The role of AdhE on ethanol tolerance and production in Clostridium thermocellum.

Many anaerobic microorganisms use the bifunctional aldehyde and alcohol dehydrogenase enzyme, AdhE, to produce ethanol. One such organism is Clostridium thermocellum, which is of interest for cellulosic biofuel production. In the course of engineering this organism for improved ethanol tolerance and production, we observed that AdhE was a frequent target of mutations. Here, we characterized those mutations to understand their effects on enzymatic activity, as well ethanol tolerance and product formation in the organism. We found that there is a strong correlation between NADH-linked alcohol dehydrogenase (ADH) activity and ethanol tolerance. Mutations that decrease NADH-linked ADH activity increase ethanol tolerance; correspondingly, mutations that increase NADH-linked ADH activity decrease ethanol tolerance. We also found that the magnitude of ADH activity did not play a significant role in determining ethanol titer. Increasing ADH activity had no effect on ethanol titer. Reducing ADH activity had indeterminate effects on ethanol titer, sometimes increasing and sometimes decreasing it. Finally, this study shows that the cofactor specificity of ADH activity was found to be the primary factor affecting ethanol yield. We expect that these results will inform efforts to use AdhE enzymes in metabolic engineering approaches.

Construction of an economical xylose-utilizing Saccharomyces cerevisiae and its ethanol fermentation.

Traditional industrial Saccharomyces cerevisiae could not metabolize xylose due to the lack of a specific enzyme system for the reaction from xylose to xylulose. This study aims to metabolically remould industrial S. cerevisiae for the purpose of utilizing both glucose and xylose with high efficiency. Heterologous gene xylA from Piromyces and homologous genes related to xylose utilization were selected to construct expression cassettes and integrated into genome. The engineered strain was domesticated with industrial material under optimizing conditions subsequently to further improve xylose utilization rates. The resulting S. cerevisiae strain ABX0928-0630 exhibits a rapid growth rate and possesses near 100% xylose utilization efficiency to produce ethanol with industrial material. Pilot-scale fermentation indicated the predominant feature of ABX0928-0630 for industrial application, with ethanol yield of 0.48 g/g sugars after 48 hours and volumetric xylose consumption rate of 0.87 g/l/h during the first 24 hours. Transcriptome analysis during the modification and domestication process revealed a significant increase in the expression level of pathways associated with sugar metabolism and sugar sensing. Meanwhile, genes related to glycerol lipid metabolism exhibited a pattern of initial increase followed by a subsequent decrease, providing a valuable reference for the construction of efficient xylose-fermenting strains.

Evaluation of Antioxidant Activity of Residue from Bioethanol Production Using Seaweed Biomass.

This study explores the potential of producing bioethanol from seaweed biomass and reusing the residues as antioxidant compounds. Various types of seaweed, including red (Gelidium amansii, Gloiopeltis furcata, Pyropia tenera), brown (Saccharina japonica, Undaria pinnatifida, Ascophyllum nodosum), and green species (Ulva intestinalis, Ulva prolifera, Codium fragile), were pretreated with dilute acid and enzymes and subsequently processed to produce bioethanol with Saccharomyces cerevisiae BY4741. Ethanol production followed the utilization of sugars, resulting in the highest yields from red algae > brown algae > green algae due to their high carbohydrate content. The residual biomass was extracted with water, ethanol, or methanol to evaluate its antioxidant activity. Among the nine seaweeds, the A. nodosum bioethanol residue extract (BRE) showed the highest antioxidant activity regarding the 2,2-diphenyl-1-picrylhydrazyl (DPPH) activity, ferric reducing antioxidant power (FRAP), and reactive oxygen species (ROS) inhibition of H2O2-treated RAW 264.7 cells. These by-products can be valorized, contributing to a more sustainable and economically viable biorefinery process. This dual approach not only enhances the utilization of marine resources but also supports the development of high-value bioproducts.

