scholarly journals Optimization of medium composition to induce cellulase production of Bacillus sp. by Response Surface Methodology

2014 ◽  
Vol 17 (2) ◽  
pp. 47-55
Author(s):  
Loan Thi Bich Nguyen ◽  
Huong Thuy Nguyen
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Yeast Extract ◽  
Cellulase Activity ◽  
Cellulase Production ◽  
Culture Collection ◽  
Medium Composition ◽  
Interactive Effects ◽  
Design Matrix ◽  
Meat Extract

In the past, optimization in biological analyses has been performed by measuring influence of one factor at a time. The disadvantage of this technique is not presence any interactive effects of factors studies and it needs a large number of experiments. Consequently, the Response Surface Methodology (RSM) is the most popular choice for optimization. It used the effects of mathematics and statistics to study optimization with minimum experimental trials and therefore interactive variables may be involved. This study has selected and screened seven Bacillus strain in Vietnam Type Culture Collection which can product cellulase in the medium with CMC as an inducer. VTCC-B-0497 presented the best result. Then, only 15 experiments of design matrix by Box-Behnken were necessary to determine optimal concentrations of three variables including the concentration of Carboxymethylcellulose, Yeast extract and Meat extract to product cellulase. The model could be employed to predict the response. The maximum of cellulase activity was 2.48 U at the concentration of Carboxymethylcellulose 0.25% w/v, yeast extract 0.7% w/v and meat extract 0.2% w/v.

scholarly journals Enhanced Production of Cellulase from Pineapple Waste by Response Surface Methodology

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
P. Saravanan ◽  
R. Muthuvelayudham ◽  
T. Viruthagiri
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Yeast Extract ◽  
Cellulase Activity ◽  
Cellulase Production ◽  
Pineapple Waste ◽  
Enhanced Production ◽  
Validation Experiment ◽  
Soybean Cake ◽  
Cake Flour

Optimization of the media components for cellulase production usingTrichoderma reeseiwas carried out. The optimization of cellulase production using pineapple waste as substrate was performed with statistical methodology based on experimental designs. The screening of nutrients and their influence on the cellulase production was studied using a Plackett-Burman design. Avicel, soybean cake flour, KH2PO4, and yeast extract were found to have the positive influence for the production of cellulase. The selected components were optimized using response surface methodology. The optimum concentrations are avicel: 26.5 g/L, soybean cake flour: 22.5 g/L, KH2PO4: 4.5 g/L, and yeast extract: 12.3 g/L. A maximum cellulase activity of 8.61 IU/mL was obtained under the optimized medium in the validation experiment.

scholarly journals Response surface methodology-artificial neural network based optimization and strain improvement of cellulase production by Streptomyces sp.

2020 ◽  
Vol 36 (4) ◽  
Author(s):  
Ega Soujanya Lakshmi ◽  
Manda Rama Narasinga Rao ◽  
Muddada Sudhamani
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Wild Strain ◽  
Cellulase Activity ◽  
Cellulase Production ◽  
Optimal Conditions ◽  
Zone Formation ◽  
Artificial Neural

ABSTRACT Thirty seven different colonies were isolated from decomposing logs of textile industries. From among these, a thermotolerant, grampositive, filamentous soil bacteria Streptomyces durhamensis vs15 was selected and screened for cellulase production. The strain showed clear zone formation on CMC agar plate after Gram’s iodine staining.  Streptomyces durhamensis vs15 was further confirmed for cellulase production by estimating the reducing sugars through dinitrosalicylic acid (DNS) method. The activity was enhanced by sequential mutagenesis using three mutagens of ultraviolet irradiation (UV), N methyl-N’-nitro-N-nitrosoguanidine (NTG) and Ethyl methane sulphonate (EMS). After mutagenesis, the cellulase activity of GC23 (mutant) was improved to 1.86 fold compared to the wild strain (vs15). Optimal conditions for the production of cellulase by the GC 23 strain were evaluated using Response Surface Methodology (RSM) and Artificial Neural Network (ANN). Effect of pH, temperature, duration of incubation, , and substrate concentration on cellulase production were evaluated. Optimal conditions for the production of cellulase enzyme using Carboxy Methyl Cellulase as a substrate are 55 oC of temperature, pH of 5.0 and incubation for 40 h. The cellulase activity of the mutant Streptomyces durhamensis GC23 was further optimised to 2 fold of the activity of the wild type by RSM and ANN.  

