Journal articles: 'Response Surface Methodology and Bioethanol'

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Abdul Ghani, Muhammad Ridzuan, and Oh Pei Ching. "Optimization of Ethanol Production from Mango Peels Using Response Surface Methodology." Applied Mechanics and Materials 625 (September 2014): 766–69. http://dx.doi.org/10.4028/www.scientific.net/amm.625.766.

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This study aims to optimize bioethanol production from mango peels using Response Surface Methodology (RSM). The effect of temperature (25–40oC), yeast concentration (6–14 g/ml) and fermentation time (48–96 hours) on bioethanol yield was investigated. Prior to the fermentation process, mango peels were treated with 0.25–1% (w/v) sulphuric acid. Optimum glucose yield was obtained at 0.25% (w/v) sulphuric acid. RSM using 3-factor 2-level central composite design (CCD) was employed to evaluate and optimize the synthesis parameters. Based on numerical optimization, the optimum fermentation conditions were at 38oC using 6 g/ml yeast for 48 hours, giving a yield of 7.34 g/ml bioethanol.

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Sorour, Noha, Saqer Herzallah, Nazieh Alkhalaileh, et al. "Biofuel production by Candida tropicalis from orange peels waste using response surface methodology." Potravinarstvo Slovak Journal of Food Sciences 17 (November 2, 2023): 862–85. http://dx.doi.org/10.5219/1913.

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Citrus fruits are widely consumed worldwide due to their nutritional and health benefits. However, the disposal of citrus waste poses significant environmental challenges. Orange peels (OP) are a substantial by-product of fruit processing and hold great potential as a source for bioethanol production, promoting investment in utilizing agricultural waste for biofuel purposes. OP offers a cost-effective substrate for producing value-added compounds, including bioethanol. Autoclaved-water treated OP biomass exhibited the highest release of reducing sugars (68.2%) this results supported by SEM images of that Autoclaving has definite effect on the structure of the OP particles. Among the five tested microbes, Candida tropicalis was selected as a promising bioethanol candidate due to its ethanol tolerance and ability to utilize xylose. Preliminary screening using Plackett-Burman Design (PBD) was conducted to identify six influential factors affecting the fermentation process at three levels, determining the optimum response region for bioethanol production by C. tropicalis. The significant variables were further investigated using Response Surface Methodology-Central Composite Rotatable Design (RSM-CCRD) at five levels, a novel approach in this study. The addition of cysteine and resazurin as reducing agents increased bioethanol production by 2.9 and 2.1 times, respectively, from the treated OP. Under the optimized conditions obtained from RSM-CCRD, bioethanol production reached 16.7 mg/mL per mg/ml reducing sugars. Implementing all the optimized conditions, including an initial pH of 5.75, 3% yeast extract, 2.25 g/L cysteine, 4% inoculum size, 0.6 g/L ZnSO4, 0.29 g/L MgSO4, 0.3 g/L MnSO4, and substrate treatment with active charcoal before fermentation, the bioethanol yield increased by 2.2 times after three days of fermentation using co-cultures of C. tropicalis and Kluyveromyces marxianus. The fermentation process was conducted at 30 °C and 150 rpm. Exploring OP as a low-cost renewable substrate and employing efficient microorganisms open new avenues for bioethanol production.

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Fahmi, Rahman, Ong, et al. "Production Process and Optimization of Solid Bioethanol from Empty Fruit Bunches of Palm Oil Using Response Surface Methodology." Processes 7, no. 10 (2019): 715. http://dx.doi.org/10.3390/pr7100715.

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This study aimed to observe the potential of solid bioethanol as an alternative fuel with high caloric value. The solid bioethanol was produced from liquid bioethanol, which was obtained from the synthesis of oil palm empty fruit bunches (PEFBs) through the delignification process by using organosolv pretreatment and enzymatic hydrolysis. Enzymatic hydrolysis was conducted using enzyme (60 FPUg−1 of cellulose) at a variety of temperatures (35 °C, 70 °C, and 90 °C) and reaction times (2, 6, 12, 18, and 24 h) in order to obtain a high sugar yield. The highest sugars were yielded at the temperature of 90 °C for 48 h (152.51 mg/L). Furthermore, fermentation was conducted using Saccharomyces cerevisiae. The bioethanol yield after fermentation was 62.29 mg/L. Bioethanol was extracted by distillation process to obtain solid bioethanol. The solid bioethanol was produced by using stearic acid as the additive. In order to get high-quality solid bioethanol, the calorific value was optimized using the response surface methodology (RSM) model. This model provided the factor variables of bioethanol concentration (vol %), stearic acid (g), and bioethanol (mL) with a minus result error. The highest calorific value was obtained with 7 g stearic acid and 5 mL bioethanol (43.17 MJ/kg). Burning time was tested to observe the quality of the solid bioethanol. The highest calorific value resulted in the longest burning time. The solid bioethanol has a potential as solid fuel due to the significantly higher calorific value compared to the liquid bioethanol.

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Choudhary, Akhilesh Kumar, H. Chelladurai, and C. Kannan. "Performance Analysis of Diesel Engine Using Bio Ethanol (Water Hyacinth) by Response Surface Methodology (RSM)." Applied Mechanics and Materials 737 (March 2015): 53–59. http://dx.doi.org/10.4028/www.scientific.net/amm.737.53.

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In current years, many researches have been worked to find new sources of alternative fuels. In this situation, the water hyacinth will be a new source for bioethanol. In this study, bioethanol extracted from water hyacinth is blended with diesel (5-BED, 5% bioethanol and 95% diesel v/v) and has been used to experimentally investigate the diesel engine performance and emission. The response surface methodology (RSM) technique with three engine operating variables like (i) Load, (ii) Compression ratio (CR) and (iii) Fuel Injection pressure (FIP) has been implemented to evaluate diesel engine performance using bioethanol diesel blend. The equations were obtained for Brake power (BP), Brake mean effective pressure (BMEP), Brake thermal efficiency (BTHE), and NO emission by using quadratic polynomial

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El-Gendy, Nour Sh, Hekmat R. Madian, and Salem S. Abu Amr. "Design and Optimization of a Process for Sugarcane Molasses Fermentation bySaccharomyces cerevisiaeUsing Response Surface Methodology." International Journal of Microbiology 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/815631.

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A statistical model was developed in this study to describe bioethanol production through a batch fermentation process of sugarcane molasses by locally isolatedSaccharomyces cerevisiaeY-39. Response surface methodology RSM based on central composite face centered design CCFD was employed to statistically evaluate and optimize the conditions for maximum bioethanol production and study the significance and interaction of incubation period, initial pH, incubation temperature, and molasses concentration on bioethanol yield. With the use of the developed quadratic model equation, a maximum ethanol production of 255 g/L was obtained in a batch fermentation process at optimum operating conditions of approximately 71 h, pH 5.6, 38°C, molasses concentration 18% wt.%, and 100 rpm.

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Akhabue Christopher Ehiaguina and Otoikhian Shegun Kevin. "Numerical Modelling and Optimization of Bioethanol Concentration Produced from Local Sawdust following Response Surface Methodology." Global Journal of Engineering and Technology Advances 11, no. 2 (2022): 001–12. http://dx.doi.org/10.30574/gjeta.2022.11.2.0073.

