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Using wheat B starch as raw material, optimize the one-step enzymatic hydrolysis process for preparing fermentable sugars and subsequent fermentation of alcohol by brewing yeast to improve its utilization value. Initially, the elemental composition of Wheat B starch was quantified. A composite enzymatic catalyst containing α-amylase and saccharase were then employed to generate fermentable sugars from wheat B starch through enzymatic hydrolysis efficiently. Various parameters, including composite enzyme concentration, solid-liquid ratio, enzyme temperature, enzymatic duration, and pH were thoroughly investigated to assess their effects on reducing sugar yield. An orthogonal optimization approach was conducted to determine the optimal conditions for enzymatic hydrolysis. Results showed that wheat B starch contained 85.61% starch, with approximately 2% protein and mineral content, and pentosan composition nearing 5%. Following the orthogonal optimization, the most effective parameters for enzymatic saccharification were identified: A composite enzyme dosage of 4 mL, a solid-liquid ratio of 1:25 g/mL, an enzymatic digestion temperature of 60 ℃, an enzymatic digestion duration of 10 h, and a pH of 5.0. Under these specific conditions, the yield of reducing sugar reached 94.6%. Subsequently, wheat B starch was converted into alcohol through yeast-mediated fermentation. This process led to a final alcohol concentration 12.76 g/L, accompanied by an alcohol yield of 31.90%. In conclusion, wheat B starch holded remarkable promise for large-scale bioethanol production, providing valuable insights for maximizing the utilization of this resource on a broad scale.

Abstract Background Production of cheese whey in the EU exceeded 55 million tons in 2022, resulting in lactose-rich effluents that pose significant environmental challenges. To address this issue, the present study investigated cheese-whey treatment via membrane filtration and the utilization of its components as fermentation feedstock. A simulation model was developed for an industrial-scale facility located in Italy’s Apulia region, designed to process 539 m3/day of untreated cheese-whey. The model integrated experimental data from ethanolic fermentation using a selected strain of Kluyveromyces marxianus in lactose-supplemented media, along with relevant published data. Results The simulation was divided into three different sections. The first section focused on cheese-whey pretreatment through membrane filtration, enabling the recovery of 56%w/w whey protein concentrate, process water recirculation, and lactose concentration. In the second section, the recovered lactose was directed towards fermentation and downstream anhydrous ethanol production. The third section encompassed anaerobic digestion of organic residue, sludge handling, and combined heat and power production. Moreover, three different scenarios were produced based on ethanol yield on lactose (YE/L), biomass yield on lactose, and final lactose concentration in the medium. A techno-economic assessment based on the collected data was performed as well as a sensitivity analysis focused on economic parameters, encompassing considerations on cheese-whey by assessing its economical impact as a credit for the simulated facility, dictated by a gate fee, or as a cost by considering it a raw material. The techno-economic analysis revealed different minimum ethanol selling prices across the three scenarios. The best performance was obtained in the scenario presenting a YE/L = 0.45 g/g, with a minimum selling price of 1.43 €/kg. Finally, sensitivity analysis highlighted the model’s dependence on the price or credit associated with cheese-whey handling. Conclusions This work highlighted the importance of policy implementation in this kind of study, demonstrating how a gate fee approach applied to cheese-whey procurement positively impacted the final minimum selling price for ethanol across all scenarios. Additionally, considerations should be made about the implementation of the simulated process as a plug-in addition in to existing processes dealing with dairy products or handling multiple biomasses to produce ethanol.

