Optimization Of Ethanol Production Research Articles

Advancements in High Gravity Fermentation Strategies for Optimizing Ethanol Production from Sugarcane-Based Substrates

Advancements in High Gravity Fermentation Strategies for Optimizing Ethanol Production from Sugarcane-Based Substrates

Ethanol production by Kluyveromyces marxianus ATCC 36907: Fermentation features and mathematical modeling

The effects of different temperatures (30 °C, 35 °C, 40 °C, and 45 °C) and initial glucose concentrations (50 g/L, 120 g/L, and 190 g/L) on the fermentative metabolism of Kluyveromyces marxianus ATCC 36907 were evaluated to optimize ethanol production. Mathematical models were developed based on experimental data to describe cell growth, substrate consumption, and ethanol production. Various kinetic models integrated with material balances were examined. The Akaike information criterion (AIC) was employed to identify the most accurate model representing the experimental behavior. Interestingly, the ethanol production rate was independent of the growth rate of K. marxianus. The growth kinetics indicated that the growth rate could be controlled by the oxygen concentration, which was influenced by cell concentration rather than glucose consumption. A desirability function was utilized to optimize ethanol productivity, substrate conversion efficiency and temperature, considering the conditions for future applications in simultaneous saccharification and fermentation (SSF) processes. The optimized experimental conditions obtained were validated, resulting in a new model specific to these conditions. This new model analysis confirmed the achievement of the objective to prioritize ethanol production. The optimized conditions for maximum ethanol production were initial glucose concentration of 91 g/L and temperature of 40 °C. Under these conditions, the ethanol concentration reached 12 g/L, with glucose conversion efficiency into ethanol of 0.13 g/g and productivity of 1.09 g/L/h after 11 h. This approach provided valuable insights into the fermentative behavior of K. marxianus, serving as a foundation for the design, optimization, and process control in biorefineries.

Ethanol production by immobilized Saccharomyces cerevisiae cells on 3D spheres designed by different lattice structure types

Natural or synthesized materials can be used for cell immobilization to enhance cell viability and productivity in fermentation processes (batch, fed-batch or continuous fermentations). 3D printing is one of the newest technologies to produce unique immobilization support materials. In this research, the selection strategy of 3D lattice structure type for unique immobilization materials, effect of different lattice structure types on cell immobilization in a shake flask experiments and optimization of ethanol production in a laboratory scale bioreactor with 3D spheres were studied. Firstly, 3D designs were compared to determine the best type of 3D spheres with a higher area:volume ratio for cell immobilization. Then shake flask experiments were performed and showed that W, 20 mm is the best 3D sphere combination for ethanol fermentation. Finally, over 37 g/L ethanol (ethanol yield ranged from 41.91% to 46.36%) was produced at all repeated batch cycles by using 100 g/L initial sugar with at least 82% sugar utilization capacity in a lab-scale bioreactor successfully. All results showed that 3D-printed materials could be used as immobilization agents for microorganisms by selecting the proper geometry, size and printing technology.

Bioethanol production from expired cookies and economic analysis for practical application

This work examined the potential of bioethanol production from expired cookies (EC) by the separate hydrolysis and fermentation process. EC was hydrolyzed by glucoamylase with different enzyme addition (3.5 U/g to 140 U/g) to produce the EC hydrolysate. The glucose concentration increased with enzyme addition from 3.5 U/g to 14 U/g and the highest glucose concentration of 21.2 g/L was obtained. The EC hydrolysate was used by Saccharomyces cerevisiae for bioethanol production. The optimal ethanol production obtained from this study was 40.1 g/L in term of economics and efficiency. According to the mass balance, the highest ethanol yield from EC was 0.4 g/g. Techno-economic analysis of the plant with capacity of 5 tons EC/day was also assessed in this study. The total capital cost and annual operation cost were US$540400.7 and US$144543.9/y, respectively. The revenue of the plant was US$390522/y with the sales of 660 t/y ethanol and 412.5 t/y oils. The plant should feed the EC more than 1.04 t/d (334.2 t/y) to avoid the shutdown point. This is the first study to demonstrate the bioethanol production from EC and assess the economic feasibility for industrial application.

Synergy of Cellulase Systems between Acetivibrio thermocellus and Thermoclostridium stercorarium in Consolidated-Bioprocessing for Cellulosic Ethanol.

