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Modeling and Optimization of Lactic Acid Production using Cashew Apple Juice as Substrate

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The production of lactic acid by Lactobacillus casei B-442 was studied and modeled. Sugar feedstock was provided using cashew apple juice, an alternative glucose and fructose feedstock that proved to yield high concentrations of lactic acid. The fermentations were carried out in a 1-L fermenter under constant agitation (150 rpm) and controlled pH (6.5). Lactic acid production was evaluated through a dynamic study, varying the initial concentration of sugar in the range of 20 to 60 g/L. Biomass, reducing sugars, and lactic acid concentration were measured throughout the experiments. The highest production of lactic acid (59.3 g/L) was obtained operating the fermentation with 60 g/L of reducing sugar from the cashew apple juice. A rigorous kinetic model was developed for batch fermentation of cashew apple juice for lactic acid production by L. casei B-442. The growth of biomass and lactic acid production were affected by substrate limitation, substrate inhibition and lactic acid inhibition. The model assumed growth- and non-growth-associated lactic acid production and a term for microorganism death was also included in the model. Parameters of the kinetic model were determined based on experimental data by using the least mean squares method and Levenberg–Marquardt algorithm. The model validation was performed and the model was statistically able to fit the profiles for growth of biomass, sugar consumption and lactic acid production. The optimization of the process, using the model, was carried out and the optimum operating conditions aiming highest productivity, lowest production cost and highest gross profit are presented.

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The authors thank the financial support and scholarship from the Brazilian funding institute CNPq and CAPES.

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Correspondence to Fabiano A. N. Fernandes.

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Guilherme, A.A., Silveira, M.S., Fontes, C.P.M.L. et al. Modeling and Optimization of Lactic Acid Production using Cashew Apple Juice as Substrate. Food Bioprocess Technol 5, 3151–3158 (2012).

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