scholarly journals Optimization of Aeration and Agitation Rate for Lipid and Gamma Linolenic Acid Production byCunninghamella bainieri2A1 in Submerged Fermentation Using Response Surface Methodology

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Normah Saad ◽  
Peyman Abdeshahian ◽  
Mohd Sahaid Kalil ◽  
Wan Mohtar Wan Yusoff ◽  
Aidil Abdul Hamid
Keyword(s):  
Response Surface Methodology ◽  
Production Process ◽  
Response Surface ◽  
Linolenic Acid ◽  
Lipid Production ◽  
Aeration Rate ◽  
Agitation Speed ◽  
Agitation Rate ◽  
Optimum Conditions ◽  
Gamma Linolenic Acid

The locally isolated filamentous fungusCunninghamella bainieri2A1 was cultivated in a 5 L bioreactor to produce lipid and gamma-linolenic acid (GLA). The optimization was carried out using response surface methodology based on a central composite design. A statistical model, second-order polynomial model, was adjusted to the experimental data to evaluate the effect of key operating variables, including aeration rate and agitation speed on lipid production. Process analysis showed that linear and quadratic effect of agitation intensity significantly influenced lipid production process (P<0.01). The quadratic model also indicated that the interaction between aeration rate and agitation speed had a highly significant effect on lipid production (P<0.01). Experimental results showed that a lipid content of 38.71% was produced in optimum conditions using an airflow rate and agitation speed of 0.32 vvm and 599 rpm, respectively. Similar results revealed that 0.058 (g/g) gamma-linolenic acid was produced in optimum conditions where 1.0 vvm aeration rate and 441.45 rpm agitation rate were used. The regression model confirmed that aeration and agitation were of prime importance for optimum production of lipid in the bioreactor.

Enhancing the production of gamma-linolenic acid in Hansenula polymorpha by fed-batch fermentation using response surface methodology

2011 ◽  
Vol 65 (2) ◽  
Author(s):  
Bhimabol Khongto ◽  
Kobkul Laoteng ◽  
Anan Tongta
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Linolenic Acid ◽  
Yeast Extract ◽  
Batch Fermentation ◽  
Hansenula Polymorpha ◽  
Gamma Linolenic Acid ◽  
Fed Batch ◽  
Fed Batch Fermentation ◽  
Gla Production

AbstractGamma-linolenic acid (GLA, C18:3Δ6,9,12) is an n-6 polyunsaturated fatty acid (PUFA) that has been used for the alleviation and treatment of a number of symptoms and diseases. Increasing GLA demand has led to a search for alternative producers and potential strategies for GLA production. Based on the successful performance of Hansenula polymorpha, a methylotrophic yeast, as a “cell factory” for the production of valuable bioproducts, a bioprocess development approach was implemented for GLA production in the recombinant yeast carrying the mutated Δ6-desaturase gene of Mucor rouxii. Using a substrate-feeding strategy under glycerol-limited conditions, the physical-chemical variables during the fed-batch fermentation of the recombinant H. polymorpha were optimised for GLA production through response surface methodology using a Box-Behnken design. The medium composition, including yeast extract and trace elements, and dissolved oxygen tension (DOT) were targeted. We found that DOT was the most effective variable for enhancing GLA yield. These results also suggest that the optimum conditions for GLA production are 28 % saturation of DOT, 1 g L−1 of yeast extract and 3.6 mL L−1 of the Pichia trace metals 1 (PTM1).

scholarly journals Optimization of Pectate Lyase Production from Paenibacillus polymyxa N10 using Response Surface Methodology

2010 ◽  
Vol 3 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Molnapat Songpim ◽  
Pilanee Vaithanomsat ◽  
Sawitri Chuntranuluck
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Polynomial Regression ◽  
Pectate Lyase ◽  
Paenibacillus Polymyxa ◽  
Aeration Rate ◽  
Agitation Rate ◽  
Stirred Tank Bioreactor ◽  
Lyase Activity ◽  
Negative Effect

The parameters affecting the production of pectate lyase from P. polymyxa N10 were studied using the response surface methodology agitation rate (X1, 100-300 rpm), temperature (X2, 25-45 °C) and pH (X3, 5.5-9.5). The most significant factors influencing enzyme production were temperature and pH. The second order polynomial regression model obtained was fitted and found adequate, with an R2 of 0.9600 (p < 0.001). A maximum pectate lyase activity of 84.5 U/ml was attained in 72 h of cultivation at agitation rate 200 rpm, temperature 35 °C and pH 8. Optimizations of agitation rate and aeration on pectate lyase production were also carried out in a 5-l stirred-tank bioreactor. The aeration rate was varied in the range of 0.5-2 vvm at agitation rate of 200 rpm (temperature 35°C and initial pH 8). At agitation rate of 200 rpm, the shear force was high and then decreased the pectate lyase activity due to its negative effect on the enzyme structure. A maximum pectate lyase activity of 110.42 U/ml in the bioreactor was close to that obtained from the shake flask fermentation study.