Boosting Solar-Driven CO2 Conversion to Ethanol via Single-Atom Catalyst with Defected Low-Coordination Cu-N2 Motif.

Cu-based catalysts have been shown to selectively catalyze CO2 photoreduction to C2+ solar fuels. However, they still suffer from poor activity and low selectivity. Herein, we report a high-performance carbon nitride supported Cu single-atom catalyst featuring defected low-coordination Cu-N2 motif (Cu-N2-V). Lead many recently reported photocatalysts and its Cu-N3 and Cu-N4 counterparts, Cu-N2-V exhibits superior photocatalytic activity for CO2 reduction to ethanol and delivers 69.8 µmol g-1 h-1 ethanol production rate, 97.8 % electron-based ethanol selectivity, and a yield of ~10 times higher than Cu-N3 and Cu-N4. Revealed by the extensive experimental investigation combined with DFT calculations, the superior photoactivity of Cu-N2-V stems from its defected Cu-N2 configuration, in which the Cu sites are electron enriched and enhance electron delocalization. Importantly, Cu in Cu-N2-V exist in both Cu+ and Cu2+ valence states, although predominantly as Cu+. The Cu+ sites support the CO2 activation, while the co-existence of Cu+/Cu2+ sites are highly conducive for strong *CO adsorption and subsequent *CO-*CO dimerization enabling C-C coupling. Furthermore, the hollow microstructure of the catalyst also promotes light adsorption and charge separation efficiency. Collectively, these make Cu-N2-V an effective and high-performance catalyst for the solar-driven CO2 conversion to ethanol. This study also elucidates the C-C coupling reaction path via *CO-*CO to *COCOH and rate-determining step, and reveals the valence state change of partial Cu species from Cu+ to Cu2+ in Cu-N2-V during CO2 photoreduction reaction.

Coupling Benzylamine Oxidation with CO2 Photoconversion to Ethanol over a Black Phosphorus and Bismuth Tungstate S-Scheme Heterojunction.

Photoconversion of CO2 and H2 O into ethanol is an ideal strategy to achieve carbon neutrality. However, the production of ethanol with high activity and selectivity is challenging owing to the less efficient reduction half-reaction involving multi-step proton-coupled electron transfer (PCET), a slow C-C coupling process, and sluggish water oxidation half-reaction. Herein, a two-dimensional/two-dimensional (2D/2D) S-scheme heterojunction consisting of black phosphorus and Bi2 WO6 (BP/BWO) was constructed for photocatalytic CO2 reduction coupling with benzylamine (BA) oxidation. The as-prepared BP/BWO catalyst exhibits a superior photocatalytic performance toward CO2 reduction, with a yield of 61.3 µmol g-1 h-1 for ethanol (selectivity of 91 %).In situ spectroscopic studies and theoretical calculations reveal that S-scheme heterojunction can effectively promote photogenerated carrier separation via the Bi-O-P bridge to accelerate the PCET process. Meanwhile, electron-rich BP acts as the active site and plays a vital role in the process of C-C coupling. In addition, the substitution of BA oxidation for H2 O oxidation can further enhance the photocatalytic performance of CO2 reduction to C2 H5 OH. This work opens a new horizon for exploring novel heterogeneous photocatalysts in CO2 photoconversion to C2 H5 OH based on cooperative photoredox systems.

Saccharomyces cerevisiae employs complex regulation strategies to tolerate low pH stress during ethanol production.