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This work studies the modelling and optimization of bioethanol production from locally sourced saw dust waste. The saw dust samples are obtained from common wood species in the Nigerian tropical rain forest. Nigeria is one of the producers of wooden products in the world. Many species of wood can be found in Nigeria’s tropical rain forest. Some of the most common wood species include; Astonia boonei (duku), Bombax bounopozense (West African bombax), Brachystegia eurycoma (Okwen), Terminalia superba (White afara). Sawdust samples were obtained from a local saw mill in Edo State, Nigeria. The samples were pre-treated, hydrolyzed, fermented and the bioethanol distilled out. Optimization of bioethanol was performed by using Central Composite design of response surface methodology. Four variables such as acid concentration, hydrolyzing time, hydrolysis temperature and fermentation time were considered as influencing factors on the yield of bioethanol. The optimization of ethanol was investigated in this study under the following conditions: acid concentration (0.5-2.5 %w/w), hydrolysis temperature (100-130 °C), hydrolysis time (10-50 minutes) and fermentation time (2-6 days). It was observed from the statistical analysis that the maximum ethanol yield of 24.85 % (g/L) was obtained at optimum acid hydrolysis of acid concentration 2.0 %w/w, Hydrolysis time 40 minutes, Hydrolysis temperature 122.50 °C, and Fermentation time 5 days.

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Akhabue, Christopher Ehiaguina, and Shegun Kevin Otoikhian. "Numerical Modelling and Optimization of Bioethanol Concentration Produced from Local Sawdust following Response Surface Methodology." Global Journal of Engineering and Technology Advances 11, no. 2 (2022): 001–12. https://doi.org/10.5281/zenodo.6961469.

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This work studies the modelling and optimization of bioethanol production from locally sourced saw dust waste. The saw dust samples are obtained from common wood species in the Nigerian tropical rain forest. Nigeria is one of the producers of wooden products in the world. Many species of wood can be found in Nigeria’s tropical rain forest. Some of the most common wood species include; Astonia boonei (duku), Bombax bounopozense (West African bombax), Brachystegia eurycoma (Okwen), Terminalia superba (White afara). Sawdust samples were obtained from a local saw mill in Edo State, Nigeria. The samples were pre-treated, hydrolyzed, fermented and the bioethanol distilled out. Optimization of bioethanol was performed by using Central Composite design of response surface methodology. Four variables such as acid concentration, hydrolyzing time, hydrolysis temperature and fermentation time were considered as influencing factors on the yield of bioethanol. The optimization of ethanol was investigated in this study under the following conditions: acid concentration (0.5-2.5 %w/w), hydrolysis temperature (100-130 °C), hydrolysis time (10-50 minutes) and fermentation time (2-6 days). It was observed from the statistical analysis that the maximum ethanol yield of 24.85 % (g/L) was obtained at optimum acid hydrolysis of acid concentration 2.0 %w/w, Hydrolysis time 40 minutes, Hydrolysis temperature 122.50 °C, and Fermentation time 5 days.

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Gebresemati, Mebrahtom, and Alula Gebregergs. "Optimization of Banana Peels Hydrolysis for the Production of Bioethanol: Response Surface Methodology." International Letters of Natural Sciences 48 (November 2015): 53–60. http://dx.doi.org/10.18052/www.scipress.com/ilns.48.53.

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Energy consumption has increased steadily over the last four decades as the population has grown and more countries have become industrialized. On the other hand waste disposal has become the major concern of developing cities. Many countries such as Ethiopia have abundant raw materials for biofuels, yet these have not been explored. This study was designed to utilize banana peels for the production of bioethanol using the yeast Saccharomyces cerevisiae. The effects of factors in hydrolysis (the effect of hydrolysis parameters) were investigated and the optimum combination factor was carried out with response surface design. The parameters were varied over 3 levels and 17 experimental runs were conducted to produce fermentable sugar. The optimum results were obtained at 1.50 % v/v acid concentration, 91.02 °C temperature and 21.66 min retention time. At this optimum condition, fermentation with and without benzyl penicillin was performed to determine its effect on bioethanol.

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Gebresemati, Mebrahtom, and Alula Gebregergs. "Optimization of Banana Peels Hydrolysis for the Production of Bioethanol: Response Surface Methodology." International Letters of Natural Sciences 48 (November 3, 2015): 53–60. http://dx.doi.org/10.56431/p-f6oa7x.

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Energy consumption has increased steadily over the last four decades as the population has grown and more countries have become industrialized. On the other hand waste disposal has become the major concern of developing cities. Many countries such as Ethiopia have abundant raw materials for biofuels, yet these have not been explored. This study was designed to utilize banana peels for the production of bioethanol using the yeast Saccharomyces cerevisiae. The effects of factors in hydrolysis (the effect of hydrolysis parameters) were investigated and the optimum combination factor was carried out with response surface design. The parameters were varied over 3 levels and 17 experimental runs were conducted to produce fermentable sugar. The optimum results were obtained at 1.50 % v/v acid concentration, 91.02 °C temperature and 21.66 min retention time. At this optimum condition, fermentation with and without benzyl penicillin was performed to determine its effect on bioethanol.

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Chyuan, Ong Hwai. "Optimization of bioethanol production from Manihot glaziovii by response surface methodology." New Biotechnology 33 (July 2016): S90. http://dx.doi.org/10.1016/j.nbt.2016.06.1031.

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Ghaderi, Mohammad, Hossein Javadikia, Leila Naderloo, Mostafa Mostafaei, and Hekmat Rabbani. "An analysis of noise pollution emitted by moving MF285 Tractor using different mixtures of biodiesel, bioethanol and diesel through artificial intelligence." Journal of Low Frequency Noise, Vibration and Active Control 38, no. 2 (2019): 270–81. http://dx.doi.org/10.1177/1461348418823572.

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In the present study, the noise pollution from different compositions of biodiesel, bioethanol, and diesel fuels in MF285 Tractor was studied in the second and third gears from two positions: driver and bystander, at 1000 and 1600 r/min, and running on 10 different fuel levels. For data analysis, the ANFIS network, neural network, and response surface methodology were applied. Comparing the means of noise pollution at different levels demonstrated that the B25E6D69 fuel, made up of 25% biodiesel and 6% bioethanol, had the lowest noise pollution. The lowest noise pollution was at 1000 r/min. Although the noise pollution emitted in the third gear was a little more than that emitted in the second gear. All the resultant models, laid by response surface methodology, neural network, and ANFIS had excellent results. Considering the statistical criteria, the best models with high correlation coefficients and low mean square errors were ANFIS, response surface methodology, and artificial neural network models, respectively.

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Chaudhary, Asma, Zawar Hussain, Ayesha Aihetasham, et al. "Pomegranate peels waste hydrolyzate optimization by Response Surface Methodology for Bioethanol production." Saudi Journal of Biological Sciences 28, no. 9 (2021): 4867–75. http://dx.doi.org/10.1016/j.sjbs.2021.06.081.

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Pereira, Lucas Matheus Soares, Thaís Moré Milan, and Delia Rita Tapia-Blácido. "Using Response Surface Methodology (RSM) to optimize 2G bioethanol production: A review." Biomass and Bioenergy 151 (August 2021): 106166. http://dx.doi.org/10.1016/j.biombioe.2021.106166.

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Ye, Yanshuai, Jingyi Hu, Zhiqing Zhang, Weihuang Zhong, Ziheng Zhao, and Jian Zhang. "Effect of Different Ratios of Gasoline-Ethanol Blend Fuels on Combustion Enhancement and Emission Reduction in Electronic Fuel Injection Engine." Polymers 15, no. 19 (2023): 3932. http://dx.doi.org/10.3390/polym15193932.