Anaerobes harbor some of the most efficient biological machinery for cellulose degradation, especially thermophilic bacteria, such as Acetivibrio thermocellus and Thermoclostridium stercorarium, which play a fundamental role in transferring lignocellulose into ethanol through consolidated bioprocessing (CBP). In this study, we compared activities of two cellulase systems under varying kinds of hemicellulose and cellulose. A. thermocellus was identified to contribute specifically to cellulose hydrolysis, whereas T. stercorarium contributes to hemicellulose hydrolysis. The two systems were assayed in various combinations to assess their synergistic effects using cellulose and corn stover as the substrates. Their maximum synergy degrees on cellulose and corn stover were, respectively, 1.26 and 1.87 at the ratio of 3:2. Furthermore, co-culture of these anaerobes on the mixture of cellulose and xylan increased ethanol concentration from 21.0 to 40.4 mM with a high cellulose/xylan-to-ethanol conversion rate of up to 20.7%, while the conversion rates of T. stercorarium and A. thermocellus monocultures were 19.3% and 15.2%. The reason is that A. thermocellus had the ability to rapidly degrade cellulose while T. stercorarium co-utilized both pentose and hexose, the metabolites of cellulose degradation, to produce ethanol. The synergistic effect of cellulase systems and metabolic pathways in A. thermocellus and T. stercorarium provides a novel strategy for the design, selection, and optimization of ethanol production from cellulosic biomass through CBP.

Determinação de regiões para instalação de usinas sucroalcooleiras flex: uma abordagem multicritério para localização

Abstract The development of sugarcane varieties has allowed Brazilian ethanol plants to operate longer during the harvest, however, in the off-season they remain idle due to the absence of biomass. To increase energy safety and guarantee supply in critical periods, it has been proposed to adapt ethanol plants to the flex-biomass model, allowing the production of biofuel from corn as well. Considering the costs of building or adapting a plant, strategically defining the location is essential for optimizing ethanol production. The aim of this study is to verify whether the combination of location criteria can identify the most suitable regions for the construction of new plants and map them. The method consists of the Analytical Hierarchical Process (AHP) with GIS techniques. We found two large continuous regions suitable for the construction of new flex ethanol plants, corresponding together to 11% of the study area. However, in these two suitable regions, only 0.33% of the territory has more than 90% suitability. Therefore, we confirmed the existence of more suitable regions and concluded that the mapping of these areas enhances the resources application, avoiding installation in inappropriate areas.

Optimization of ethanol production from co-substrate of waste glycerol and acetic acid by Enterobacter aerogenes

Optimization of ethanol production from co-substrate of waste glycerol and acetic acid by Enterobacter aerogenes

Genome-Scale Metabolic Model of Caldicellulosiruptor bescii Reveals Optimal Metabolic Engineering Strategies for Bio-based Chemical Production.

ABSTRACTMetabolic modeling was used to examine potential bottlenecks that could be encountered for metabolic engineering of the cellulolytic extreme thermophile Caldicellulosiruptor bescii to produce bio-based chemicals from plant biomass. The model utilizes subsystems-based genome annotation, targeted reconstruction of carbohydrate utilization pathways, and biochemical and physiological experimental validations. Specifically, carbohydrate transport and utilization pathways involving 160 genes and their corresponding functions were incorporated, representing the utilization of C5/C6 monosaccharides, disaccharides, and polysaccharides such as cellulose and xylan. To illustrate its utility, the model predicted that optimal production from biomass-based sugars of the model product, ethanol, was driven by ATP production, redox balancing, and proton translocation, mediated through the interplay of an ATP synthase, a membrane-bound hydrogenase, a bifurcating hydrogenase, and a bifurcating NAD- and NADP-dependent oxidoreductase. These mechanistic insights guided the design and optimization of new engineering strategies for product optimization, which were subsequently tested in the C. bescii model, showing a nearly 2-fold increase in ethanol yields. The C. bescii model provides a useful platform for investigating the potential redox controls that mediate the carbon and energy flows in metabolism and sets the stage for future design of engineering strategies aiming at optimizing the production of ethanol and other bio-based chemicals.IMPORTANCE The extremely thermophilic cellulolytic bacterium, Caldicellulosiruptor bescii, degrades plant biomass at high temperatures without any pretreatments and can serve as a strategic platform for industrial applications. The metabolic engineering of C. bescii, however, faces potential bottlenecks in bio-based chemical productions. By simulating the optimal ethanol production, a complex interplay between redox balancing and the carbon and energy flow was revealed using a C. bescii genome-scale metabolic model. New engineering strategies were designed based on an improved mechanistic understanding of the C. bescii metabolism, and the new designs were modeled under different genetic backgrounds to identify optimal strategies. The C. bescii model provided useful insights into the metabolic controls of this organism thereby opening up prospects for optimizing production of a wide range of bio-based chemicals.