Optimization of slicing sugar beet for improving the purity of diffusion juice using response surface methodology and genetic algorithm

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Maryam Naghipour Zade ◽  
Mohammad Hossein Aghkhani ◽  
Abbas Rohani ◽  
Khalil Behzad ◽  
Armaghan Kosari-Moghaddam
Keyword(s):  
Genetic Algorithm ◽  
Response Surface Methodology ◽  
Sugar Beet ◽  
Production Process ◽  
Response Surface ◽  
Quadratic Model ◽  
Sugar Production ◽  
Optimum Conditions ◽  
The Impact

Abstract The purity is accounted for one of the main characteristics of sugar beet juice in the sugar production process. In this regard, in the paper, the impact of slicing parameters including blade type, slicing angle from 0 to 90°, slicing thickness from 3 to 6 mm, and preheating duration from 3 to 15 min was studied on juice purity using Response Surface Methodology (RSM). The Genetic Algorithm (GA) technique was also employed to find the optimum values of variables to reach the highest juice purity. The results indicated that the quadratic model was the best model to predict juice purity. The Findings presented that as cossette thickness and slicing angle increased, the juice purity was improved. Optimization of the quadratic model by GA showed the best cossette thickness was 6 mm for both blades. The results of optimization indicated that 92.25 and 94.45% juice purities could be obtained from optimum conditions.

scholarly journals Optimizing of Microalgae Scenedesmus sp. Biomass Production in Wet Market Wastewater Using Response Surface Methodology

2021 ◽  
Vol 13 (4) ◽  
pp. 2216
Author(s):  
Najeeha Mohd Apandi ◽  
Mimi Suliza Muhamad ◽  
Radin Maya Saphira Radin Mohamed ◽  
Norshuhaila Mohamed Sunar ◽  
Adel Al-Gheethi ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Biomass Yield ◽  
Biomass Productivity ◽  
Maximum Growth ◽  
Maximum Growth Rate ◽  
Aeration Rate ◽  
Composition Analysis ◽  
Wet Market ◽  
Central Composite

The present study aimed to optimize the production of Scenedesmus sp. biomass during the phycoremediation process. The biomass productivity was optimized using face centred central composite design (FCCCD) in response surface methodology (RSM) as a function of two independent variables that included wet market wastewater concentrations (A) with a range of 10% to 75% and aeration rate (B) with a range of 0.02 to 4.0 L/min. The results revealed that the highest biomass productivity (73 mg/L/d) and maximum growth rate (1.19 day−1) was achieved with the 64.26% of (A) and 3.08 L/min of (B). The GC-MS composition analysis of the biomass yield extract revealed that the major compounds are hexadecane (25%), glaucine (16.2%), and phytol (8.33%). The presence of these compounds suggests that WMW has the potential to be used as a production medium for Scenedesmus sp. Biomass, which has several applications in the pharmaceutical and chemical industry.

scholarly journals Enzyme optimization to reduce the viscosity of pitanga (Eugenia uniflora L.) juice

2016 ◽  
Vol 19 (0) ◽  
Author(s):  
Ricardo Schmitz Ongaratto ◽  
Luiz Antonio Viotto
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Incubation Time ◽  
Regression Models ◽  
Incubation Temperature ◽  
Correlation Coefficients ◽  
Enzyme Concentration ◽  
Optimum Conditions ◽  
Activity Time ◽  
Independent Variables

Summary The aim of this work was to separately evaluate the effects of pectinase and cellulase on the viscosity of pitanga juice, and determine the optimum conditions for their use employing response surface methodology. The independent variables were pectinase concentration (0-2.0 mg.g–1) and cellulase concentration (0-1.0 mg.g–1), activity time (10-110 min) and incubation temperature (23.2-56.8 °C). The use of pectinase and cellulase reduced the viscosity by about 15% and 25%, respectively. The results showed that enzyme concentration was the most important factor followed by activity time, and for the application of cellulase the incubation temperature had a significant effect too. The regression models showed correlation coefficients (R2) near to 0.90. The pectinase application conditions that led to the lowest viscosity were: concentration of 1.7 mg.g–1, incubation temperature of 37.6 °C and incubation time of 80 minutes, while for cellulase the values were: concentration of 1.0 mg.g-1, temperature range of 25 °C to 35 °C and incubation time of 110 minutes.

scholarly journals OPTIMIZATION OF REFLUX EXTRACTION FOR CAESALPINIA SAPPAN LINN. WOOD BY USING RESPONSE SURFACE METHODOLOGY

2020 ◽  
Vol 83 (1) ◽  
pp. 85-92
Author(s):  
Mohd Azahar Mohd Ariff ◽  
Muhammad Syafiq Abd Jalil ◽  
Noor ‘Aina Abdul Razak ◽  
Jefri Jaapar
Keyword(s):  
Particle Size ◽  
Response Surface Methodology ◽  
Drinking Water ◽  
Response Surface ◽  
Extraction Time ◽  
Percentage Error ◽  
Optimum Conditions ◽  
Caesalpinia Sappan ◽  
The Mean ◽  
Repeated Runs