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The severity of engine emissions for the environment and human health cannot be ignored. This article optimizes the combustion and emission of gasoline-cassava bioethanol fuel blends in electronic fuel injection engines using response surface methodology to achieve the goal of reducing carbon and pollutant emissions. The experiment investigated the effects of different gasoline-cassava bioethanol mixing ratios (G100, G90E10, G80E20, and G70E30) on engine performance, including torque, brake specific fuel consumption, power, total hydrocarbons, nitrogen oxides, and carbon monoxide emissions. The results show that the gasoline-cassava bioethanol fuel blend is not as good as G100 in terms of braking power, torque, and brake specific fuel consumption, but better than G100 in terms of carbon monoxide emissions and total hydrocarbon emissions. Then, the optimization objective function was determined, and the combustion and emission characteristics were optimized using the response surface methodology method. The optimization results indicate that the response surface methodology method can determine the interaction between design variables such as brake specific fuel consumption, nitrogen oxides, and total hydrocarbon emissions and find the best solution. In this experiment, the independent variables of the best solution were 72.9 N·m torque, 30% G70E30 mixing rate, and 2000 rpm speed, corresponding to brake specific fuel consumption at 313 g/(kW·h), nitrogen oxide emissions at 2.85 × 103 ppm, and total hydrocarbon emissions at 166 ppm. The findings of this study indicate that by optimizing the gasoline-cassava bioethanol mixture ratio, lower emission levels can be achieved in electronic fuel injection engines, thereby promoting the sustainable development of renewable energy and reducing pollutant emissions.

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Cherian, Elsa, M. Dharmendira Kumar, and G. Baskar. "Production and optimization of cellulase from agricultural waste and its application in bioethanol production by simultaneous saccharification and fermentation." Management of Environmental Quality: An International Journal 27, no. 1 (2016): 22–35. http://dx.doi.org/10.1108/meq-07-2015-0128.

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Purpose – The purpose of this paper is to optimize production of cellulase enzyme from agricultural waste by using Aspergillus fumigatus JCF. The study also aims at the production of bioethanol using cellulase and yeast. Design/methodology/approach – Cellulase production was carried out using modified Mandel’s medium. The optimization of the cellulase production was carried out using Plackett-Burman and Response surface methodology. Bioethanol production was carried out using simultaneous saccharification and fermentation. Findings – Maximum cellulase production at optimized conditions was found to be 2.08 IU/ml. Cellulase was used for the saccharification of three different feed stocks, i.e. sugar cane leaves, corn cob and water hyacinth. Highest amount of reducing sugar was released was 29.1 gm/l from sugarcane leaves. Sugarcane leaves produced maximum bioethanol concentration of 9.43 g/l out of the three substrates studied for bioethanol production. Originality/value – The present study reveals that by using the agricultural wastes, cellulase production can be economically increased thereby bioethanol production.

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Rezania, Shahabaldin, Shaza Eva Mohamad, Adibah Yahya, and Madihah Md Salleh. "Bioethanol production from cocoa waste by locally isolated microorganism using response surface methodology." MOJ Biology and Medicine 3, no. 4 (2018): 160–66. http://dx.doi.org/10.15406/mojbm.2018.03.00092.

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The rate of ethanol production can be affected by different parameters that involved during fermentation. In this study, acid treated cocoa waste (CW) was used as a lignocellulosic substrate for ethanol production in the simultaneous saccharification and fermentation (SSF) using microorganism isolated from locally fermented food tapai ubi and tapai pulut. For optimization, the experiments were carried out using response surface methodology (RSM). The effect of four independent variables temperature, CW concentration, inoculum size and pH during fermentation was investigated. A central composite design (CCD) was used to evaluate the effect and interactions of the parameters. ANOVA analysis revealed that pH and inoculum size had the most significant effects on the ethanol production. The optimized condition for the ethanol production was at temperature 31.7°C, pH 6.0, inoculum size 10.5% and CW concentration 0.3g/L while after optimization, ethanol podcution increased from 6.2±0.8g/L to 9.5±1.1g/L.

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Ghazanfar, Misbah, Muhammad Irfan, Muhammad Nadeem, et al. "Bioethanol Production Optimization from KOH-Pretreated Bombax ceiba Using Saccharomyces cerevisiae through Response Surface Methodology." Fermentation 8, no. 4 (2022): 148. http://dx.doi.org/10.3390/fermentation8040148.

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The present study was based on the production of bioethanol from alkali-pretreated seed pods of Bombax ceiba. Pretreatment is necessary to properly utilize seed pods for bioethanol production via fermentation. This process assures the accessibility of cellulase to the cellulose found in seedpods by removing lignin. Untreated, KOH-pretreated, and KOH-steam-pretreated substrates were characterized for morphological, thermal, and chemical changes by scanning electron microscopy (SEM), thermogravimetric analysis (TGA), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). Hydrolysis of biomass was performed using both commercial and indigenous cellulase. Two different fermentation approaches were used, i.e., separate hydrolysis and fermentation (SHF) and simultaneous saccharification and fermentation (SSF). Findings of the study show that the maximum saccharification (58.6% after 24 h) and highest ethanol titer (57.34 g/L after 96 h) were observed in the KOH-steam-treated substrate in SSF. This SSF using the KOH-steam-treated substrate was further optimized for physical and nutritional parameters by one factor at a time (OFAT) and central composite design (CCD). The optimum fermentation parameters for maximum ethanol production (72.0 g/L) were 0.25 g/L yeast extract, 0.1 g/L K2HPO4, 0.25 g/L (NH4)2SO4, 0.09 g/L MgSO4, 8% substrate, 40 IU/g commercial cellulase, 1% Saccharomyces cerevisiae inoculum, and pH 5.

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K.Tamilarasan, A.Subramanian та Kumar M.Dharmendira. "Optimization of Enzymatic Hydrolysis of Rice Starch by Immobilized α-Amylase using Response Surface Methodology". International Journal of BioSciences and Technology (IJBST) ISSN: 0974-3987 3, № 6 (2010): 61–67. https://doi.org/10.5281/zenodo.1438337.

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ABSTRACT: Enzymatic hydrolysis of starch from natural sources finds potential application in commercial production of alcoholic beverage and bioethanol. This work deals with the modeling of the enzymatic hydrolysis of rice waste using immobilized α-amylase. Optimization strategies (starch concentration, enzyme concentration, temperature and time) were evaluated by the use of Response Surface Methodology (RSM). The experimental result on enzymatic hydrolysis of rice waste was subjected to multiple linear regression analysis using MINITAB 14 software. The most significant effect of starch concentration, temperature and time were found on hydrolysis of rice starch by immobilized α-amylase enzyme. The statistical significance of the model was validated by F-test for analysis of variance (p ≤ 0.01).The maximum glucose produced 1.16 mg/ml at starch concentration 8.17(%), enzyme concentration 1.34 (%), temperature 34°C, time 96.41 min. Key words: Enzymatic hydrolysis, response surface methodology, regression analysis, immobilization http://www.ijbst.org/Home/papers-published/ijbst-2010-volume-3-issue-6

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Shaghaghi-Moghaddam, Reza, Hoda Jafarizadeh-Malmiri, Parviz Mehdikhani, Reza Alijanianzadeh, and Sepide Jalalian. "Optimization of submerged fermentation conditions to overproduce bioethanol using two industrial and traditional Saccharomyces cerevisiae strains." Green Processing and Synthesis 8, no. 1 (2019): 157–62. http://dx.doi.org/10.1515/gps-2018-0044.