Bioethanol Production from an Underutilized Plant, Calabash (Crescentia Cujete) Using Co-Culture of Saccharomyces Cerevisiae and Cronobacter Malonaticus

Response surface methodology (RSM) model was used to optimize ethanol production from calabash (Crescentia cujete) pulp juice using co-culture of Saccharomyces cerevisiae and Cronobacter malonaticus. The calabash pulp was squeezed with muslin cloth, and vacuum filtered to clear solution before use. The clear juice was tested for reducing sugars using the Dinitrosalicylic acid (DNS) method. Twenty three runs (23), including 3 controls, of the fermentation were conducted at varying temperatures, pH, and volumes of inoculum. The process parameters (input variables): volumes of inoculum, temperature, and pH were subjected to response surface model, using the Central composite design (CCD). Fermentation was done in conical flasks covered with cotton wool and foil in a stationary incubator for four days (96 hours). Active co-culture of Saccharomyces cerevisiae and Cronobacter malonaticus was used, with inoculum developed using Marcfaland’s method. Samples were collected every 24 hours, centrifuged, filtered and analyzed for measurement of the output variables: reducing sugar, cell density and ethanol concentration. The concentration of reducing sugars from Calabash pulp was 3.2 mg/ml. Results obtained also revealed that the fermentation can take place on a wide range of temperature; 29-31.60C . The optimal pH range for performance of the co-culture for the fermentation process was pH range 7.9- 8.0. The optimum volume of inoculum was 5.5%v/v (ie 5.5 ml in 94.5ml juice). The optimized process using the RSM model gave 6.97% v/v bioethanol at 29oC and pH 7.9. The bioethanol yield from Calabash substrate is reasonable with co-culture considering the concentration of reducing sugars obtained from the juice and the duration of the fermentation.

Optimization of Ethanol Production from Watermelon by Enzyme Treatment

Optimization of Ethanol Production from Watermelon by Enzyme Treatment

Response surface methodology and optimization of the processes for bioethanol production from Calabash (Crescentia cujete) Using Cronobacter malonaticus

Aim: Response surface methodology (RSM) model was applied to optimize ethanol production from Calabash (Crescentia cujete) pulp juice using Cronobacter malonaticus. Study Design: The Calabash pulp was squeezed with muslin cloth, and vacuum filtered to clear solution before use. The clear juice was tested for reducing sugars using the Dinitrosalicylic acid (DNS) method. Twenty three (23) runs, including 3 controls, of the fermentation was conducted at varying temperatures, pH, and volumes of inoculum. The process parameters (input variables): volumes of inoculum, temperature, and pH were subjected to response surface model, using the Central Composite Design (CCD). Place and Duration of Study: This study was carried out in the Environmental Microbiology Laboratory, University of Port Harcourt for six months. Methodology: Fermentation was done in conical flasks covered with cotton wool and foil in a stationary incubator for four days (96 hours). Active stock culture of Cronobacter malonaticus was used, with inoculum developed using Marcfaland’s method. Samples were collected every 24 hours, centrifuged, filtered and analyzed for measurement of the output variables: Reducing sugar, cell density and ethanol concentration. Results: The concentration of reducing sugars from Calabash pulp was 3.2 mg/ml. Results obtained also revealed that the fermentation can take place on a wide range of temperature 28-32°C. The optimal pH range for performance of C.malonaticus for the fermentation process was pH 5.95-6.5. The optimum volume of inoculum was 10%v/v (i.e. 10 ml in 90 ml juice). The optimized process using the RSM model gave 5.08% v/v bioethanol, being the highest achieved at pH6.08 and 28oC . Conclusion: The bioethanol yield from Calabash substrate is reasonable considering that the bacterium used is not known for ethanol production. Also the concentration of reducing sugars in the substrate and the duration of fermentation could be responsible for the yield.