BACKGROUND: Industrial bioethanol production may involve a low pH environment caused by inorganic acids, improving the tolerance of Saccharomyces cerevisiae to a low pH environment is of industrial importance to increase ethanol yield, control bacterial contamination, and reduce production cost. In our previous study, acid tolerance of a diploid industrial Saccharomyces cerevisiae strain KF-7 was chronically acclimatized by continuous ethanol fermentation under gradually increasing low-pH stress conditions. Two haploid strains B3 and C3 having excellent low pH tolerance were derived through the sporulation of an isolated mutant. Diploid strain BC3 was obtained by mating these two haploids. In this study, B3, C3, BC3, and the original strain KF-7 were subjected to comparison transcriptome analysis to investigate the molecular mechanism of the enhanced phenotype. RESULT: The comparison transcriptome analysis results suggested that the upregulated vitamin B1 and B6 biosynthesis contributed to the low pH tolerance. Amino acid metabolism, DNA repairment, and general stress response might also alleviate low pH stress. CONCLUSION: Saccharomyces cerevisiae seems to employ complex regulation strategies to tolerate low pH during ethanol production. The findings provide guides for the construction of low pH-tolerant industrial strains that can be used in industrial fermentation processes.

Ethanol yield improvement in Saccharomyces cerevisiae GPD2 Delta FPS1 Delta ADH2 Delta DLD3 Delta mutant and molecular mechanism exploration based on the metabolic flux and transcriptomics approaches.

BACKGROUND: Saccharomyces cerevisiae generally consumes glucose to produce ethanol accompanied by the main by-products of glycerol, acetic acid, and lactic acid. The minimization of the formation of by-products in S. cerevisiae was an effective way to improve the economic viability of the bioethanol industry. In this study, S. cerevisiae GPD2, FPS1, ADH2, and DLD3 genes were knocked out by the Clustered Regularly Interspaced Short Palindromic Repeats Cas9 (CRISPR-Cas9) approach. The mechanism of gene deletion affecting ethanol metabolism was further elucidated based on metabolic flux and transcriptomics approaches. RESULTS: The engineered S. cerevisiae with gene deletion of GPD2, FPS1, ADH2, and DLD3 was constructed by the CRISPR-Cas9 approach. The ethanol content of engineered S. cerevisiae GPD2 Delta FPS1 Delta ADH2 Delta DLD3 Delta increased by 18.58% with the decrease of glycerol, acetic acid, and lactic acid contents by 22.32, 8.87, and 16.82%, respectively. The metabolic flux analysis indicated that the carbon flux rethanol in engineered strain increased from 60.969 to 63.379. The sequencing-based RNA-Seq transcriptomics represented 472 differential expression genes (DEGs) were identified in engineered S. cerevisiae, in which 195 and 277 genes were significantly up-regulated and down-regulated, respectively. The enriched pathways of up-regulated genes were mainly involved in the energy metabolism of carbohydrates, while the down-regulated genes were mainly enriched in acid metabolic pathways. CONCLUSIONS: The yield of ethanol in engineered S. cerevisiae increased with the decrease of the by-products including glycerol, acetic acid, and lactic acid. The deletion of genes GPD2, FPS1, ADH2, and DLD3 resulted in the redirection of carbon flux.

Using fermentation waste of ethanol-producing yeast for bacterial riboflavin production and recycling of spent bacterial mass for enhancing the growth of oily plants.

AIM: This study aims to use fermentation waste of ethanol production (solid and liquid) for riboflavin and recycling of bacterial biomass as biofertilizers to enhance the growth of some oily crop plants. METHODS AND RESULTS: Out of 10 yeast isolates from fresh milk, Clavispora lusitaniae ASU 33 (MN583181) was able to ferment different concentrations of glucose (2.5%, 5%, 7.5%, 10%, 15% and 20%) into ethanol with high efficiency at 10%. Among seven non-Lactobacillus bacterial isolates recovered from cheese samples, two bacterial isolates Bacillus subtlis-SR2 (MT002768) and Novosphingobium panipatense-SR3 (MT002778) were selected for their high riboflavin production. Different media (control medium, fermentation waste medium and a mixture of the fermentation waste medium and control medium [1:1]) were used for riboflavin production. These media were inoculated by a single or mixture of B. subtlis-SR2, N. panipatense-SR3. The addition of the waste medium of ethanol production to the control medium (1:1) had a stimulatory effect on riboflavin production whether inoculated with either a single strain or a mixture of B. subtlis-SR2 and N. panipatense-SR3. A mixture of fermentation waste and control media inoculated with N. panipatense produced a high riboflavin yield in comparison with other media. Inoculation of Zea mays and Ocimum basilicum plants with either the bacterial biomass waste of riboflavin production (B. subtlis or N. panipatense) or a mixture of B. subtlis and N. panipatense) shows a stimulatory effect on the plant growth in comparison with control (uninoculated plants). CONCLUSIONS: These results demonstrate the possibility of minimizing the cost of riboflavin and biofertilizer manufacturing via interlinking ethanol and riboflavin with the biofertilizer production technology. SIGNIFICANCE AND IMPACT OF STUDY: This study outlines the methods of evaluating the strength of spent media by applying procedures developed in the vitamin production industries. Furthermore, bacterial biomass waste can act as an environmentally friendly alternative for agrochemicals.