Optimization of Culture Conditions for Cold-Active Cellulase Production by Penicillium cordubense D28 Using Response Surface Methodology

2011 ◽  
Vol 183-185 ◽  
pp. 994-998
Author(s):  
Shuo Dong ◽  
Nai Yu Chi ◽  
Qing Fang Zhang
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Cellulase Activity ◽  
Cellulase Production ◽  
Culture Conditions ◽  
Batch Reactors ◽  
Corn Meal ◽  
Cold Active ◽  
Initial Ph ◽  
Cost Efficient

The design of an optimum and cost-efficient medium for production of cold-active cellulase by Penicillium cordubense D28 was attempted by using response surface methodology (RSM). Based on the Plackett–Burman design, corn meal, (NH4)2SO4 and branc were selected as the most critical nutrient. Subsequently, they were investigated by the Box-Behnken design. Results showed that the maximum cold-active cellulase activity of 110.4U/mL was predicted when the concentration of corn meal, (NH4)2SO4 and branc were 21.97 g/L, 2.39 g/L and 14.99 g/L, respectively. The results were further verified by triplicate experiments. The batch reactors were operated under an optimized condition of the respective corn meal, (NH4)2SO4 and branc concentration of 22 g/L , 2.4 g/L and 15 g/L , the initial pH of 6.0 and experimental temperature of 20 ± 1°C. Without further pH adjustment, the maximum cold-active cellulase activity of 109.8 U/mL was obtained based on the optimized medium with further verified the practicability of this optimum strategy.

scholarly journals Optimization of cellulase production by bacillus sp. BPPT CC RK2 with pH and temperature variation using response surface methodology

2018 ◽  
Vol 67 ◽  
pp. 02051
Author(s):  
Misri Gozan ◽  
Andre Fahriz Harahap ◽  
Chandra Paska Bakti ◽  
Siswa Setyahadi
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Agricultural Waste ◽  
Cellulase Activity ◽  
Preliminary Test ◽  
Cellulase Production ◽  
Bacillus Sp ◽  
Positive Effects ◽  
Rsm Optimization ◽  
Quadratic Effects

Indonesia has abundant ethanol biomass feedstocks. However the second-generation ethanol production process is still hampered by the unavailability of cellulase enzyme in the process of decomposition of lignocellulose into saccharides that can be processed into ethanol through fermentation. Cellulase is known as exozyme produced by Bacillus sp. in submerged fermentation. In this study, cellulase production by Bacillus sp. CC BPPT RK2 on natural and abundant agricultural waste substrates (rice bran and coconut water) was evaluated by investigating the optimum conditions for cellulase production in a 50 ml laboratory scale. Preliminary test using Luria Bentani (LB) medium with additional CMC (1%) were done to select optimum range of pH and Temperature. The preliminary tests results were then followed by optimization of pH and temperature, which were carried out using response surface methodology (RSM). RSM optimization model showed optimum values 6.23 for pH and 40.04 °C, with 14 terms (each with 1 degree of freedom), 4 linear effects, 6 interaction effects and 4 quadratic effects. These optimization by RSM results were slightly different compared to preliminary test, showing the effect of interactions between parameters. The characteristics of interaction among variables tested against the cellulase activity are reported in this study including: positive effects on cellulase activity of the resulting responses; negative interactions affecting the response of cellulase activity; synergistic interaction; and antagonistic interactions between each other.

Optimization of Medium Components for β-Glucosidase Production from Aspergillus Niger by Response Surface Methodology

2013 ◽  
Vol 419 ◽  
pp. 328-333 ◽  
Author(s):  
Chao Zhang ◽  
Rui Huang ◽  
Hui Tian ◽  
Ru Ming Zhao ◽  
Fa Shun Yu ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Yeast Extract ◽  
Influence Factors ◽  
Mutual Effect ◽  
Tween 80 ◽  
Fermentation Medium ◽  
Medium Composition ◽  
Malt Extract ◽  
Medium Components