Optimization of ethanol production using newly isolated ethanologenic yeasts

Yeasts are important microorganisms used for ethanol production; however, they are not equally efficient in the amount of ethanol production under different environmental conditions. It is, therefore, necessary to screen for elite strains to utilize them for commercial production of these commodities. In this study, yeasts were isolated from different Ethiopian traditional fermented alcoholic beverages (teji, tella, shamiata and areqe tinisis), milk and ergo, teff and maize dough, soil and compost, flowers, and fruits to evaluate their potential use for ethanol fermentation process. Isolates were screened for efficient ethanol production and the selected ones were identified using phenotypic and genetic characters using D1/D2 region of LSU rDNA sequence analysis. The yeast isolates were evaluated based on their growth and fermentation of different carbon sources. Response surface methodology (RSM) was applied to optimize temperature, pH and incubation time using central composite design (CCD) in Design-Expert 7.0.0. A total of 211 yeasts colonies were isolated of which 60% were ethanologenic yeasts (ethanol producers) and 40% were non-ethanol producers. The yeast population detected from various sources was in the range of 105CFU from traditional foods and beverages to that of 103CFU from fruits and soil samples. The data also showed that the number of colony types (diversity) did not correlate with population density. The highly fermentative isolates were taxonomically characterized into four genera, of which 65% of the isolates (ETP37, ETP50; ETP53, ETP89, ETP94) were categorized under Saccharomyces cerevisiae, and the remaining were Pichia fermentans ETP22, Kluyveromyces marxianus ETP87, and Candida humilis ETP122. The S. cerevisiae isolates produced ethanol (7.6-9.0 g/L) similar with K. marxianus ETP87 producing 7.97 g/L; comparable to the ethanol produced from commercial baker's yeast (8.43 g/L) from 20 g/L dextrose; whereas C. humilis ETP122 and P. fermentans ETP22 produced 5.37 g/L and 6.43 g/L ethanol, respectively. S. cerevisiae ETP53, K. marxianus ETP87, P. fermentans ETP22 and C. humilis ETP122 tolerated 10% extraneous ethanol but the percentage of ethanol tolerance considerably decreased upon 15%. S. cerevisiae ETP53 produced ethanol optimally at pH 5.0, 60 h, and 34oC. pH 4.8, temperature 36oC, and 65 h of time were optimal growth conditions of ethanol fermentation by K. marxianus ETP87. The ethanol fermentation conditions of P. fermentans ETP22 was similar to S. cerevisiae ETP53 though the ethanol titer of S. cerevisiae ETP53 was higher than P. fermentans ETP22. Therefore, S. cerevisiae ETP53, K. marxianus and P. fermentans ETP22 are good candidates for ethanol production.

Statistical optimization of bioethanol production from waste bread hydrolysate

A recent trend in sustainable bioethanol production is the use of agricultural waste or food waste as an inexpensive and the most available feedstock. Bread waste is the major food waste that could be successfully used for the production of bioethanol. The aim of this study was to optimize ethanol production by the response surface methodology (RSM) using waste bread hydrolysate. Waste bread hydrolysate was obtained using crude hydrolytic enzymes that produce bacterial isolate Hymenobacter sp. CKS3. The influence of time of fermentation (24?72 h) and waste brewer?s yeast inoculum (1?4 %) on ethanol production was studied. The optimal conditions, obtained by central composite design (CCD), were 48.6 h of fermentation and 2.85 % of inoculum. Under these conditions, a maximum of 2.06 % of ethanol concentration was reached. The obtained ethanol concentration was in good correlation, coefficient of 0.858, with yeast cell yield. The results obtained in this study imply that waste bread hydrolysate could be used as a biomass source for biofuel production with multiple benefits relating to environmental protection, reduction of production costs, and saving fossil fuels.