Caesalpinia sappan linn. (CSL) is a plant which is also known as Sepang tree contains various medicinal values such as to treat diarrhea, skin rashes, syphilis, jaundice, drinking water for blood purifying, diabetes, and to improve skin complexion. The aim of this study is to obtain the most optimum condition in terms of the ratio of sample to solvent, particle size, and extraction time to get the highest amount of concentration of the CSL extract. In this study, the ranges of each parameters used were: ratio sample to solvent: 1.0:20, 1.5:20, 2.0:20, 2.5:20, 3.0:20, particle size: 1 mm, 500 um, 250 um, 125 um, 63 um, and extraction time: 1 hr, 2 hr, 3 hr, 4 hr, 5 hr. The concentration was analyzed using a UV-vis spectrophotometer. The optimum conditions were obtained by response surface methodology. From the design, 20 samples were run throughout this experiment. The optimized value from the RSM were 2.0:20 for ratio sample to solvent, 125 µm of particle size and 2.48 hours with the concentration of 37.1184 ppm. The accuracy of the predictive model was validated with 2 repeated runs and the mean percentage error was less than 3%. This confirmed the model’s capability for optimizing the conditions for the reflux extraction of CSL’s wood.

scholarly journals Optimising Brewery-Wastewater-Supported Acid Mine Drainage Treatment vis-à-vis Response Surface Methodology and Artificial Neural Network

Processes ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1485
Author(s):  
Enoch A. Akinpelu ◽  
Seteno K. O. Ntwampe ◽  
Abiola E. Taiwo ◽  
Felix Nchu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Response Surface Methodology ◽  
Acid Mine Drainage ◽  
Response Surface ◽  
Mine Drainage ◽  
Sulphate Reduction ◽  
Optimum Conditions ◽  
Acid Mine ◽  
Artificial Neural

This study investigated the use of brewing wastewater (BW) as the primary carbon source in the Postgate medium for the optimisation of sulphate reduction in acid mine drainage (AMD). The results showed that the sulphate-reducing bacteria (SRB) consortium was able to utilise BW for sulphate reduction. The response surface methodology (RSM)/Box–Behnken design optimum conditions found for sulphate reduction were a pH of 6.99, COD/SO42− of 2.87, and BW concentration of 200.24 mg/L with predicted sulphate reduction of 91.58%. Furthermore, by using an artificial neural network (ANN), a multilayer full feedforward (MFFF) connection with an incremental backpropagation network and hyperbolic tangent as the transfer function gave the best predictive model for sulphate reduction. The ANN optimum conditions were a pH of 6.99, COD/SO42− of 0.50, and BW concentration of 200.31 mg/L with predicted sulphate reduction of 89.56%. The coefficient of determination (R2) and absolute average deviation (AAD) were estimated as 0.97 and 0.046, respectively, for RSM and 0.99 and 0.011, respectively, for ANN. Consequently, ANN was a better predictor than RSM. This study revealed that the exclusive use of BW without supplementation with refined carbon sources in the Postgate medium is feasible and could ensure the economic sustainability of biological sulphate reduction in the South African environment, or in any semi-arid country with significant brewing activity and AMD challenges.

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.

Optimization of photocatalytic degradation of real textile dye house wastewater by response surface methodology

2016 ◽  
Vol 74 (9) ◽  
pp. 1999-2009 ◽  
Author(s):  
Sayed Mohammad Bagher Hosseini ◽  
Narges Fallah ◽  
Sayed Javid Royaee
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Flow Rate ◽  
Advanced Oxidation Process ◽  
Influential Factor ◽  
P Value ◽  
Textile Dye ◽  
Optimum Conditions ◽  
Effective Parameters ◽  
Initial Ph

This study evaluates the advanced oxidation process for decolorization of real textile dyeing wastewater containing azo and disperse dye by TiO2 and UV radiation. Among effective parameters on the photocatalytic process, effects of three operational parameters (TiO2 concentration, initial pH and aeration flow rate) were examined with response surface methodology. The F-value (136.75) and p-value &lt;0.0001 imply that the model is significant. The ‘Pred R-Squared’ of 0.95 is in reasonable agreement with the ‘Adj R-Squared’ of 0.98, which confirms the adaptability of this model. From the quadratic models developed for degradation and subsequent analysis of variance (ANOVA) test using Design Expert software, the concentration of catalyst was found to be the most influential factor, while all the other factors were also significant. To achieve maximum dye removal, optimum conditions were found at TiO2 concentration of 3 g L−1, initial pH of 7 and aeration flow rate of 1.50 L min−1. Under the conditions stated, the percentages of dye and chemical oxygen demand removal were 98.50% and 91.50%, respectively. Furthermore, the mineralization test showed that total organic compounds removal was 91.50% during optimum conditions.

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