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Abstract The present study focuses on the overproduction of bioethanol through submerged fermentation. In a batch-scale submerged bioreactor using a traditional and an industrial Saccharomyces cerevisiae (NCYC 4109 and SFO6) strains, the fermentation was accomplished. The effects of the substrate brix (20.50–24.00 °Bx) and inoculum percentage in the initial fermentation solution (15%–45%) as independent variables on bioethanol production (g/l) as the dependent variable were assessed using the response surface methodology. Using the obtained experimental values for the response variable based on experiments for the fermentation parameters, a general model (second-order) with high coefficient of determination values (R2 > 95%) was generated to predict the bioethanol concentrations that were obtained using both yeast strains. The obtained results indicated that the optimum fermentation conditions to overproduce bioethanol (56.14 g/l) using the SFO6 yeast were at the substrate brix and inoculum percentage values of 24.70 °Bx and 26.35%, respectively. However, a higher concentration of bioethanol (53.1 g/l) using the NCYC 4109 yeast strain was obtained at the substrate brix and inoculum percentage values of 24.68 °Bx and 40.07%, respectively.

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Phong, H. X., N. N. Thanh, B. H. D. Long, and P. Thanonkeo. "OPTIMIZATION OF HIGH-TEMPERATURE BIOETHANOL PRODUCTION FROM PINEAPPLE PEEL HYDROLYSATE USING RESPONSE SURFACE METHODOLOGY." Rasayan Journal of Chemistry 13, no. 04 (2020): 2167–72. http://dx.doi.org/10.31788/rjc.2020.1345923.

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Hayder, Nadhim, Hussain Flayeh, and Ali Ahmed. "Optimization of Bioethanol Production from Biodegradable Municipal Solid Waste using Response Surface Methodology (RSM)." Journal of Engineering and Sustainable Development 2018, no. 01 (2018): 47–65. http://dx.doi.org/10.31272/jeasd.2018.1.5.

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Grahovac, Jovana A., Jelena M. Dodić, Siniša N. Dodić, Stevan D. Popov, Aleksandar I. Jokić, and Zoltan Z. Zavargo. "Optimization of bioethanol production from intermediates of sugar beet processing by response surface methodology." Biomass and Bioenergy 35, no. 10 (2011): 4290–96. http://dx.doi.org/10.1016/j.biombioe.2011.07.016.

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Ngozi, Ursulla Nwogwugwu, O. Abu Gideon, Akaranta Onyewuchi, et al. "Response surface methodology and optimization of the processes for bioethanol production from Calabash (Crescentia cujete) Using Cronobacter malonaticus." GSC Biological and Pharmaceutical Sciences 14, no. 2 (2021): 204–16. https://doi.org/10.5281/zenodo.4606660.

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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.

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Gimbun, Jolius, Nor Shahirah Mohd Nasir, Sumaiya Zainal Abidin, Chin Kui Cheng, and Maizirwan Mel. "Optimisation of Bioethanol Production from Oil Palm Trunk Sap." E3S Web of Conferences 422 (2023): 01004. http://dx.doi.org/10.1051/e3sconf/202342201004.

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This paper presents an optimization of bioethanol production from oil palm trunk sap (OPTS) fermentation. The OPTS was obtained from an old palm tree (30 years old), whereas ethanol fermentation was carried out using Saccharomyces cerevisiae. The sugar content in OPTS and fermentation mother liquor was determined using high-performance liquid chromatography (HPLC). The parameters such as initial pH, temperature, and agitation rate were optimised using response surface methodology (RSM) with rotatable central composite design (CCD). It was found that the highest yield of bioethanol (75.82%) was obtained at the initial pH (5.79), temperature (31.05 ºC), and agitation rate (164.38 rpm). The optimization model of OPTS fermentation to bioethanol developed in this work may provide useful guidance to obtain a high ethanol yield from OPTS.

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Ademakinwa, Adedeji Nelson, Mayowa Oladele Agunbiade, and Femi Kayode Agboola. "Trilepisium madagascariense fruit-wastes as cheap feedstock for bioethanol production." Acta Biologica Szegediensis 63, no. 1 (2019): 45–50. http://dx.doi.org/10.14232/abs.2019.1.45-50.

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Trilepisium madagascariense fruits are carbohydrate-rich and this study directly fermented the fruit wastes into bioethanol without the need for nutrient supplementation. The total reducing sugar (TRS) present in the mesocarp and seed of T. madagascariense fruit wastes (Tmfw) was fermented to bioethanol using Aureobasidium pullulans. Bioethanol production by A. pullulans was also optimized using Box-Behnken response surface methodology (RSM). The TRS in the mesocarp and seed of Tmfw were 11.2 ± 0.8 and 17.1 ± 1.2 g/L, respectively and further hydrolysis with cellulase resulted in increased TRS indicating the presence of cellulose. Pre-optimization, the bioethanol yield (Yps) and volumetric productivity (Qp) obtained from the fermentation of the seed by A. pullulans were 0.57 ± 0.03 g/g and 0.21 ± 0.02 g/L-1h-1, respectively. The optimum conditions for maximum bioethanol production were pH (5.95), time (24 h) and substrate concentration (5 g/L) resulting in Yps, Qp of 0.66 ± 0.06 g/g and 0.27 + 0.01 g/L-1h-1, respectively after model validation. Tmfw served as a suitable, cheap, non-toxic and readily available substrate especially in Nigeria to produce bioethanol while A. pullulans is a fungus that might be utilized for large-scale industrial bioethanol production.

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Osemwengie, S. O., E. I. Osagie, and B. Onwukwe. "Optimization of bioethanol production from cassava peels." Journal of Applied Sciences and Environmental Management 24, no. 12 (2021): 2077–83. http://dx.doi.org/10.4314/jasem.v24i12.11.

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The bioethanol production from waste is acquiring attraction as a strategy for increasing energy security. This study aims to optimize the production of ethanol from cassava peel using Box Bhenken experimental design. The total carbohydrate content of about 90% in cassava peel was subjected to enzymatic hydrolysis using Alpha-amylase followed by Simultaneous Saccharification and Fermentation (SSF) by Saccharomyces cerevisiae for bioethanol production. The production of bioethanol from cassava peels was investigated for 1-4 hours (hydrolysis time), 0.5–1.5mg/L (enzyme loading), and 1-5 days (incubation time). A statistical model was developed and validated to predict the yield of bioethanol after fermentation, and the Response Surface Methodology (RSM) was used to optimize the conditions. The results revealed that the maximum ethanol yield of 1.911% was obtained at the optimum hydrolysis time, enzyme loading, and incubation time (i.e. 2.5 hours, 1 mg/L, and 3 days respectively).

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Sari, Ni Ketut, Mohammad Kimpria Prabawa, Syaroh Ryadhani Alviola, Dira Ernawati, Komang Nickita Sari, and Maria Anityasari. "Production of bioethanol from coconut water through fermentation process." IOP Conference Series: Earth and Environmental Science 1454, no. 1 (2025): 012007. https://doi.org/10.1088/1755-1315/1454/1/012007.

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Abstract The substantial and increasing coconut production in Indonesia results in a corresponding rise in coconut water production. To address this surplus, coconut water can be utilized to produce bioethanol through fermentation. Bioethanol is ethanol derived from plant materials rich in carbohydrates, cellulose, or glucose. This study explores the production of bioethanol from coconut water using Alcotec 48 Turbo Yeast. The ethanol content is analyzed using an alcohol refractometer, followed by distillation to enhance ethanol concentration. The initial glucose content of coconut water post-hydrolysis is 14% (v/v). Optimal conditions for fermentation were found with 14 g/L of Alcotec 48 Turbo Yeast over a period of 6 days, yielding a bioethanol content of 37% (v/v). After distillation under the same conditions, the bioethanol content increased to 53% (v/v). Using Response Surface Methodology (RSM) in Minitab 17, further optimization revealed that fermenting with 6 g/L of Alcotec 48 Turbo Yeast for 2 days resulted in a bioethanol content of 19.7829%. Subsequent distillation at 14 g/L of yeast over 9 days maintained the bioethanol content at 53.764%. This research demonstrates the potential of utilizing coconut water for bioethanol production, highlighting effective fermentation and distillation strategies to enhance ethanol yield.