The demand for new products derived from agro-industrial residues has increased recently. Furthermore, vinasse, a wastewater from ethanol production, needs treatment to be reused in the sugarcane industry, reducing industrial water consumption. This study performed vinasse filtration with charcoal from industrial sugarcane residues and used filtered molasses dilution in ethanolic fermentation. There were five treatments in randomized blocks with three repetitions. The treatments included deionized water and natural vinasse as positive and negative controls, respectively, and filtered vinasse from charcoal made from bamboo, sugarcane bagasse, and straw. Hence, fermentation for ethanol production was performed. Compared with natural vinasse, filtered vinasse with all types of charcoal showed lower soluble solids, total residual reducing sugars, higher ethanol concentrations, and greater fermentative efficiency. Filtered vinasse from bagasse and straw charcoals had efficiencies of 81.14% and 77.98%, respectively, in terms of ethanol production, which are close to those of deionized water (81.49%). In a hypothetical industry, vinasse charcoal filtration and charcoal regeneration should prevent 84.12% of water consumption from environmental resources. This process is feasible because it uses a product of sugarcane residue to treat wastewater and reduce industrial water consumption and vinasse disposal. HIGHLIGHTS Charcoal from sugar mill residues can be used for vinasse filtration.; The filtered vinasse should be used in molasses dilution.; Filtered vinasse has a fermentation efficiency close to deionized water in molasses dilution.; Using bagasse and straw charcoal for vinasse filtration in industry is feasible.; Charcoal regeneration is possible, and it may increase porosity.;

Due to the electrical nature of the cell, it is possible to modulate its behavior through the application of non-lethal external electric fields to improve fermentation processes. In this work, a microbial cell system with a chamber and two electrodes inside and connected to a voltage source was used. One of the electrodes was kept isolated to create an electric field without the flow of current. Cultures with two ethanol-producing microbial strains (Saccharomyces cerevisiae and Zymomonas mobilis) were conducted in this device. The application of voltages between 0 and 18 V was evaluated to determine the impact of the generated electric field on ethanol production. To analyze the possible effect of the field on the central carbon metabolism in each strain, biochemical-based kinetic models were formulated to describe the experimental fermentation kinetics obtained.It was found that low applied voltages did not have significant effects on growth rate in either strain, but all voltages evaluated increased substrate consumption and ethanol production rate in Z. mobilis, while only 18 V affected these rates in S. cerevisiae, indicating that Z. mobilis was the most sensitive to the electric field. At the end of the fermentation, significant increases in ethanol yields of 10.7% and 19.5% were detected for S. cerevisiae and Z. mobilis, respectively. The proposed mathematical models showed that substrate transport through the membrane catalyzed by the phosphotransferase system (PTS) for Z. mobilis and hexose transport proteins mechanism and hexokinase (HK) activity for S. cerevisiae and the transformation of pyruvate to ethanol, catalyzed by the decarboxylase (PDC) and alcohol dehydrogenase (ADH) enzymes, were the reactions most affected by the application of the external field.

Kluyveromyces markus CGMCC13907 and Saccharomyces cerevisiae AS2. 119 were selected as mixed starter cultures for fermentation of whey liquid to produce whey vinegar. Plackett-Burman Design (PBD) and Box-Behnken Design (BBD) were used to optimize the ethanol fermentation process. The results showed that the optimal ethanol fermentation process was K. markus CGMCC13907 inoculum volume 4. 0×106 CFU/mL, S. cerevisiae AS2. 119 inoculum volume 4. 5×106 CFU/ mL, fermentation time 151 h, fermentation temperature 40. 0 ×, fermentation pH value 5. 6, ginger powder dosage 0. 09 g/100 mL. Under this condition, the concentration of ethanol in fermentation liquid reached 8. 70 %vol, which increased by 56. 2% compared with that before optimization. K. markus CGMCC13907 combined with S. cerevisiae AS2. 119 could effectively solve the lactose fermentation problem in the process of making vinegar from whey, and achieve a better ethanol concentration. [ABSTRACT FROM AUTHOR]