Evaluación de levaduras en la producción de etanol a partir de melaza de caña de azúcar

El objetivo de la investigación consistió en evaluar el efecto de la adición de tres tipos de levaduras comerciales Saccharomyces cerevisiae, Saccharomyces exiguus y Candida utilis, utilizando disolución de melaza, las etapas del experimento consistieron en la activación de levadura y fermentación para la producción de etanol mediante una destilación simple; determinando la producción de etanol más óptima del experimento, con diferentes concentraciones de sacarosa (19°Bx, 23°Bx y 27°Bx) y diferentes condiciones ambientales (27°C, 30°C y 33°C). Se aplicó un modelo estadístico de diseño cuadrado latino utilizando el programa Microsoft Excel, tomando como factor de interés tipos de levaduras y factores secundarios los sólidos solubles (°Bx) y temperaturas de almacenamiento (°C). Se formularon nueve tratamientos (T), de los cuales se observaron diferencias significativas (p<0,05) entre los sólidos solubles (°Bx) y (p>0,05) para los tipos de levaduras estudiadas y las temperaturas de almacenamiento. Durante la producción de etanol a partir de la disolución de melaza de caña, el mejor tratamiento fue el T8, utilizando levadura Saccharomyces cerevisiae a 27°Bx y con temperatura de 30°C.

Hybrid neural network modeling and particle swarm optimization for improved ethanol production from cashew apple juice.

A hybrid neural model (HNM) and particle swarm optimization (PSO) was used to optimize ethanol production by a flocculating yeast, grown on cashew apple juice. HNM was obtained by combining artificial neural network (ANN), which predicted reaction specific rates, to mass balance equations for substrate (S), product and biomass (X) concentration, being an alternative method for predicting the behavior of complex systems. ANNs training was conducted using an experimental set of data of X and S, temperature and stirring speed. The HNM was statistically validated against a new dataset, being capable of representing the system behavior. The model was optimized based on a multiobjective function relating efficiency and productivity by applying the PSO. Optimal estimated conditions were: S0 = 127gL-1, X0 = 5.8gL-1, 35°C and 111rpm. In this condition, an efficiency of 91.5% with a productivity of 8.0gL-1h-1 was obtained at approximately 7h of fermentation.

Optimization and scale-up of ethanol production by a flocculent yeast using cashew apple juice as feedstock

Biofuels have been gaining more space in the global energy sector, with special attention to ethanol, which has shown growing demand. Ethanol is a potential and promising alternative fuel due to the use of abundant renewable sources and its combustion characteristics. From this scenario, this research aimed to optimize ethanol production by a flocculant Saccharomyces cerevisiae CCA008 using cashew apple juice (CAJ) as feedstock. The alcoholic fermentation of CAJ was influenced for all evaluated variables (inoculum and substrate concentration, temperature, and agitation) and statistical models were successfully applied to describe the interaction between these variables and to optimize the operating conditions. The optimum conditions were initial substrate concentration (S0) of 102 g L−1, inoculum concentration (X0) of 5 g L−1, temperature (T) and agitation (Agit) settings at 34 °C and 140 rpm, respectively. Last, but not least, the scale-up of ethanol production was carried out using the predicted optimum operating conditions, the fluid dynamics characteristics and applying the best scale-up criterion (power per unit of volume). The efficiencies of the processes (on bench and pilot-scale) were not significantly different and high efficiencies (96.6–98.2%) were achieved, demonstrating satisfactory results. Moreover, maximum ethanol concentration (Pmax), YP/S and productivity (QP) did not vary significatively when the process was scaled-up. On the pilot-scale, Pmax, YP/S and QP were 49.2 ± 2.2 g L−1, 0.493 ± 0.00 g g−1 and 5.0 ± 0.2 g L−1 h−1, respectively. Therefore, ethanol could be efficiently produced by the fermentation of CAJ using the flocculent yeast S. cerevisiae CCA008 and the process could be easily scaled up.

The Optimization of Ethanol Production from Oil Palm Empty Fruit Bunches Hydrolysate by Using a Statistical Experimental Design