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Pandiyan, K., Rameshwar Tiwari, Surender Singh, et al. "Optimization of Enzymatic Saccharification of Alkali Pretreated Parthenium sp. Using Response Surface Methodology." Enzyme Research 2014 (May 12, 2014): 1–8. http://dx.doi.org/10.1155/2014/764898.

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Parthenium sp. is a noxious weed which threatens the environment and biodiversity due to its rapid invasion. This lignocellulosic weed was investigated for its potential in biofuel production by subjecting it to mild alkali pretreatment followed by enzymatic saccharification which resulted in significant amount of fermentable sugar yield (76.6%). Optimization of enzymatic hydrolysis variables such as temperature, pH, enzyme, and substrate loading was carried out using central composite design (CCD) in response to surface methodology (RSM) to achieve the maximum saccharification yield. Data obtained from RSM was validated using ANOVA. After the optimization process, a model was proposed with predicted value of 80.08% saccharification yield under optimum conditions which was confirmed by the experimental value of 85.80%. This illustrated a good agreement between predicted and experimental response (saccharification yield). The saccharification yield was enhanced by enzyme loading and reduced by temperature and substrate loading. This study reveals that under optimized condition, sugar yield was significantly increased which was higher than earlier reports and promises the use of Parthenium sp. biomass as a feedstock for bioethanol production.

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Kim, Ho-Yong, Chang-Young Hong, Seon-Hong Kim, Hwanmyeong Yeo, and In-Gyu Choi. "Optimization of The Organosolv Pretreatment of Yellow Poplar for Bioethanol Production by Response Surface Methodology." Journal of the Korean Wood Science and Technology 43, no. 5 (2015): 600–612. http://dx.doi.org/10.5658/wood.2015.43.5.600.

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Zouhair, Fatima Zahra, Younes En-Nahli, Mohammed Rachid Kabbour, et al. "Model study on dilute acid pretreatment of argan pulp for bioethanol production using response surface methodology." Mediterranean Journal of Chemistry 8, no. 4 (2019): 290–301. http://dx.doi.org/10.13171/mjc841906025fzz.

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The present work describes comparative dilute acid pretreatment of the argan pulp (residue produced during the argan oil extraction) used as an economical source for bioethanol production. Response surface methodology was used to optimize the pretreatment process and to explore the effect of operational parameters (acid concentration, temperature, time and biomass loading), depending on the acid type (HCl, H2SO4) and pretreatment approach, on total and reducing sugars recovery, in addition to phenolic compounds rate as inhibitors produced during pretreatment process. Experimental results predict an optimal yield of total and reducing sugars of 171.46 mg/ml and 54.83 mg/ml, respectively, were achieved at an optimized time of 30 min with 7% of sulfuric acid at 160°C using 40 % for biomass loading.

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Faramarzi, Sara, Younes Anzabi, and Hoda Jafarizadeh-Malmiri. "Selenium supplementation during fermentation with sugar beet molasses and Saccharomyces cerevisiae to increase bioethanol production." Green Processing and Synthesis 8, no. 1 (2019): 622–28. http://dx.doi.org/10.1515/gps-2019-0032.

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Abstract A bench scale submerged fermentation process was used to bioethanol produce using sugar beet molasses and Saccharomyces cerevisiae, as substrate and microbial strain, respectively. Effects of selenium amount on growth of S. cerevisiae and bioethanol production were evaluated. The obtained results indicated that growth of S. cerevisiae (manifested as turbidity intensity) in the samples containing 0, 5, 10, 15, 20 and 25 μg sodium selenite, during aerobic process, was 0.1707, 0.1678, 0.1679, 0.1664, 0.1627 and 0.160% a.u./h (after 14 h incubation), respectively. Statistical analysis based on compression test indicated that there were insignificant (p > 0.05) differences between growth rate of the yeast in the fermented samples containing S. cerevisiae and 5 to 25 μg selenium salt. Response surface methodology was utilized to evaluate effects of two fermentation parameters namely, amount of selenium (5-25 μg) and substrate brix (10-25°Bx) on the concentration (g/L) of produced bioethanol. Obtained results revealed that maximum bioethanol concentration (55 g/L) was achieved using 15 μg selenium and molasses with 25°Bx. Furthermore, results have also indicated that, without using selenium and using molasses with 25°Bx, bioethanol with concentration of 29 g/L was produced.

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Roncevic, Zorana, Bojana Bajic, Sinisa Dodic, Jovana Grahovac, Radmila Pajovic-Scepanovic, and Jelena Dodic. "Optimization of bioethanol production from soybean molasses using different strains of Saccharomyces cerevisiae." Chemical Industry 73, no. 1 (2019): 1–12. http://dx.doi.org/10.2298/hemind180713004r.

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Bioethanol technology represents an important scientific research area because of the high market value and wide availability of its primary and by-products. Worldwide interest in utilizing bioethanol as a renewable and sustainable energy source has significantly increased in the last few years due to limited reserves of fossil fuels and concerns about climate change. Therefore, improvement of the bioethanol production process is a priority research field at the international scale, due to both economic and environmental reasons. The aim of this study was to optimize production of bioethanol from soybean molasses based media using response surface methodology. Three different strains of the yeast Saccharomices cerevisiae, commercially available in dried form, were used as production microorganisms, and the best results were obtained by using dried baker?s yeast. The results of optimization of alcoholic fermentation using dried baker?s yeast indicate that the highest value of the overall desirability function (0.945) is obtained when the initial sugar content is 18.10 % (w/v) at the fermentation time of 48.00 h. At these conditions the model predicts that bioethanol concentration is 8.40 % (v/v), yeast cell number 2.21?108 cells/mL and the residual sugar content is 0.35 % (w/v).

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SINGH, NAVJOT, MONICA SACHDEVA TAGGAR, JASPREET KAUR, ANU KALIA, and TOSH GARG. "OPTIMIZATION OF BIOETHANOL PRODUCTION FROM CORN COBS BY SIMULTANEOUS SACCHARIFICATION AND FERMENTATION USING RESPONSE SURFACE METHODOLOGY." Cellulose Chemistry and Technology 57, no. 3-4 (2023): 359–68. http://dx.doi.org/10.35812/cellulosechemtechnol.2023.57.31.

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Ngozi Ursulla Nwogwugwu, Gideon O. Abu, Onyewuchi Akaranta, et al. "Response surface methodology and optimization of the processes for bioethanol production from Calabash (Crescentia cujete) Using Cronobacter malonaticus." GSC Biological and Pharmaceutical Sciences 14, no. 2 (2021): 204–16. http://dx.doi.org/10.30574/gscbps.2021.14.2.0019.

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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.

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Putri Ayu Salsabila, Della Ainurrohma, and Indah Wahyuningtyas. "The Effect of Time, Ph and Starter Concentration on Bioethanol Content in the Tobacco Stem Fermentation Process." Journal of Biobased Chemicals 4, no. 2 (2024): 155–72. https://doi.org/10.19184/jobc.v4i2.1410.