Background: Production of cheese whey in the EU exceeded 55 million tons in 2022, resulting in lactose-rich effluents that pose significant environmental challenges. To address this issue, the present study investigated cheese-whey treatment via membrane filtration and the utilization of its components as fermentation feedstock. A simulation model was developed for an industrial-scale facility located in Italy's Apulia region, designed to process 539 m 3 /day of untreated cheese-whey. The model integrated experimental data from ethanolic fermentation using a selected strain of Kluyveromyces marxianus in lactose-supplemented media, along with relevant published data., Results: The simulation was divided into three different sections. The first section focused on cheese-whey pretreatment through membrane filtration, enabling the recovery of 56% w/w whey protein concentrate, process water recirculation, and lactose concentration. In the second section, the recovered lactose was directed towards fermentation and downstream anhydrous ethanol production. The third section encompassed anaerobic digestion of organic residue, sludge handling, and combined heat and power production. Moreover, three different scenarios were produced based on ethanol yield on lactose (Y E/L ), biomass yield on lactose, and final lactose concentration in the medium. A techno-economic assessment based on the collected data was performed as well as a sensitivity analysis focused on economic parameters, encompassing considerations on cheese-whey by assessing its economical impact as a credit for the simulated facility, dictated by a gate fee, or as a cost by considering it a raw material. The techno-economic analysis revealed different minimum ethanol selling prices across the three scenarios. The best performance was obtained in the scenario presenting a Y E/L  = 0.45 g/g, with a minimum selling price of 1.43 €/kg. Finally, sensitivity analysis highlighted the model's dependence on the price or credit associated with cheese-whey handling., Conclusions: This work highlighted the importance of policy implementation in this kind of study, demonstrating how a gate fee approach applied to cheese-whey procurement positively impacted the final minimum selling price for ethanol across all scenarios. Additionally, considerations should be made about the implementation of the simulated process as a plug-in addition in to existing processes dealing with dairy products or handling multiple biomasses to produce ethanol., (© 2024. The Author(s).)

Global energy demand is experiencing a notable surge due to growing energy security. Renewable energy sources, like ethanol, are becoming more viable. In the present study, the application of a PSO-PID (Particle Swarm Optimization - Proportional Integral Derivative) controller with a split-range control strategy was suggested for the regulation of temperature within the fermentation system. To optimize performance, a POS-PID controller with a split-range arrangement utilizing two control valves for hot and cold utilities was constructed. The study began by examining the open-loop dynamic response of the system to inlet temperature and concentration disturbances during ethanol production fermentation. Subsequently, a transfer function model was developed through linearization at the steady-state operating point. The split-range controller structure, implemented by optimizing the PSO-PID controller parameters using PSO, effectively demonstrated temperature control in simulations of a nonlinear model. In this investigation, the ethanol fermentation system was modeled as a CSTR using a modified Monod equation for microbial growth kinetics. Various dynamic behavioral disturbances were explored and verified in the model with plant data in this study. The simulation model results were validated through plant data. The proposed method showed superior closed-loop performance with respect to errors, with the actuators proving to be effective than other reported methods for temperature control.

The demand for new products derived from agro-industrial residues has increased recently. Furthermore, vinasse, a wastewater from ethanol production, needs treatment to be reused in the sugarcane industry, reducing industrial water consumption. This study performed vinasse filtration with charcoal from industrial sugarcane residues and used filtered molasses dilution in ethanolic fermentation. There were five treatments in randomized blocks with three repetitions. The treatments included deionized water and natural vinasse as positive and negative controls, respectively, and filtered vinasse from charcoal made from bamboo, sugarcane bagasse, and straw. Hence, fermentation for ethanol production was performed. Compared with natural vinasse, filtered vinasse with all types of charcoal showed lower soluble solids, total residual reducing sugars, higher ethanol concentrations, and greater fermentative efficiency. Filtered vinasse from bagasse and straw charcoals had efficiencies of 81.14% and 77.98%, respectively, in terms of ethanol production, which are close to those of deionized water (81.49%). In a hypothetical industry, vinasse charcoal filtration and charcoal regeneration should prevent 84.12% of water consumption from environmental resources. This process is feasible because it uses a product of sugarcane residue to treat wastewater and reduce industrial water consumption and vinasse disposal., Competing Interests: The authors declare there is no conflict., (© 2024 The Authors This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/).)

