scholarly journals Application of Response Surface Methodology for Optimizing the Production of Bioethanol from Calabash (Crescentia cujete) Substrate Using Saccharomyces cerevisiae

2019 ◽  
pp. 1-12 ◽  
Author(s):  
N. U. Nwogwugwu ◽  
G. O. Abu ◽  
O. Akaranta ◽  
E. C. Chinakwe
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Reducing Sugars ◽  
Surface Model ◽  
Wide Range ◽  
Crescentia Cujete ◽  
Input Variables ◽  
Ph Range ◽  
Rsm Model

Aim: The study employed the Response surface methodology (RSM) model to optimize ethanol production from Calabash (Crescentia cujete) pulp juice using Saccharomyces cerevisiae. 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 Saccharomyces cerevisiae 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 25-40°C. The optimal pH range for performance of S. cerevisiae for the fermentation process was pH 5.0-6.5. The optimum volume of inoculum was 5.5%v/v (ie 5.5 ml in 94.5ml juice). The optimized process using the RSM model gave 6.19% v/v bioethanol. Control: The bioethanol yield from Calabash substrate is reasonable considering the concentration of reducing sugars obtained from the juice and the duration of the fermentation.

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

2021 ◽  
pp. 17-33
Author(s):  
N. U. Nwogwugwu ◽  
G.O. Abu ◽  
O. Akaranta
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Response Surface ◽  
Reducing Sugars ◽  
Surface Model ◽  
Wide Range ◽  
Crescentia Cujete ◽  
Input Variables ◽  
Ph Range ◽  
Rsm Model ◽  
Clear Solution

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

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

2021 ◽  
Vol 14 (2) ◽  
pp. 204-216
Author(s):  
Ngozi Ursulla Nwogwugwu ◽  
Gideon O. Abu ◽  
Onyewuchi Akaranta ◽  
Ettienne C. Chinakwe ◽  
Ikenna N.Nwachukwu ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Ethanol Production ◽  
Response Surface ◽  
Reducing Sugars ◽  
Surface Model ◽  
Wide Range ◽  
Crescentia Cujete ◽  
Input Variables ◽  
Ph Range ◽  
Rsm Model

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.

scholarly journals Modeling and Sensitivity Analysis of the Forward Osmosis Process to Predict Membrane Flux Using a Novel Combination of Neural Network and Response Surface Methodology Techniques

Membranes ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 70
Author(s):  
Jasir Jawad ◽  
Alaa H. Hawari ◽  
Syed Javaid Zaidi
Keyword(s):  
Response Surface Methodology ◽  
Experimental Design ◽  
Response Surface ◽  
Forward Osmosis ◽  
Feed Solution ◽  
Operating Conditions ◽  
Ann Model ◽  
Membrane Flux ◽  
Input Variables ◽  
Rsm Model

The forward osmosis (FO) process is an emerging technology that has been considered as an alternative to desalination due to its low energy consumption and less severe reversible fouling. Artificial neural networks (ANNs) and response surface methodology (RSM) have become popular for the modeling and optimization of membrane processes. RSM requires the data on a specific experimental design whereas ANN does not. In this work, a combined ANN-RSM approach is presented to predict and optimize the membrane flux for the FO process. The ANN model, developed based on an experimental study, is used to predict the membrane flux for the experimental design in order to create the RSM model for optimization. A Box–Behnken design (BBD) is used to develop a response surface design where the ANN model evaluates the responses. The input variables were osmotic pressure difference, feed solution (FS) velocity, draw solution (DS) velocity, FS temperature, and DS temperature. The R2 obtained for the developed ANN and RSM model are 0.98036 and 0.9408, respectively. The weights of the ANN model and the response surface plots were used to optimize and study the influence of the operating conditions on the membrane flux.

scholarly journals Optimization design of heat pipe heat exchanger using response surface methodology

2021 ◽  
Vol 261 ◽  
pp. 01030
Author(s):  
Shuai Pu ◽  
Wei Huang
Keyword(s):  
Response Surface Methodology ◽  
Heat Exchanger ◽  
Heat Pipe ◽  
Response Surface ◽  
Optimization Design ◽  
Design Method ◽  
Surface Model ◽  
Experimental Design Method ◽  
Input Variables ◽  
Pipe Heat

In this paper, Optimization design of heat pipe heat exchanger (HPHX) is processed utilizing the Response Surface Methodology (RSM). The response surface model was built by regressive analysis using Latin hypercube experimental design method and numerical simulation. Through response surface analysis, it is found that the two input variables affecting the performance of HPHX are the heat pipe pitch and the Inlet and outlet distance. Moreover, the maximum value of the overall performance factor on the response surface is searched using genetic algorithm, and the optimal values of four input variables are obtained.

