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.

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.

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.

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.

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.

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