This study presents a novel data-driven modeling approach employing machine learning to develop predictive “soft sensors” for real-time monitoring of ethanol and substrate levels during bioethanol fermentation processes. By utilizing readily measurable parameters such as pH, redox potential, capacitance, and temperature, the model enables continuous prediction of less frequently measured variables including ethanol, substrate, and cell concentrations. Eleven fermentations were conducted, focusing on intensified ethanol production from sugarcane substrate, utilizing cell cycling techniques to augment output. Despite the importance of fermentation data, its acquisition is often constrained by limitations in availability and resources. To address these challenges, this research integrates synthetic time series data generation, thereby enhancing the applicability of machine learning. Through the use of a variational autoencoder (VAE), synthetic time series data was successfully generated, facilitating training and testing of a deep neural network on both original and synthetic datasets. Results demonstrate a significant 30% increase in prediction robustness with the incorporation of generated data, while maintaining comparable accuracy levels. The augmented data effectively enhances the generalization ability of trained models, mitigating overfitting and expanding decision boundaries, thereby overcoming challenges associated with small datasets and inevitable data deviations. This innovative approach offers a promising avenue for enhancing the reliability and scalability of bioethanol fermentation monitoring through AI-based biosensors.

The need for ethanol which is increasing at all times demands development related to ethanol production, especially those produced through the fermentation process both development in terms of raw materials and processes. Ethanol fermentation process continues to have problems one of them is wash out or the carrying of microorganisms into the product stream which causes the number of microorganisms to continue to decrease in the fermenter. One way to solve the problem of wash out is to tether the microorganism first to the anchoring medium (immobilized cell) and choose the suitable type of fermenter. The purpose of this study was to determine the effect of glucose concentration and the best conditions on the ethanol fermentation process continue with immobilized cell fixed bed fermenter to the value of ethanol concentration and yield ethanol produced as well as the percent of microorganisms still carried into the product streams. Based on the results of the study, the best conditions were obtained with a residence time of 2 days with the ethanol concentration of 1.20%v/v, the yield of fermented ethanol was 37.75%w/w, and % number of cells released was 0.45% at a glucose feed concentration of 150g/L. Fermentation is carried out under conditions of immobilized cell using microorganisms from the type of yeast Saccharomyces cerevisiae. In this study the variables that were considered fixed were the expansion ½ height of 1.47m column height, temperature of 25-30°C, and a pH of 5.5.

In this article, the problem of real‐time estimation of the fermentative ethanol process is tackled. The considered observer is a model‐based technique that is robust regarding the model parameter uncertainties and inline noisy measurements. An unstructured kinetic model was used to describe the production of ethanol in a batch bioreactor for Saccharomyces cerevisiae. The biomass concentration was selected as the measured bioreactor´s output via an inline device, where the estimate variables were the substrate and ethanol concentrations. An experimental prototype was constructed to demonstrate the observer's real‐time performance. The experimental results show that the robust, smooth sliding mode observer performs better than the standard proportional sliding mode observer. [ABSTRACT FROM AUTHOR]

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., (© The Author(s) 2024. Published by Oxford University Press on behalf of FEMS.)

With the breakthrough of cellulose pretreatment and enzyme hydrolysis technology, fermentation has become one of the main limiting factors for process enhancement. Current fermentation techniques are still dominated by the old-fashioned batch mode production with the lag and stationary phase demanding considerable operational time. This handicaps production efficiency and economic viability. In addition, a downtime between two batches is requested for harvesting, cleaning and sterilization, which reduces the overall productivity and increases human labor. Continuous culturing in chemostat, on the other hand, can enhance production and reduce labor (e.g. eliminating downtime intervals, and prior-fermentation steps like shake-flask culture, inoculation and subculture). However, ethanol content might be diluted, making downstream distillation and purification difficult and costly. This study endeavors to explore possible unsteady-state operation/control strategies to improve process performance. Starting from a simplified model of ethanol fermentation, stability analysis of the semi-continuous fermentation process is performed and the instability conditions of the system under ethanol inhibition is conducted. Based on the optimal periodic control (OPC) theory, the optimal criteria for switch production by periodic operations are explored, and the benefit of periodic dilution rate in the chemostat model in terms of averaged conversion rate is discussed. The results show that for the classical chemostat model with a Monod growth function, the performance of the averaged conversion rate can be improved under certain conditions, thus providing theoretical support for the study of self-cyclic fermentation. [ABSTRACT FROM AUTHOR]

