Optimization of physical parameters for phycobiliprotein extracted from Oscillatoria agardhii and Synechococcus nidulans / Oscillatoria agardhii ve Synechococcus nidulans türlerinden fikobiliprotein ekstraksiyonu için fiziksel parametrelerin optimizasyonu

2015 ◽  
Vol 40 (6) ◽  
Author(s):  
İrem Deniz ◽  
Esra İmamoğlu ◽  
Meltem Conk Dalay
Keyword(s):  
Response Surface Methodology ◽  
Experimental Design ◽  
Light Intensity ◽  
Response Surface ◽  
Process Parameters ◽  
High Yield ◽  
Physical Parameters ◽  
Agitation Rate ◽  
Orbital Shaking ◽  
Oscillatoria Agardhii

AbstractObjective: Physical process parameters play a major role in the cultivation of cyanobacteria to provide high yield. The aim of this study was to optimize physical parameters such as light intensity and agitation rate which might affect the phycobiliprotein formations for cyanobacterial strains of Oscillatoria agardhii and Synechococcus nidulans using response surface methodology.Methods: The cyanobacterial strains were cultured in 250 mL flasks containing 100 mL of EM medium in orbital shaking incubator under the temperature of 22±2°C at different light intensities and agitation rates for 10 days. The experimental design was carried out using 2Results: The optimization solution of O. agardhii (approximately at 156 rpm under the light intensity of 65 μmol photons mConclusion: High agitation rate stimulated the faster growth than increased the light intensity for the growths of cyanobacterial strains.

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.

Optimization of the Fermentation Conditions for 1-Deoxynojirimycin Production by Streptomyces lawendulae Applying the Response Surface Methodology

2011 ◽  
Vol 7 (3) ◽  
Author(s):  
Zhao-Jun Wei ◽  
Le-Chun Zhou ◽  
Hua Chen ◽  
Gui-Hai Chen
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Starch Content ◽  
Ultra Violet ◽  
Soluble Starch ◽  
High Yield ◽  
Yield Strain ◽  
Fermentation Time ◽  
Ethyl Sulfate ◽  
Initial Ph

Moranoline (1-Deoxynojirimycin, DNJ) is a piperidine alkaloid, and shows high inhibit activities to glucoamylase and ?-glucosidase. One DNJ high-yield strain of Streptomyces lawendulae was obtained after isolated form soil and mutated with the ultra violet (UV) and ethyl sulfate (DES), which named as TB-412, and can produce DNJ with 35.925 mg/L. Response surface methodology (RSM) was applied to optimize the parameters of DNJ yield from S. lawendulae TB-412. The effects of independent variables of fermentation, including time, temperature, initial pH and the soluble starch content were investigated. The statistical analysis showed that the fermentation time, pH and the soluble starch content, and the quadratics of time, temperature, pH and the soluble starch content, as well as the interactions between fermentation time and pH, and time and the soluble starch content, showed significant effects on DNJ yield. The optimal process parameters for DNJ production within the experimental range of the variables researched was at 11d, 27 °C, pH 7.5, and 8% soluble starch content. At this condition, the DNJ yield was predicted to be 42.875 mg/L.

Optimizing the physical parameters to achieve maximum products from co-liquefaction using response surface methodology

Fuel ◽  
2017 ◽  
Vol 207 ◽  
pp. 102-108 ◽  
Author(s):  
Siti Nur Ain Mohd Hassan ◽  
Mohd Azlan Mohd Ishak ◽  
Khudzir Ismail
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Physical Parameters

Fiber laser processing of GFRP composites and multi-objective optimization of the process using response surface methodology

2018 ◽  
Vol 53 (11) ◽  
pp. 1459-1473 ◽  
Author(s):  
Shiva Dayal Rao B ◽  
Abhijeet Sethi ◽  
Alok Kumar Das
Keyword(s):  
Response Surface Methodology ◽  
Fiber Laser ◽  
Response Surface ◽  
Process Parameters ◽  
Heat Affected Zone ◽  
Cutting Speed ◽  
Kerf Width ◽  
Laser Irradiance ◽  
Input Process ◽  
Cut Surface

In the present investigation, a continuous wave fiber laser with maximum power of 400 W was used to cut a glass fiber reinforced plastic sheet of 4.56 mm thickness using Nitrogen as assisting gas. The influence processing parameters such as laser irradiance, gas pressure, and cutting speed on the cut surface quality were investigated by using response surface methodology. The different responses of laser cut surface such as upper kerf width, taper percentage along the cut depth, and heat-affected zone on the top surface were measured to analyze the influence of input process parameters on the responses. A statistical analysis on the obtained results was conducted and found that the optimum values of different input process parameters were laser irradiance: 8.28 × 105 watt/cm2, cutting speed: 600 mm/min and assisting gas pressure: 7.84 bar. The corresponding values of responses were upper kerf width: 177.4 µm, taper 0.73%, and heat-affected zone on top surface: 109.23 µm. The confirmation experiments were conducted with the obtained optimum parameter setting and observed that the predicted values and experimental values for upper kerf width, taper percentage and top surface heat-affected zone were within the error limits of 2.52%, 1.84%, and 0.45%, respectively. Furthermore, damages like loose fibers, interlayer fractures, evaporation of matrix material and fiber breakages were observed.

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