 15 g/L, a considerable product inhibition was observed. The parameters of different models were determined and compared. The modified Gompertz equation gave the best fit when solving only the equation for biomass growth at different initial substrate concentrations. Solving the entire set of differential equations for bacterial growth, substrate consumption, and product formation, the best results were obtained when using a variant of the logistic equation for biomass growth. This variant included a term for product inhibition and described in the best way all experimental data. Solving the model for different biomass concentrations showed that an increase in biomass led to a shorter lag phase and the stationary phase was reached faster. The results obtained, optimum conditions and the kinetic model, are good bases for studying pH-controlled fermentation, as well as a continuous process.