Concentration Optimization of Localized Cu0 and Cu+ on Cu-Based Electrodes for Improving Electrochemical Generation of Ethanol from Carbon Dioxide.

Copper-based electrodes can catalyze electroreduction of CO2 to two-carbon products. However, obtaining a specific product with high efficiency depends on the oxidation state of Cu for the Cu-based materials. In this study, Cu-based electrodes were prepared on fluorinated tin oxide (FTO) using the one-step electrodeposition method. These electrodes were used as efficient electrocatalysts for CO2 reduction to ethanol. The concentration ratio of Cu0 and Cu+ on the electrodes was precisely modulated by adding monoethanolamine (MEA). The results of spectroscopic characterization showed that the concentration ratio of localized Cu+ and Cu0 (Cu+/Cu0) on the Cu-based electrodes was controlled from 1.24/1 to 1.54/1 by regulating the amount of MEA. It was found that the electrode exhibited the best electrochemical efficiency and ethanol production in the CO2 reduction reaction at the optimal concentration ratio Cu+/Cu0 of 1.42/1. The maximum faradaic efficiencies of ethanol and C2 were 48% and 77%, respectively, at the potential of -0.6 V vs. a reversible hydrogen electrode (RHE). Furthermore, the optimal concentration ratio of Cu+/Cu0 achieved the balance between Cu+ and Cu0 with the most favorable free energy for the formation of *CO intermediate. The stable existence of the *CO intermediate significantly contributed to the formation of the C-C bond for ethanol production.

Enhancing short-term ethanol-type fermentation of waste activated sludge by adding saccharomycetes and the implications for bioenergy and resource recovery.

Ethanol-type sludge fermentation has recently attracted much attention because it can enhance direct interspecies electron transfer and thus improve the anaerobic digestion of waste activated sludge (WAS). In this paper, the enhancement of short-term ethanol-type fermentation of WAS via adding Saccharomyces was investigated. The experimental results show that the maximum ethanol production of 1030.8 ± 20.6 mg/L was achieved, with the optimum fermentation conditions of a pH of 5.1, temperature of 26.0 â„ƒ and time of 8.0 hr. Although the content of volatile fatty acid (VFA) increased within 10 hr, it is one order of magnitude lower than the content of ethanol, indicating that the VFA generation did not affect the efficient production of ethanol. The analyses of changes in the microbial community during the fermentation process demonstrate that the greatest Saccharomyces activity occurred in the first 8 hr and it can play an important role in ethanol production even at a very low relative abundance. Meanwhile, most typical acid-producing bacteria were inhibited, but the hydrogenotrophic methanogens (i.e., Methanobacterium) were enriched to a certain extent. Further statistical analyses reveal that the Rhodobacter, Thermomonas, Terrimonas and Saccharomyces are responsible for ethanol production during the fermentation. However, these findings not only provide a reference for the development of enhancing ethanol-type fermentation of sludge, but also are expected to provide a new way of thinking for the efficient bioenergy and resource recovery from sludge.