Copyright of Food & Fermentation Industries is the property of Food & Fermentation Industries and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Traditional batch ethanol fermentation poses the problems of poor production and economic viability because the lag and stationary phase always demand considerable fermentation time; plus, downtime between batches is requested to harvest, clean, and sterilize, decreasing the overall productivity and increasing labor cost. To promote productivity and prolong the production period, avoid process instability, and assure a substantial production of ethanol and a minimal quantity of residual substrate, this paper proposed a nonlinear adaptive control which can realize global stabilizing control of the process starting from batch mode to achieve batch/washout avoidance. Due to the dynamic nature and complexity of the process, novel estimation and control schemes are designed and tested on an ethanol fermentation model. These schemes are global stabilizing control laws including adaptive control to avoid input saturation, nonlinear estimation of the unknown influential concentration through a higher-order sliding mode observer, and state observers and parameter estimators used to estimate the unknown states and kinetics. Since the temperature is an important factor for an efficient operation of the process, a split ranging control framework is also developed. To verify the process performance improvement by continuous fermentation, tests performed via numerical simulations under realistic conditions are presented. [ABSTRACT FROM AUTHOR]

Copyright of Science & Technology of Food Industry is the property of Science & Technology of Food Industry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Background The use of ionic liquids (ILs) to fractionate lignocelluloses for various bio-based chemicals productions is in the ascendant. On this basis, the protic ILs consisting of triethylammonium hydrogen sulfate ([TEA][HSO4]) possessed great promise due to the low price, low pollution, and high efficiency. In this study, the microwave-assistant [TEA][HSO4] fractionation process was established for corn stover fractionation, so as to facilitate the monomeric sugars production and supported the downstream acetone–butanol–ethanol (ABE) fermentation. Results The assistance of microwave irradiation could obviously shorten the fractionation period of corn stover. Under the optimized condition (190 W for 3 min), high xylan removal (93.17 ± 0.63%) and delignification rate (72.90 ± 0.81%) were realized. The mechanisms for the promotion effect of the microwave to the protic ILs fractionation process were ascribed to the synergistic effect of the IL and microwaves to the depolymerization of lignocellulose through the ionic conduction, which can be clarified by the characterization of the pulps and the isolated lignin specimens. Downstream valorization of the fractionated pulps into ABE productions was also investigated. The [TEA][HSO4] free corn stover hydrolysate was capable of producing 12.58 g L−1 of ABE from overall 38.20 g L−1 of monomeric sugars without detoxification and additional nutrients supplementation. Conclusions The assistance of microwave irradiation could significantly promote the corn stover fractionation by [TEA][HSO4]. Mass balance indicated that 8.1 g of ABE and 16.61 g of technical lignin can be generated from 100 g of raw corn stover based on the novel fractionation strategy.