Demulsification of a Water-in-crude Oil Emulsion with a Corn Oil BasedDemulsifier using the Response Surface Methodology: Modelling and Optimization

2021 ◽  
Vol 14 ◽  
Author(s):  
Abed Saad ◽  
Nour Abdurahman ◽  
Rosli Mohd Yunus
Keyword(s):  
Response Surface Methodology ◽  
Crude Oil ◽  
Water Content ◽  
Response Surface ◽  
Separation Efficiency ◽  
Corn Oil ◽  
Oil Emulsion ◽  
Optimal Values ◽  
Input Variables ◽  
Oil Emulsions

: In this study, the Sany-glass test was used to evaluate the performance of a new surfactant prepared from corn oil as a demulsifier for crude oil emulsions. Central composite design (CCD), based on the response surface methodology (RSM), was used to investigate the effect of four variables, including demulsifier dosage, water content, temperature, and pH, on the efficiency of water removal from the emulsion. As well, analysis of variance was applied to examine the precision of the CCD mathematical model. The results indicate that demulsifier dose and emulsion pH are two significant parameters determining demulsification. The maximum separation efficiency of 96% was attained at an alkaline pH and with 3500 ppm demulsifier. According to the RSM analysis, the optimal values for the input variables are 40% water content, 3500 ppm demulsifier, 60 °C, and pH 8.

scholarly journals Efficient Removal of Levofloxacin by Activated Persulfate with Magnetic CuFe2O4/MMT-k10 Nanocomposite: Characterization, Response Surface Methodology, and Degradation Mechanism

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3583
Author(s):  
Junying Yang ◽  
Minye Huang ◽  
Shengsen Wang ◽  
Xiaoyun Mao ◽  
Yueming Hu ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Photoelectron Spectroscopy ◽  
Degradation Mechanism ◽  
Sol Gel ◽  
Combustion Method ◽  
Copper Ferrite ◽  
X Ray ◽  
Rsm Model

In this study, a magnetic copper ferrite/montmorillonite-k10 nanocomposite (CuFe2O4/MMT-k10) was successfully fabricated by a simple sol-gel combustion method and was characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), the Brunner–Emmett–Teller (BET) method, vibrating sample magnetometer (VSM), and X-ray photoelectron spectroscopy (XPS). For levofloxacin (LVF) degradation, CuFe2O4/MMT-k10 was utilized to activate persulfate (PS). Due to the relative high adsorption capacity of CuFe2O4/MMT-k10, the adsorption feature was considered an enhancement of LVF degradation. In addition, the response surface methodology (RSM) model was established with the parameters of pH, temperature, PS dosage, and CuFe2O4/MMT-k10 dosage as the independent variables to obtain the optimal response for LVF degradation. In cycle experiments, we identified the good stability and reusability of CuFe2O4/MMT-k10. We proposed a potential mechanism of CuFe2O4/MMT-k10 activating PS through free radical quenching tests and XPS analysis. These results reveal that CuFe2O4/MMT-k10 nanocomposite could activate the persulfate, which is an efficient technique for LVF degradation in water.

scholarly journals Optimization of the extraction of natural phenolic antioxidants from the seeds of Tamarindus indica L. - an undervalued by product of food processing - using response surface methodology

2018 ◽  
Vol 62 (1) ◽  
pp. 67-74 ◽  
Author(s):  
Atreyi Sarkar ◽  
Uma Ghosh
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Extraction Time ◽  
Phenolic Antioxidants ◽  
Extraction Temperature ◽  
Tamarindus Indica ◽  
Solvent Concentration ◽  
Antioxidant Power ◽  
Wide Range ◽  
Ferric Reducing Antioxidant Power

The seeds of Tamarindus indica are known to possess a wide range of phenolic compounds with high antioxidant activity as measured by the ferric reducing antioxidant power (FRAP). In the present study, the optimum conditions for the extraction of crude phenolic antioxidants from Tamarind seed were determined using response surface methodology (RSM). A central composite design (CCD) was used to investigate the effects of four independent variables, namely concentration of extractable solids in solvent (g/ml; X1), extraction time (h; X2), extraction temperature (°C; X3) and solvent concentration (%, v/v; X4) on the responses of total polyphenol content (TPC) and FRAP. The CCD consisted of 30 experimental runs. A second-order polynomial model was used for predicting the responses. Canonical analysis of the surface responses revealed that the predicted optimal conditions for the maximal yield of TPC and FRAP were concentration of extractable solids in solvent of 0.049 g/ml, extraction time of 3.24 h, extraction temperature of 45 °C and a solvent concentration of 50%. The experimental values in the optimised condition coincided with the predicted ones within a 95% confidence interval, hence indicating the suitability of the model and the success of RSM in optimizing the extraction parameters.

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