Ethanol Production from Colpomenia sinuosa by an Alginate Fermentation Strain Meyerozyma guilliermondii.

With the consumption of energy and the spread of COVID-19, the demand for ethanol production is increasing in the world. The industrial ethanol fermentation microbes cannot metabolize the alginate component of macro algae, which affects the ethanol yield. In this research, the ethanol production process from macro algae by an alginate fermentation yeast Meyerozyma guilliermondii, especially the pretreatment process of Colpomenia sinuosa, was studied. At the same time, the experimental design of Box-Behnken was carried out to achieve the optimum fermentation performance. The concentration of KH2PO4 (A: 2-6 g.L-1), pH (B: 4-7), reaction time (C: 60-120 h) and temperature (D: 24-34 °C) were variable input parameters. During the ethanol production process, the algae powder was firstly mixed with water at 90 °C for 0.5 h. Later the fermentation culture medium was prepared and then it was fermented by the yeast Meyerozyma guilliermondii to produce ethanol. And the optimal fermentation parameters were as follows: fermentation temperature of 28 °C, KH2PO4 dosage of 4.7 g.L-1, initial pH of 6, and fermentation time of 99 h. The ethanol yield reached 0.268 g.g-1 (ethanol to algae), close to the predicted value of model. The generation of alginate lyase during the fermentation of algae was also examined. The highest alginate lyase activity reached 46.42 U.mL-1.

Moderate Surface Segregation Promotes Selective Ethanol Production in CO2 Hydrogenation Reaction over CoCu Catalysts.

Cobalt-copper (CoCu) catalysts have industrial potential in CO/CO2 hydrogenation reactions, and CoCu alloy has been elucidated as a major active phase during reactions. However, due to elemental surface segregation and dealloying phenomena, the actual surface morphology of CoCu alloy is still unclear. Combining theory and experiment, the dual effect of surface segregation and varied CO coverage over the CoCu(111) surface on the reactivity in CO2 hydrogenation reactions is explored. The relationship between C-O bond scission and further hydrogenation of intermediate *CH2 O was discovered to be a key step to promote ethanol production. The theoretical investigation suggests that moderate Co segregation provides a suitable surface Co ensemble with lateral interactions of co-adsorbed *CO, leading to promoted selectivity to ethanol, in agreement with theory-inspired experiments.

Engineering the thermotolerant industrial yeast Kluyveromyces marxianus for anaerobic growth.

Current large-scale, anaerobic industrial processes for ethanol production from renewable carbohydrates predominantly rely on the mesophilic yeast Saccharomyces cerevisiae. Use of thermotolerant, facultatively fermentative yeasts such as Kluyveromyces marxianus could confer significant economic benefits. However, in contrast to S. cerevisiae, these yeasts cannot grow in the absence of oxygen. Responses of K. marxianus and S. cerevisiae to different oxygen-limitation regimes were analyzed in chemostats. Genome and transcriptome analysis, physiological responses to sterol supplementation and sterol-uptake measurements identified absence of a functional sterol-uptake mechanism as a key factor underlying the oxygen requirement of K. marxianus. Heterologous expression of a squalene-tetrahymanol cyclase enabled oxygen-independent synthesis of the sterol surrogate tetrahymanol in K. marxianus. After a brief adaptation under oxygen-limited conditions, tetrahymanol-expressing K. marxianus strains grew anaerobically on glucose at temperatures of up to 45 °C. These results open up new directions in the development of thermotolerant yeast strains for anaerobic industrial applications.

Ethanol yield calculations in biorefineries.