β-Glucosidase is the key enzyme for the utilization of lignocellulose.But the commercial β-glucosidase can’t be produced. This paper focuses on the study of the β-glucosidase fermentation process.The fermentation medium components for β-glucosidase production from Aspergil lusniger was optimized by response surface methodology (RSM). Firstly, the three of the most important influence factors yeast extract, MnSO4•H2O and MgSO4•7H2O was obtained from Plackett-Burman design screening. Then the path of steepest ascent experiment was adopted to approach the optimal region of the medium composition. Lastly, the optimal concentration and mutual effect of three factors were predicted by RSM. The results showed that the best medium composition was Malt extract 18g/L, Yeast extract 3.22g/L, KH2PO4 3g/L, MnSO4•H2O 0.58mM, Tween-80 0.5mL/L and MgSO4•7H2O 0.23g/L. Under these fermentation conditions, the activity of β-glucosidase was up to 7.33IU/mL with increasing 23.2% than before.

scholarly journals Optimization of Cellulase Production by Aspergillus niger ITBCC L74 with Bagasse as Substrate using Response Surface Methodology

2018 ◽  
Vol 25 (3) ◽  
pp. 115
Author(s):  
Abdullah Abdullah ◽  
Hamid Hamid ◽  
Marcelinus Christwardana ◽  
H. Hadiyanto
Keyword(s):  
Response Surface Methodology ◽  
Aspergillus Niger ◽  
Response Surface ◽  
Cellulase Activity ◽  
Cellulase Production ◽  
Lignocellulosic Material ◽  
Huge Amount ◽  
Activity Effect ◽  
Mgcl2 Concentration ◽  
Important Enzyme

Cellulase is a very important enzyme for lignocelluloses based ethanol production. Bagasse contains mainly cellulose (57.76%), hemicellulose (12.44%), lignin (21.34%), and others (7.96%). Lignocellulosic material has been considered as the good option for cellulase production because it is cheap and already available in a huge amount. The objective of this research was to produce cellulase enzyme and to optimize it by using response surface methodology. The bagasse with water content of 80% was incubated with 2 ml inoculum of Aspergillus niger ITBCC L74 in a 250 ml Erlenmeyer flask. After reaching the specified time the enzyme was extracted and then determined for its activity. Effect of process parameters such as pH, urea and MgCl2 addition were studied. The optimal cellulase activity was achieved at urea concentration of 4.5% (w/w), MgCl2 concentration of 1 mM and pH of 3.5, with maximum enzyme activity was 0.630 U/gr.

The Optimization of Pb(II),Cu(II),Zn(II) and Cd(II) Ions Removal by Micro-Electrolysis Using Response Surface Methodology

2013 ◽  
Vol 800 ◽  
pp. 537-545
Author(s):  
Jian Ping Xu ◽  
Zhi Huang ◽  
Yan Ling Gao
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Mine Drainage ◽  
Polynomial Equation ◽  
Interactive Effects ◽  
Quadratic Model ◽  
Design Matrix ◽  
Box Behnken Design ◽  
Operating Variables ◽  
Order Polynomial

In this study, the Box–Behnken design matrix and response surface methodology (RSM) have been applied in the experiments to evaluate the interactive effects of four most important operating variables: pH (2.0–4.0), temperature (30–40°C )，iron/carbon ratio（1/2–3/2）and iron carbon amounts (2-4) on the removal of Pb (II), Cu(II)，Zn (II) and Cd (II) ions in acid mine drainage with micro-electrolysis (ME) . The total 29 experiments were conducted in the present study for the construction of a quadratic model. The independent variables have significant value 0.0001, which indicates the importance of these variables in the ME process. The values of “Prob > F” less than 0.0500 indicate that model terms are significant for the removal of Cr (VI), Ni (II) and Zn (II) ions. The regression equation coefficients were calculated and the data fitted to a second-order polynomial equation for removal of Pb (II), Cu(II)，Zn (II) and Cd (II) ions with ME.

scholarly journals OVAT Analysis and Response Surface Methodology Based on Nutrient Sources for Optimization of Pigment Production in The Marine-Derived Fungus Talaromyces albobiverticillius 30548 Submerged Fermentation

Marine Drugs ◽  
2021 ◽  
Vol 19 (5) ◽  
pp. 248
Author(s):  
Mekala Venkatachalam ◽  
Alain Shum-Chéong-Sing ◽  
Yanis Caro ◽  
Laurent Dufossé ◽  
Mireille Fouillaud
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Yeast Extract ◽  
Maximum Yield ◽  
Nitrogen Sources ◽  
Industrial Applications ◽  
Fungal Species ◽  
Pigment Production ◽  
Interactive Effects ◽  
Medium Components