Ethanol is a gasoline substituting fuel which its market has continued to grow rapidly in recent years. Generally, ethanol isproduced from a variety of raw materials and biomass is one modern source of renewable energy that obtains as a byproduct from the agriculture and forestry industries. The oil palm empty fruit bunch (OPEFB) is one of the potential lignocellulosic biomassesfor ethanol production. In this study, ethanol production from OPEFB was investigated. Firstly, OPEFB was alkali-pretreatment with 15% (w/v) NaOH at 121 ̊C for 45 min and it provided of 67.2% cellulose, 22.8% hemicellulose and 7.2% lignin. The cellulose content in the alkali-pretreated OPEFB had increased 39.4% from untreated OPEFB, while the hemicellulose and lignin had decreased to 33.1% and 36.7% respectively. Secondly, alkali-pretreated OPEFB was hydrolyzed with 7% (v/v) H2SO4at 140°C for 90 min. The highest glucose yield of 92.38% was obtained representing 55.54 g/L. Lastly, the glucose resulting was fermented to ethanol by Saccharomyces cerevisiae. Lastly, a response surface methodology (RSM) with a central composite design (CCD) was applied in the experimental design to optimize the ethanol production condition. A verification experiment indicated the optimal fermentation condition was as follows: 55 g/L initial glucose, pH 6.25, 2% inoculum size at 35±2ºC for 48 h. The highest ethanol yield of 40.76%(22.4 g/L, 0.41 g/g glucose) was over 80% of the theoretical ethanol yield produced from glucose fermentation, which was 28.05 g/L (0.51 g/g glucose). The ethanol yield achieved appears quite attractive and demonstrates that OPEFB have excellent potentialresource of renewable energy. While the experimental design is useful for optimization designs with several variables and describing more complex behavior by including higher orders model components.

Chemical mutagenesis of Saccharomyces cerevisiae for enhancing bioethanol production with fermentation at very high sugar concentration

Saccharomyces cerevisiae is one of the most promising unicellular fungi on account of its vital applications in biotechnology as well as bioethanol production. Improvement of ethanol production via very high-gravity (VHG) fermentation (fermentation at high sugar levels) was successfully developed using the ethidium bromide (EtB) mutagenesis of S. cerevisiae. This study found two developed mutants of S. cerevisiae (EtB20a and EtB20b) with varied capacity for ethanol production using EtB, depending on random amplified polymorphic DNA analysis. Mutant EtB20b showed improved ethanol yield (19.5%) compared with the wild-type (18.0%), while the other mutant EtB20a exhibited retarded ethanol production (9.1%). Optimization of ethanol production by mutant EtB20b was performed under other conditions including temperature, pH, inoculum size, and incubation period. The highest production capacity of the yeasts was 20.8, 19.9, 19.5, and 19.5% at an optimum temperature of 30 °C, pH 6.0, incubation period of 72 h, and 1 mL of yeast suspension (optical density at 600 nm) with glucose utilization of 42.6, 40.7, 39.8, and 39.9%, respectively.

Adaptability and stability of saccharine sorghum cultivars.

The Brazilian bioenergy sector has been trying the use of saccharine sorghum in order to optimize ethanol production. However, there are few varieties fitted to this objective and little knowledge about their adaptability and stability. Then, the purpose of this work was to study the adaptability and stability of saccharine sorghum, taking into account the effects of the G x E interaction, to select superior genotypes and validate if the two selection methods for identification of genotypes with better phenotypic stability complement one another. Thus, the methodologies of Eberhart and Russell as well as Cruz et al. were used; and according to Eberhart and Russell, the BRS 511 genotype is preferred in ethanol production because it presents highly predictable and responsive behavior to changes in environments for all the traits evaluated in specific or broad conditions. The method also identified the genotypes CMSXS644, CMSXS647 and Sugargraze for green mass production; CMSXS629, CMSXS630, CMSXS646, CMSXS647, BRS 508, BRS509 and CV198 for tons of brix per hectare; and finally, CMSXS629, CMSXS630, CMSXS643, CMSXS646, BRS 506 and BRS 509 for total soluble solid content. The methods used in this study were not complementary to selection genotypes. Key words: Bioethanol, ethanol production, genotype and environment interaction, genetic breeding, Sorghum bicolor (L.) Moench.

Solventogenesis in Clostridium aceticum producing high concentrations of ethanol from syngas

The ethanol production capability of Clostridium aceticum was investigated and optimized, in order to evaluate the ability of that organism to produce high concentrations of fuel-ethanol. The results showed that C. aceticum can produce significant amounts of ethanol when a natural pH drop occurs in the fermentation broth as a consequence of acetic acid production in a first stage. Applying different pH-regulating strategies allowed to optimize ethanol production, which proved to be more efficient in case of natural acidification due to acetic acid, reaching up to 5.6 g/L ethanol, compared to artificial pH adjustment through the addition of hydrogen chloride. Playing with the pH value and the bioreactor operating conditions showed that, under specific conditions, C. aceticum is able to perform the reverse reaction as well and convert ethanol, produced at low pH, back to acetic acid, impeding, under those specific conditions, further accumulation of ethanol in the fermentation broth.