The ethanol yield on sugar during alcoholic fermentation allows for diverse interpretation in academia and industry. There are several different ways to calculate this parameter, which is the most important one in this industrial bioprocess and the one that should be maximized, as reported by Pereira, Rodrigues, Sonego, Cruz and Badino (A new methodology to calculate the ethanol fermentation efficiency at bench and industrial scales. Ind Eng Chem Res 2018; 57: 16182-91). On the one hand, the various methods currently employed in industry provide dissimilar results, and recent evidence shows that yield has been consistently overestimated in Brazilian sugarcane biorefineries. On the other hand, in academia, researchers often lack information on all the intricate aspects involved in calculating the ethanol yield in industry. Here, we comment on these two aspects, using fuel ethanol production from sugarcane in Brazilian biorefineries as an example, and taking the work of Pereira, Rodrigues, Sonego, Cruz and Badino (A new methodology to calculate the ethanol fermentation efficiency at bench and industrial scales. Ind Eng Chem Res 2018; 57: 16182-91.) as a starting point. Our work is an attempt to demystify some common beliefs and to foster closer interaction between academic and industrial professionals from the fermentation sector. Pereira, Rodrigues, Sonego, Cruz and Badino (A new methodology to calculate the ethanol fermentation efficiency at bench and industrial scales. Ind Eng Chem Res 2018; 57: 16182-91).

Ethanol production process driving changes on industrial strains.

Ethanol production has key differences between the two largest producing countries of this biofuel, Brazil and the USA, such as feedstock source, sugar concentration and ethanol titers in industrial fermentation. Therefore, it is highly probable that these specificities have led to genome adaptation of the Saccharomyces cerevisiae strains employed in each process to tolerate different environments. In order to identify particular adaptations, in this work, we have compared the genomes of industrial yeast strains widely used to produce ethanol from sugarcane, corn and sweet sorghum, and also two laboratory strains as reference. The genes were predicted and then 4524 single-copy orthologous were selected to build the phylogenetic tree. We found that the geographic location and industrial process were shown as the main evolutionary drivers: for sugarcane fermentation, positive selection was identified for metal homeostasis and stress response genes, whereas genes involved in membrane modeling have been connected with corn fermentation. In addition, the corn specialized strain Ethanol Red showed an increased number of copies of MAL31, a gene encoding a maltose transporter. In summary, our work can help to guide new strain chassis selection for engineering strategies, to produce more robust strains for biofuel production and other industrial applications.

Improving ethanol production by studying the effect of pH using a modified metabolic model and a systemic approach.

pH is an important factor affecting the growth and production of microorganisms; especially, its effect on ethanologenic microorganisms. It can change the ionization state of metabolites via the change in the charge of their functional groups that may lead to metabolic alteration. Here, we estimated the ionization state of metabolites and balanced the charge of reactions in genome-scale metabolic models of Saccharomyces cerevisiae, Escherichia coli, and Zymomonas mobilis at pH levels 5, 6, and 7. The robustness analysis was first implemented to anticipate the effect of proton exchange flux on growth rates for the constructed metabolic models at various pH. In accordance with previous experimental reports, the models predict that Z. mobilis is more sensitive to pH rather than S. cerevisiae and the yeast is more regulated by pH rather than E. coli. Then, a systemic approach was proposed to predict the pH effect on metabolic change and to find effective reactions on ethanol production in S. cerevisiae. The correlated reactions with ethanol production at predicted optimal pH in a range of proton exchange rates determined by robustness analysis were identified using the Pearson correlation coefficient. Then, fluxes of these reactions were applied to cluster the various pHs by principal component analysis and to identify the role of these reactions on metabolic differentiation because of pH change. Finally, 12 reactions were selected for up and downregulation to improve ethanol production. Enzyme regulators of the selected reactions were identified using the BRENDA database and 11 selected regulators were screened and optimized via Plackett-Burman and two-level full factorial designs, respectively. The proposed approach has enhanced yields of ethanol from 0.18 to 0.36 mol/mol carbon. Hence, not only a comprehensive approach for understanding the effect of pH on metabolism was proposed in this study, but also it successfully introduced key manipulations for ethanol overproduction.

Improved high-temperature ethanol production from sweet sorghum juice using Zymomonas mobilis overexpressing groESL genes.