Pigment production from filamentous fungi is gaining interest due to the diversity of fungal species, the variety of compounds synthesized, and the possibility of controlled massive productions. The Talaromyces species produce a large panel of metabolites, including Monascus-like azaphilone pigments, with potential use as natural colorants in industrial applications. Optimizing pigment production from fungal strains grown on different carbon and nitrogen sources, using statistical methods, is widespread nowadays. The present work is the first in an attempt to optimize pigments production in a culture of the marine-derived T. albobiverticillius 30548, under the influence of several nutrients sources. Nutrient combinations were screened through the one-variable-at-a-time (OVAT) analysis. Sucrose combined with yeast extract provided a maximum yield of orange pigments (OPY) and red pigments (RPY) (respectively, 1.39 g/L quinizarin equivalent and 2.44 g/L Red Yeast pigment equivalent), as well as higher dry biomass (DBW) (6.60 g/L). Significant medium components (yeast extract, K2HPO4 and MgSO4·7H2O) were also identified from one-variable-at-a-time (OVAT) analysis for pigment and biomass production. A five-level central composite design (CCD) and a response surface methodology (RSM) were applied to evaluate the optimal concentrations and interactive effects between selected nutrients. The experimental results were well fitted with the chosen statistical model. The predicted maximum response for OPY (1.43 g/L), RPY (2.59 g/L), and DBW (15.98 g/L) were obtained at 3 g/L yeast extract, 1 g/L K2HPO4, and 0.2 g/L MgSO4·7H2O. Such optimization is of great significance for the selection of key nutrients and their concentrations in order to increase the pigment production at a pilot or industrial scale.

Optimization of Fermentation Conditions for Cold-Active Cellulase Production by Response Surface Methodology

2011 ◽  
Vol 183-185 ◽  
pp. 1025-1029
Author(s):  
Shuo Dong ◽  
Nai Yu Chi ◽  
Qing Fang Zhang
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Cellulase Activity ◽  
Cellulase Production ◽  
Inoculum Size ◽  
Batch Reactors ◽  
Fermentation Conditions ◽  
Cold Active ◽  
Seed Age ◽  
Cost Efficient

The design of an optimum and cost-efficient fermentation conditions for production of cold-active cellulase by Penicillium cordubense D28 was attempted by using response surface methodology (RSM). Based on the Plackett–Burman design, temperature, seed age and inoculum size were selected as the most critical condition. Subsequently, they were investigated by the Box-Behnken design. Results showed that the maximum cold-active cellulase activity of 110.4U/mL was predicted when the coded values of temperature, seed age and inoculum size were -0.495, 0.455, and 0.253, respectively. The results were further verified by triplicate experiments. The batch reactors were operated under an optimized condition of the respective temperature, seed age and inoculum size of 17°C, 29h and 12.5%. The maximum cold-active cellulase activity of 219.9 U/mL was obtained based on the optimized fermentation conditions with further verified the practicability of this optimum strategy.

Optimisation of medium composition for probiotic biomass production using response surface methodology

2013 ◽  
Vol 81 (1) ◽  
pp. 59-64 ◽  
Author(s):  
Masumeh Anvari ◽  
Gholam Khayati ◽  
Shora Rostami
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Yeast Extract ◽  
Polynomial Regression ◽  
Probiotic Bacterium ◽  
Medium Composition ◽  
Bifidobacterium Animalis ◽  
Extract Concentration ◽  
Initial Ph ◽  
Probiotic Biomass

This study was aimed to optimise lactose, inulin and yeast extract concentration and also culture pH for maximising the growth of a probiotic bacterium,Bifidobacterium animalissubsp.lactisin apple juice and to assess the effects of these factors by using response surface methodology. A second-order central composite design was applied to evaluate the effects of these independent variables on growth of the microorganism. A polynomial regression model with cubic and quadratic terms was used for analysis of the experimental data. It was found that the effects involving inulin, yeast extract and pH on growth of the bacterium were significant, and the strongest effect was given by the yeast extract concentration. Estimated optimum conditions of the factors on the bacterial growth are as follows: lactose concentration=9·5 g/l; inulin concentration=38·5 mg/l; yeast extract concentration=9·6 g/l and initial pH=6·2.

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