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The depletion of fossil fuels has now occurred in various parts of the world. Meanwhile, the demand for fuel energy continues to increase. This condition encourages researchers to look for alternative fuels with high availability of raw materials. Bioethanol is an environmentally friendly renewable energy with biomass production raw materials, it can be an alternative solution to replace fuel oil. One of the biomass that has the potential to be used as a raw material for bioethanol production is tobacco. Tobacco stems have high cellulose and hemicellulose content so that they can be used in bioethanol production. This research method uses base pretreatment and base hydrolyzate, then fermentation and distillation processes are carried out. The results of tobacco stem bioethanol were analyzed using the Response Surface Methodology (RSM) approach, Central Composite Design (CCD) model. During the fermentation process, three independent variables were used, namely the fermentation time of 72-168 hours, pH 4-5, and starter concentration of 0.1% - 0.3%. The results of the Analysis of Variance (ANOVA) of ethanol content showed that the significant variables were the fermentation time and starter concentration. The results of the CCD analysis were obtained at optimum time conditions of 120 hours, pH 4.5 and starter concentration of 0.2% with a bioethanol content of 23.007%.

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Ismail, Abbas, Masniroszaime Md Zain, Siti Rozaimah Sheikh Abdullah, and Noorhisham Tan Kofli. "Pengoptimuman Pengeluaran Bioetanol Menggunakan Strain Yis Tempatan yang Diasingkan dari Malaysia Melalui Sel Yis Terkurung dalam Bebola Alginat." Jurnal Kejuruteraan 36, no. 6 (2024): 2415–24. http://dx.doi.org/10.17576/jkukm-2024-36(6)-15.

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Research in production of bioethanol has been accelerating since the world faced depleting fossil fuels. To obtain high ethanol yield and fermentation rate, response surface methodology (RSM) was applied to study the effect of medium and alginate-ST1 yeast cell beads toward production of bioethanol using local yeast strain called ST1. Bioethanol was produced by immobilized ST1 yeast grown in local brown sugar (LBS) using shake flask mode at 30˚C for 6 hour and the effect of LBS concentrations, ratio of alginate (ST1) beads to the medium volumes and the beads size were investigated. Firstly, 23 full factorial design (first order model) was carried out to identify the significant effect prior to second-order model; central composite design (CCD) can be proposed. The first order model analysis showed that the selected parameters are significant in glucose utilization and bioethanol production. The total bioethanol production was 5.30 g/L under optimum conditions, an increase of 14.16% compared to the production before optimization, which was 4.73 g/L. The CCD results showed that the optimum conditions for bioethanol production were at a ratio of 125 g/L LBS for LBS concentration, 0.47 for the ratio of alginate beads to medium volume, and 0.33 cm for alginate bead size. Overall, this study demonstrated the successful immobilization of ST1 yeasts in alginate, which improved the effectiveness and productivity of bioethanol production. This approach offers a more sustainable solution, as the yeast cells can be reused, thereby shortening the harvesting process and contributing to a more efficient bioethanol production system.

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Coşgun, Ahmet, M. Erdem Günay, and Ramazan Yıldırım. "A critical review of machine learning for lignocellulosic ethanol production via fermentation route." Biofuel Research Journal 10, no. 2 (2023): 1859–75. http://dx.doi.org/10.18331/brj2023.10.2.5.

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In this work, machine learning (ML) applications in lignocellulosic bioethanol production were reviewed. First, the pretreatment-hydrolysis-fermentation route, the most commonly studied alternative, was summarized. Next, a bibliometric analysis was performed to identify the current trends in the field; it was found that ML applications in the field are not only increasing but also expanding their relative share in publications, with bioethanol seeming to be the most frequently researched topic while biochar and biogas are also receiving increased attention in recent years. Then, the implementation of ML for lignocellulosic bioethanol production via this route was reviewed in depth. It was observed that artificial neural network (ANN) is the most commonly used algorithm (appeared in almost 90% of articles), followed by response surface methodology (RSM) (in about 25% of articles) and random forest (RF) (in about 10% of articles). Bioethanol concentration is the most common output variable in the fermentation step, while fermentable sugar and glucose concentration are studied most in hydrolysis. The datasets are usually small, while the fitnesses of the models (R2) are usually high in the papers reviewed. Finally, a perspective for future studies, mostly considering improving data availability, was provided.

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Yunita, Ria Dwi, Hardoko Insan Qudus, and Sutopo Hadi. "Optimization of Acid Hydrolysis of Cassava Rhizome into Fermentable Sugars for Bioethanol Production Using Response Surface Methodology." Oriental Journal of Chemistry 33, no. 5 (2017): 2507–17. http://dx.doi.org/10.13005/ojc/330545.

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Choudhary, Akhilesh Kumar, H. Chelladurai, and C. Kannan. "Optimization of Combustion Performance of Bioethanol (Water Hyacinth) Diesel Blends on Diesel Engine Using Response Surface Methodology." Arabian Journal for Science and Engineering 40, no. 12 (2015): 3675–95. http://dx.doi.org/10.1007/s13369-015-1810-y.

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Alvita, Livia Rhea, Vida Elsyana, and Ekajayanti Kining. "Optimization of the Hydrolysis Process of Microalgae Porphyridium cruentum Biomass with Variations of Hydrochloric Acid Concentration, Temperature, and Time using Response Surface Methodology (RSM)." ALCHEMY:Journal of Chemistry 11, no. 2 (2023): 51–56. http://dx.doi.org/10.18860/al.v11i2.19500.

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Microalgae Porphyridium cruentum has potential as a raw material for bioethanol production because it has a high carbohydrate content. These carbohydrates can be broken down into reducing sugars through the hydrolysis process. The reducing sugar obtained will be used as a substrate in the production of bioethanol. This study aimed to produce a substrate with the best-reducing sugar indicator and to determine the optimum conditions for hydrolysis of P. cruentum microalgae biomass following the Box-Behnken statistical experimental design, using Response Surface Methodology (RSM). The parameters of the optimized hydrolysis process were HCl concentration (2 - 0.2 N), temperature (60 -120 ˚C), and hydrolysis time (30-180 min). The optimum conditions that have been achieved using RSM are an HCl concentration of 1.91 N, a temperature of 60 °C, and a hydrolysis time of 180 min were predicted a maximum total reducing sugar production of 810 mg/L. The experimental result of total reducing sugar obtained at optimum conditions was 895 mg/L, which was well close to the predicted value, verifying the appropriateness of the model.Abstract is informed about the statements of the problem, methods, scientific finding results and conclusion concisely

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Derman, Eryati, Rahmath Abdulla, Hartinie Marbawi, Mohd Khalizan Sabullah, Jualang Azlan Gansau, and Pogaku Ravindra. "Simultaneous Saccharification and Fermentation of Empty Fruit Bunches of Palm for Bioethanol Production Using a Microbial Consortium of S. cerevisiae and T. harzianum." Fermentation 8, no. 7 (2022): 295. http://dx.doi.org/10.3390/fermentation8070295.