BACKGROUND: Intensified ethanol fermentation produces higher ethanol concentrations while reducing water and energy requirements. Nevertheless, the inhibitory and detrimental effect of the cellular stress barriers in this process further complicates the nonlinear dynamic relationship between the variables that directly reflect the fermentation quality. These key variables are hard to measure in real time and therefore cannot be directly controlled. RESULTS: This work presents the development of a soft sensor that predicts in real time the ethanol and substrate concentrations of an intensified fermentation. The soft sensor uses feedforward neural networks (FNNs) with easily measurable process analytical technology (PAT) tools. The application of advanced PAT tools such as redox potential and capacitance, in addition to temperature and pH are explored as input variables. The complex kinetic relationship between the studied variables was captured with FNN architectures with a single hidden layer and between 95 and 175 hidden neurons for the different cases studied. Acceptable predictions are achieved for the concentration of ethanol (RMSE = 9.5 and R2 = 0.97) and substrate (RMSE = 17.02 and R2 = 0.92). CONCLUSIONS: The results confirm that the proposed soft sensor can accurately predict the ethanol and substrate concentrations. Collectively, capacitance, redox potential, temperature and pH provide a powerful platform of PAT tools that can directly infer key variables showing the fermentation quality in real time. This study provides a significant step towards the systematic development of a reliable soft sensor with integration of advanced PAT tools. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

The use of renewable feedstocks and the variability of lignocellulosic feedstocks generating fermentable sugars also offer the advantages of the most abundant, sustainable and competitive non-food biomass. The aim of this study is to valorize the oilcake obtained from non-conventional Congolese Afzelia bella oilseeds, after extraction of the oil used in biodiesel production. The conversion of A. bella oilseeds cake into ethanol was carried out using the two methods of pretreatment (with the synthesized ionic liquid 1-butyl-3-methyl imidazolium chloride and dilute sulfuric acid), followed by hydrolysis with dilute sulfuric acid and fermentation by Saccharomyces cerevisiae. The lignocellulosic composition of the sample was 47.98% cellulose, 28.15% hemicellulose and 22.3% lignin. Pretreatment with 1-butyl-3-methyl-imidazolium chloride (ionic liquid) showed an increase in cellulose content of around 4.25% and hemicellulose content of around 7.7%, with simultaneous delignification of 12.25%. In contrast, with dilute sulfuric acid, the lignin and cellulose content of the sample fell to 3.88% and 1.88% respectively. Hemicellulose content, on the other hand, increased by only 3.58%. After dilute acid hydrolysis (5% H2SO4), the values for total reducing sugar, glucose and xylose were 66.06±1.34 mg.g-1; 36.25 ± 1.2 mg.g-1 and 29.71 ± 0.6 mg.g-1 respectively. The percentage conversion of sugars was 55.16 ± 0.5% for cellulose to glucose and 53.76 ± 0.75% for hemicellulose to xylose. The hydrolyzed product of the complex polysaccharide was then converted to ethanol using commercial yeast. Results showed an ethanol yield of around 10.3%, and Fourier Transform Infrared (FTIR) spectroscopy results confirmed bioethanol production. A. bella oilseeds cakes are therefore a potential source for ethanol production.

Background Cayratia trifolia has been extensively studied for its bioactive components and medicinal properties. This study was carried out to evaluate the fermentation ability of Saccharomyces cerevisiae 2.1 yeast to determine suitable fermentation conditions. Methods The initial sugar content for three-leaf cayratia fermentation and fermentation efficiency were calculated. The temperature for three-leaf cayratia fermentation, incubation time, and preliminary 1 liter of three-leaf cayratia wine fermentation were determined. All treatments showed that the total sugar content decreased after 9 days of fermentation compared to the initial level. Temperature during fermentation has a direct effect on yeast activity. Temperature increases the growth of yeast and speed of enzyme activity. The fermentation time changes depending on temperature, initial soluble solid contents, and yeast strains, leading to changes in the ethanol content after the end of fermentation. Results The results showed that the S. cerevisiae 2.1 was able to ferment at room temperature with an initial pH of 4.5, 24 °Brix, and a yeast density of 107 cells/mL. The appropriate fermentation conditions determined for S. cerevisiae 2.1 were 24 °Brix and incubation at room temperature (28-33°C) with a fermentation time of 11 days. Concusion In 1-L scale fermentation, three-leaf cayratia wine had 9.46% (v/v) and the fermentation efficiency was 90.34%. The wine produced had a unique color, flavor, and aroma that met the sensory evaluation of the Vietnamese national standard TCVN-3217:79.