Production of lactic acid from sucrose: strain selection, fermentation, and kinetic modeling.

Lactic acid is an important product arising from the anaerobic fermentation of sugars. It is used in the pharmaceutical, cosmetic, chemical, and food industries as well as for biodegradable polymer and green solvent production. In this work, several bacterial strains were isolated from industrial ethanol fermentation, and the most efficient strain for lactic acid production was selected. The fermentation was conducted in a batch system under anaerobic conditions for 50 h at a temperature of 34 degrees C, a pH value of 5.0, and an initial sucrose concentration of 12 g/L using diluted sugarcane molasses. Throughout the process, pulses of molasses were added in order to avoid the cell growth inhibition due to high sugar concentration as well as increased lactic acid concentrations. At the end of the fermentation, about 90% of sucrose was consumed to produce lactic acid and cells. A kinetic model has been developed to simulate the batch lactic acid fermentation results. The data obtained from the fermentation were used for determining the kinetic parameters of the model. The developed model for lactic acid production, growth cell, and sugar consumption simulates the experimental data well.

Study of kinetic parameters in a mechanistic model for bioethanol production through a screening technique and optimization.

The accurate description of the kinetics and robust modeling of biotechnological processes can only be achieved by incorporating reliable methodologies to easily update the model when there are changes in operational conditions. The purpose of this work is to provide a systematic approach with which to perform model parameters screening and updating in biotechnological processes. Batch experiments are performed to develop a mechanistic model, considering the effect of temperature on the kinetics, and further experiments (batch fermentations using sugar cane molasses from a different harvest) are used to validate the effectiveness of screening before parameters updating. The reduction in the number of kinetic parameters to be re-estimated enabled by the screening procedure reduces significantly the complexity of the optimization, which makes the updating procedure to be significantly quicker, while resulting in accurate performance of the updated model.

Estimation of temperature dependent parameters of a batch alcoholic fermentation process.

In this work, a procedure was established to develop a mathematical model considering the effect of temperature on reaction kinetics. Experiments were performed in batch mode in temperatures from 30 to 38 degrees C. The microorganism used was Saccharomyces cerevisiae and the culture media, sugarcane molasses. The objective is to assess the difficulty in updating the kinetic parameters when there are changes in fermentation conditions. We conclude that, although the re-estimation is a time-consuming task, it is possible to accurately describe the process when there are changes in raw material composition if a re-estimation of parameters is performed.