Zymomonas mobilis may encounter various types of stress during ethanol fermentation, which reduces ethanol production efficiency. This situation may be mitigated by molecular chaperones, including the chaperonin GroESL, which confers enhanced protection against various stresses. In this study, we successfully developed a Z. mobilis strain R301 that harbors groESL genes and can be used for high-temperature ethanol production from sweet sorghum juice. Sequence analyses of GroES and GroEL from Z. mobilis TISTR548 demonstrated conserved residues at specific positions within GroES and conserved glycine-glycine-methionine (GGM) repeats at the C-terminus of GroEL. The Z. mobilis wild-type and R301 strains were then evaluated for their tolerance to stresses, including high temperatures, high sugar concentrations, and high ethanol concentrations up to 40°C, 300 g/L, and 13% (v/v), respectively. Z. mobilis R301 exhibited better growth performance than the wild-type strain under all stress conditions. This is the first report on ethanol production at 40°C by recombinant Z. mobilis using sweet sorghum juice; this strain produced an ethanol concentration of 41.66 g/L, with a productivity of 0.87 g/L/h and a theoretical ethanol yield of 88.9%. Overexpression of groESL resulted in increased ethanol production, with values approximately 11% higher than those of the wild type at 40°C. Additionally, at 37°C, Z. mobilis R301 gave a higher theoretical ethanol yield (92.6%) than that shown in previous research. This work illustrates the potential for future enhancement of industrial-scale ethanol production at high temperatures utilizing Z. mobilis R301 in the bioconversion of sweet sorghum juice, a promising energy crop. KEY POINTS: • The groESL-overexpressing Z. mobilis strain was successfully constructed. • The recombinant Z. mobilis exhibited higher stress tolerance than the wild-type strain. • Overexpression of groESL genes improved ethanol production efficiency at high temperatures.

AI-based forecasting of ethanol fermentation using yeast morphological data.

Several industries require getting information of products as soon as possible during fermentation. However, the trade-off between sensing speed and data quantity presents challenges for forecasting fermentation product yields. In this study, we tried to develop AI models to forecast ethanol yields in yeast fermentation cultures, using cell morphological data. Our platform involves the quick acquisition of yeast morphological images using a nonstaining protocol, extraction of high-dimensional morphological data using image processing software, and forecasting of ethanol yields via supervised machine learning. We found that the neural network algorithm produced the best performance, which had a coefficient of determination of >0.9 even at 30 and 60 min in the future. The model was validated using test data collected using the CalMorph-PC(10) system, which enables rapid image acquisition within 10 min. AI-based forecasting of product yields based on cell morphology will facilitate the management and stable production of desired biocommodities.

Improvement of ethanol production in fed-batch fermentation using a mixture of sugarcane juice and molasse under very high-gravity conditions.

Ethanol fermentation in very high gravity (VHG) saves energy consumption for ethanol distillation. As the technology offers high ethanol yield and low waste generation and it can be operated at low cost, it could be more efficient at an industrial scale than other ethanol production methods. This work studied ethanol production using a fed-batch bioreactor with a working volume of 1.5 L. The main objective of this research was evaluate the effects of temperature, sugar concentration, and cellular concentration using a Central Composite Design (CCD). Experimental conditions were selected using the surface response technique obtained from the CCD, and the results were validated to test the reproducibility. The following operating conditions were selected: temperature of 27.0 °C, sugar concentration 300.0 g/L, and cell concentration 15.0% (v/v). Under these conditions, after 30 h of fermentation the ethanol concentration, productivity and yield were 135.0 g/L, 4.42 g/(L·h) and 90.0%, respectively. All sugar was completely consumed.

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 = 127 g L-1, X0 = 5.8 g L-1, 35 °C and 111 rpm. In this condition, an efficiency of 91.5% with a productivity of 8.0 g L-1 h-1 was obtained at approximately 7 h of fermentation.