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A simultaneous saccharification and fermentation (SSF) optimization process was carried out on pretreated empty fruit bunches (EFBs) by employing the Response Surface Methodology (RSM). EFBs were treated using sequential acid-alkali pretreatment and analyzed physically by a scanning electron microscope (SEM). The findings revealed that the pretreatment had changed the morphology and the EFBs’ structure. Then, the optimum combination of enzymes and microbes for bioethanol production was screened. Results showed that the combination of S. cerevisiae and T. harzianum and enzymes (cellulase and β-glucosidase) produced the highest bioethanol concentration with 11.76 g/L and a bioethanol yield of 0.29 g/g EFB using 4% (w/v) treated EFBs at 30 °C for 72 h. Next, the central composite design (CCD) of RSM was employed to optimize the SSF parameters of fermentation time, temperature, pH, and inoculum concentration for higher yield. The analysis of optimization by CCD predicted that 9.72 g/L of bioethanol (0.46 g/g ethanol yield, 90.63% conversion efficiency) could be obtained at 72 h, 30 °C, pH 4.8, and 6.79% (v/v) of inoculum concentration using 2% (w/v) treated EFBs. Results showed that the fermentation process conducted using the optimized conditions produced 9.65 g/L of bioethanol, 0.46 g/g ethanol yield, and 89.56% conversion efficiency, which was in close proximity to the predicted CCD model.

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Ernes, Atmiral, Lia Ratnawati, Agustin Krisna Wardani, and Joni Kusnadi. "OPTIMASI FERMENTASI BAGAS TEBU OLEH Zymomonas mobilis CP4 (NRRL B-14023) UNTUK PRODUKSI BIOETANOL (Optimization of Sugarcane Bagasse Fermentation by Zymomonas mobilis CP4 (NRRL B-14023) for Bioethanol Production)." Jurnal Agritech 34, no. 03 (2014): 247. http://dx.doi.org/10.22146/agritech.9452.

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Second generation bioethanol can be produced from fermentation of natural renewable materials, such as agricultural crops, as well as from industrial and domestic waste. The present study was aimed to optimize the fermentation process (inoculum concentration, urea concentration, and fermentation time) for ethanol production from sugarcane bagasse byZymomonas mobilis CP4 using response surface methodology (RSM) central composite experimental design (CCD). The RSM model predicted the optimum value of ethanol content was 1.257% (v/v) at inoculum concentration 15% (v/v), urea concentration 0.3% (w/v), and fermentation time 45 h. Based on the experiment, the ethanol concentrationwas 1.213% (v/v), which was in close agreement with the predicted value. Ethanol yield of this experiment was 0.479 with fermentation efﬁ ciency of 93.9%. The results presented here proved a signiﬁ cant contribution of Z. mobilis CP4 to the production of bioethanol from sugarcane bagasse.Keywords: Bioethanol, sugarcane bagasse, Zymomonas mobilis CP4, fermentation optimization ABSTRAKBioetanol generasi kedua dapat diproduksi dari fermentasi bahan terbarukan, seperti produk hasil pertanian, dan limbah atau hasil samping pengolahan industri dan rumah tangga. Tujuan penelitian ini adalah optimasi parameter fermentasi yang meliputi konsentrasi inokulum, konsentrasi urea, dan lama fermentasi untuk produksi etanol dari bagas tebu oleh Zymomonas mobilis CP4 dengan menggunakan response surface methodology (RSM) central composite experimental design (CCD). Kondisi respon yang optimal berdasarkan prediksi model diperoleh pada konsentrasi inokulum 15% (v/v), konsentrasi urea 0,3% (b/v), dan lama fermentasi 45 jam, dengan prediksi respon kadar etanol sebesar 1,257%(v/v). Berdasarkan hasil penelitian, kadar etanol optimal diperoleh sebesar 1,213% (v/v), yang menunjukkan hasil yang tidak berbeda jauh dengan prediksi model. Yield etanol yang diperoleh sebesar 0,479 dengan eﬁ siensi fermentasi 93,9%. Hasil penelitian ini membuktikan bahwa strain bakteri Zymomonas mobilis CP4 memiliki potensi yang cukup menjanjikan sebagai mikroba penghasil etanol.Kata kunci: Bioetanol, bagas tebu, Zymomonas mobilis CP4, optimasi fermentasi

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Cheng, Jia Qi, You You Sun, Yuan Cai Chen, Ying Liu, Yong You Hu, and Jay J. Cheng. "Optimization of Dilute Acid Pretreatment of Paulownia for the Production of Bioethanol by Respond Surface Methodology." Advanced Materials Research 550-553 (July 2012): 1066–70. http://dx.doi.org/10.4028/www.scientific.net/amr.550-553.1066.

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Paulownia that is widely distributed in china has the potential for fuel ethanol production because of its relative high cellulose and hemicellulose content and high growth rate. The dilute acid pretreatment hydrolysis process was optimized by developing a respond surface methodology to research the optimum condition of pretreatment. Cellulose conversion ratio and furfural concentration were conducted as the response results of the RSM. The optimal condition of pretreatment is the reaction temperature 145.5°C, the sulfuric acid concentration 1.14% and the residence time 39.3min, the highest cellulose conversion ratio 89.48% was achieved and furfural concentration was smaller than 1g/L. The chemical compositions of untreated paulownia were investigated and their structures were detected by SEM.

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Aguiar, Rodrigo O., Amanda G. P. Carréra, Roberto L. Cunha, et al. "Optimization of the Alcoholic Concentration Obtained From Sugary Cassava (Manihot esculenta Crantz) by Response Surface Methodology." Journal of Agricultural Science 12, no. 11 (2020): 157. http://dx.doi.org/10.5539/jas.v12n11p157.

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Sugary cassava or mandiocaba is a cassava variety of potential use for bioethanol production. In this study, laboratory-scale fermentations were carried out in a bioreactor with a working volume of 1L, using the yeast strain LNF CAT-1. A central composite design (CCD) was applied to determine the extent to which pH, temperature, and yeast concentration influence ethanol production with the aim of improving the fermentation process. The individual effects and the interaction of these factors were analyzed using a surface response method. Physicochemical properties of the material were also investigated and the analysis of root characterization showed high moisture content (~91%) and a low amount of starch (~4.0%), ash values close to 1.0%, total fibers 0.4%, proteins 0.15%, and lipids 0.1%. The results obtained from the wort presented a low acidity (~0.2%), pH close to neutrality (~6.5%), total soluble solids values of ~5.8%, glucose content ~2.3%, fructose ~1.0%, and sucrose ~1.2%. The second-order polynomial regression model determined that the maximum ethanol production of 2.8% (v/v) would be obtained when the optimum pH, temperature, and yeast concentration were ~5.0, 32-36 &ordm;C, and ~10-14 g L-1, respectively.

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Bano, A., and M. Irfan. "Alkali pretreatment of cotton stalk for bioethanol." Bangladesh Journal of Scientific and Industrial Research 54, no. 1 (2019): 73–82. http://dx.doi.org/10.3329/bjsir.v54i1.40733.

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Cotton stalk biomass was treated with NaOH and NaOH-steam pretreatements to get maximum cellulose content. Three factors with three levels such as biomass concentration (5, 10 and 15%), NaOH concentration (1, 3 and 5%) and residence time (4, 6 and 8 h) was performed through Box-Bhenken Design of response surface methodology. The treatment was performed with and without heating at 121oC for 15min and 15psi in an autoclave. Among these two types of treatment, maximum yield of cellulose content 87.80% was observed with 5% w/v NaOH concentration, 10g substrate loading and 4h residence time. The substrate having high cellulose content under optimized pretreatment conditions were analysed through FTIR revealing efficiency of pretreatment. The proposed model for this study was found significant in terms of lower p<0.05 values and findings of this study could be utilized for further processes like saccharification and fermentation to bioethanol. Bangladesh J. Sci. Ind. Res.54(1), 73-82, 2019

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Mohd Noor, Siti Fatimah, Norhazimah Abdul Halim, Dilaeleyana Abu Bakar Sidik, and Teh Ubaidah Noh. "Bioethanol Production from Elaeis Guineensis Oil Palm Trunk Sap using Repeated Batch Fermentation." Journal of Advanced Research in Fluid Mechanics and Thermal Sciences 126, no. 2 (2025): 201–13. https://doi.org/10.37934/arfmts.126.2.201213.

