In alcoholic fermentation processes, ethanol is the main component that is toxic to yeast because it acts as a noncompetitive inhibitor of metabolism. One way of overcoming the inhibition effect on yeast is to extract the ethanol from the broth during the fermentation. The present work evaluates ethanol production by extractive batch fermentation using CO 2 as a stripping gas. Investigation was first made of the influence of specific CO 2 flow rate (ϕ) and solution temperature on ethanol stripping. The best results, in terms of ethanol removal, were obtained at 2.0 vvm and 34.0 °C. Modeling of conventional and extractive ethanol fermentation was then performed considering cell growth, substrate consumption, ethanol production, and the entrainment of ethanol and water using first-order equations. The hybrid Andrews−Levenspiel model was able to describe the kinetics of the conventional fermentation process, and a model proposed here could accurately predict the behavior of the extractive fermentation. In all the extractive fermentations, there was faster substrate uptake and earlier substrate exhaustion, compared to the conventional fermentation. Extractive fermentation, with stripping initiated after 3 h at an ethanol concentration of 43.3 g•L −1 , resulted in an ethanol productivity (in g•L −1 •h −1 ) that was around 25% higher, and finished about 2 h earlier, compared to the control fermentation.

The ethanol accumulated in the broth during fermentation is the main component toxic to yeast, causing slower yeast growth and decreased ethanol production. One way of overcoming this inhibition effect is to use extractive fermentation, where the ethanol is removed from the broth during the fermentation process. The present work evaluates ethanol production by extractive fed-batch fermentation with CO 2 stripping, under different conditions of substrate concentration in the must feed (Cs F ), vat filling time (F t ), and start time of ethanol stripping with CO 2 . First, the process kinetic parameters were estimated by modeling of conventional fed-batch fermentations (without stripping) in a 5 L bubble column bioreactor, with fitting of the model to experimental data. This procedure used a sucrose concentration of 180 g•L −1 in the must feed, temperature of 34.0 °C, and vat filling times of 3 and 5 h. Subsequently, extractive fed-batch ethanol fermentations were performed at 34.0 °C with a sucrose concentration of 180 g•L −1 in the feed, specific CO 2 flow rate (ϕ) of 2.5 vol•vol −1 •min −1 (vvm), and F t of 3 or 5 h, starting ethanol stripping with CO 2 after 3 or 5 h of fermentation. The hybrid Andrews−Levenspiel model was able to provide accurate descriptions of the behaviors of the conventional and extractive fed-batch ethanol fermentations, considering the removal of ethanol and water from the broth. Use of F t of 5 h and start of ethanol stripping at 3 h of fermentation substantially reduced the inhibitory effects of the substrate and ethanol on the yeast cells. This condition enabled the extractive fed-batch ethanol fermentation to be performed using substrate concentrations of up to 240 g•L −1 in the feed, with substrate exhaustion occurring after approximately 12 h. The total ethanol concentration reached 110.3 g•L −1 (14 °GL (degrees Gay-Lussac)), around 33% higher than that obtained using conventional fed-batch fermentation without ethanol removal.

The development of rapid, accurate, and cost-effective technologies for process monitoring is highly desirable in the biofuels sector. Here, a technique based on the combination of Fourier transform mid-infrared (FT-MIR) spectroscopy and partial least-squares (PLS) regression was evaluated as a tool for real-time monitoring of the process for bioethanol production from sucrose by Saccharomyces cerevisiae. Industrial musts composed of juice and molasses of sugar cane and sweet sorghum juice were used in the fermentations. Considering the chemical complexity of the substrates, the PLS models presented excellent external validation results, with root-mean-square error of prediction (RMSEP) values of 0.54, 1.02, 0.66, 1.93, 0.50, and 1.64 g L −1 for sucrose, glucose, fructose, ethanol, glycerol, and cells, respectively. The findings demonstrated that FT-MIR spectroscopy can be applied for real-time monitoring of the process, with potential to reduce costs and provide accurate information for more efficient control of the process.

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One way of overcoming the substrate and ethanol inhibition effects in the industrial ethanol production process is to use fed-batch fermentation coupled with an ethanol removal technique. This work describes the optimization and experimental validation of sugar cane ethanol production by fed-batch fermentation with in situ ethanol removal by CO2 stripping. The optimization employing a genetic algorithm (GA) was used to find the optimum feed flow rate (F) and the ethanol concentration (C E0) in the medium at which to initiate stripping, in order to obtain maximum ethanol productivity. Conventional ethanol fermentation employing the optimum feed flow rate was performed with must containing 257.1 g L–1 of sucrose (180 g L–1 of total sucrose concentration), resulting in achievement of an ethanol concentration of 82.2 g L–1. The stripping fed-batch fermentation with high total sucrose concentration (260–300 g L–1) or 371.4–428.6 g L–1 in the must feeding was performed with optimal values of the feed flow rate and the ethanol concentration (C E0) in the medium at which to initiate stripping. At the highest sucrose feed (total concentration of 300 g L–1), the total ethanol concentration reached 136.9 g L–1 (17.2 °GL), which was about 65% higher than the value obtained in fed-batch fermentation without ethanol removal by CO2 stripping. This strategy proved to be a promising way to minimize inhibition by both the substrate and ethanol, leading to increased sugar cane ethanol production, reduced vinasse generation, and lower process costs.

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