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Elaeis guineensis (E. guineensis) oil palm tree (OPT) presented a novel biomass source, with its OPT sap demonstrating the potential for bioethanol production due to its rich sugar content. The increasing waste of the OPT necessitated exploring ways to maximize its utilization and functionality, making bioethanol production a pertinent avenue for sustainable resource utilization. This study aimed to compare the bioethanol yield concentration production in optimized conditions and non–optimized conditions based on response surface methodology (RSM) data from Box–Behnken design (BBD). This study also investigated the viability of felled E. guineensis OPT sap for bioethanol production on the effect of sugar composition and fermentation conditions. Analysis revealed significant variations in fructose, glucose, and sucrose levels across different trunk segments, with sucrose notably higher in some areas. Using Saccharomyces cerevisiae (S. cerevisiae) Kyokai no. 7 in a 2L bioreactor, the study employed repeated batch fermentation to explore the efficiency of bioethanol yield production across 13 cycles under optimized and non–optimized conditions. The optimized fermentation conditions included a felled E. guineensis OPT sap medium with an initial pH of 6.50, supplemented with 6.80 g/L of peptone and 13.28 g/L of corn steep liquor (CSL) at 30°C. The non–optimized conditions were similar but conducted at room temperature. The maximum bioethanol yield concentration of 35.65 g/L, averaging 23–35 g/L per cycle, highlighted the effectiveness and stability of repeated fermentation under optimized conditions, with the bioethanol yield ranging from 3–4 volume/volume percentage (v/v %). The optimized condition significantly improved bioethanol concentration (38.42 %) and volume content (28.67 %), enhancing production efficiency. Bioethanol yield production was markedly improved under optimized conditions, as confirmed by statistical analysis, while non–optimized settings yielded unstable reported data. This research highlighted the importance of controlled environmental conditions and optimized fermentation processes. The study underscored the potential of felled E. guineensis OPT sap as a biomass source for bioethanol, suggesting promising avenues for the scale–up of bioethanol production in the future.

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Zaafouri, Kaouther, Manel Ziadi, Aida Ben Hassen-Trabelsi, et al. "Optimization of Hydrothermal and Diluted Acid Pretreatments of Tunisian Luffa cylindrica (L.) Fibers for 2G Bioethanol Production through the Cubic Central Composite Experimental Design CCD: Response Surface Methodology." BioMed Research International 2017 (2017): 1–14. http://dx.doi.org/10.1155/2017/9524521.

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This paper opens up a new issue dealing with Luffa cylindrica (LC) lignocellulosic biomass recovery in order to produce 2G bioethanol. LC fibers are composed of three principal fractions, namely, α-cellulose (45.80% ± 1.3), hemicelluloses (20.76% ± 0.3), and lignins (13.15% ± 0.6). The optimization of LC fibers hydrothermal and diluted acid pretreatments duration and temperature were achieved through the cubic central composite experimental design CCD. The pretreatments optimization was monitored via the determination of reducing sugars. Then, the 2G bioethanol process feasibility was tested by means of three successive steps, namely, LC fibers hydrothermal pretreatment performed at 96°C during 54 minutes, enzymatic saccharification carried out by means of a commercial enzyme AP2, and the alcoholic fermentation fulfilled with Saccharomyces cerevisiae. LC fibers hydrothermal pretreatment liberated 33.55 g/kg of reducing sugars. Enzymatic hydrolysis allowed achieving 59.4 g/kg of reducing sugars. The conversion yield of reducing sugar to ethanol was 88.66%. After the distillation step, concentration of ethanol was 1.58% with a volumetric yield about 70%.

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Lama, Muñoz Antonio, Juan Miguel Romero-García, Corpas Cristóbal Cara, Manuel Moya, and Galiano Eulogio Castro. "Low energy-demanding recovery of antioxidants and sugars from olive stones as preliminary steps in the biorefinery context." Industrial Crops and Products 60 (June 22, 2014): 30–38. https://doi.org/10.1016/j.indcrop.2014.05.051.

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Olive stones constitute the main solid by-product of the olive oil extraction process. As a lignocellulosic material, their use as a source of fermentable sugars, antioxidants and other applications has been proposed. In this work the possibilities of a better use of this material through a relatively low energy-demanding operation, e.g. autoclave treatment, are assessed. Dilute acid extraction was used for evaluating the influence of the main variables (temperature, acid concentration and pretreatment time) on the sugar composition and the antioxidant capacity of liquid fractions (prehydrolyzates) issued from autoclave treatment. Results show that the highest production of fermentable sugars, 27 g/100 g initial dry matter, was obtained at the most severe pretreatment conditions (130 ◦C for 90 min and 2% sulfuric acid), with xylose being 90% of the released sugars, while cellulose degradation was limited. Concerning antioxidant capacity of the prehydrolyzates, the best result was obtained at the highest temperatura (130 ◦C) and time (90 min) but using no acid. This procedure is proposed as a preliminary step of a broader treatment scheme which can also include further steps of pretreatment and eventually enzymatic hydrolysis and fermentation. As a conclusion, a two-step process strategy is suggested to optimize the recovery of antioxidants in the first step, and the production of fermentable sugars in the second step.

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Chouaibi, Moncef, Khaled Ben Daoued, Khouloud Riguane, Tarek Rouissi, and Giovanna Ferrari. "Production of bioethanol from pumpkin peel wastes: Comparison between response surface methodology (RSM) and artificial neural networks (ANN)." Industrial Crops and Products 155 (November 2020): 112822. http://dx.doi.org/10.1016/j.indcrop.2020.112822.

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Ishmayana, Safri, Deafani Nisrina Ulayya, Debora Tamaris Horasio, et al. "OPTIMIZATION OF METAL ION CONCENTRATION IN YEAST EXTRACT-PEPTONE MEDIUM FOR ENHANCED BIOETHANOL FERMENTATION USING RESPONSE SURFACE METHODOLOGY." Applied Biological Research 27, no. 1 (2025): 94–105. https://doi.org/10.48165/abr.2025.27.01.9.

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Bioethanol is a renewable eco-friendly alternative energy source produced by fermenting simple sugars using Saccharomyces cerevisiae. However, stress factors during fermentation can reduce yeast efficiency. Optimizing the metal ion supplementation in the growth medium is one strategy to mitigate these effects and improve ethanol yield. The present study was aimed to determine the optimal concentrations of calcium, magnesium, and zinc ions for maximizing ethanol production. Fermentation was carried out in yeast extract-peptone (YEP) medium supplemented with these metal ions. Optimization was conducted using response surface methodology with a central composite design (RSM-CCD). The experimental steps included yeast cell rejuvenation, media preparation, starter culture development, and fermentation. Optimal concentrations of calcium, magnesium, and zinc were 26.36, 368.18, and 66.82 mg L⁻¹, respectively. Under these conditions, the predicted ethanol yield was 0.567 g g⁻¹, while the validation experiment produced 0.274 ± 0.018 g g⁻¹. This represents a 20.7% increase compared to the center point (0.274 vs 0.227 g g⁻¹). Although optimization enhanced ethanol yield, further refinement of fermentation conditions and medium composition is needed to reduce the gap between predicted and experimental values and to improve overall fermentation performance.

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Journal articles on the topic 'Response Surface Methodology and Bioethanol'

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