Contemporaneous Production of Amylase and Protease through CCD Response Surface Methodology by Newly Isolated Bacillus megaterium Strain B69

The enormous increase in world population has resulted in generation of million tons of agricultural wastes. Biotechnological process for production of green chemicals, namely, enzymes, provides the best utilization of these otherwise unutilized wastes. The present study elaborates concomitant production of protease and amylase in solid state fermentation (SSF) by a newly isolated Bacillus megaterium B69, using agroindustrial wastes. Two-level statistical model employing Plackett-Burman and response surface methodology was designed for optimization of various physicochemical conditions affecting the production of two enzymes concomitantly. The studies revealed that the new strain concomitantly produced 1242 U/g of protease and 1666.6 U/g of amylase by best utilizing mustard oilseed cake as the substrate at 20% substrate concentration and 45% moisture content after 84 h of incubation. An increase of 2.95- and 2.04-fold from basal media was observed in protease and amylase production, respectively. ANOVA of both the design models showed high accuracy of the polynomial model with significant similarities between the predicted and the observed results. The model stood accurate at the bench level validation, suggesting that the design model could be used for multienzyme production at mass scale.

Download Full-text

Model-Based Design of Experiments for Kinetic Study of Anisole Upgrading Process over Pt/γAl2O3: Model Development and Optimization by Application of Response Surface Methodology and Artificial Neural Network

Chemical Product and Process Modeling ◽

10.1515/cppm-2016-0071 ◽

2017 ◽

Vol 12 (3) ◽

Author(s):

Majid Saidi ◽

Mohammad Ali Roshanfekr Fallah ◽

Nasrin Nemati ◽

Mohammad Reza Rahimpour

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Model Development ◽

Simulated Data ◽

High Accuracy ◽

Coefficient Of Determination ◽

Complex Nature ◽

Conversion Model ◽

Selectivity Model ◽

Artificial Neural

AbstractThe kinetic of catalytic upgrading of anisole as a lignin−derived bio−oil component is investigated experimentally overPt/γAl2O3at 573−673 K and 14 bar. According to experimental results, benzene, phenol, 2−methylphenol, 2,6−dimethylphenol, 2,4,6−trimethylphenol, and hexamethylbenzene are identified as the main products. The results indicated that the kinetically significant reaction classes are hydrogenolysis, hydrodeoxygenation (HDO), alkylation, and hydrogenation. The response surface methodology (RSM) is applied to optimize the experimental data which obtained at suggested conditions by design of experiment (DOE). Due to the complex nature of the system, artificial neural networks (ANNs) were employed as an efficient tool to model the behavior of the system.RSMandANNmethods were constructed based upon theDOE’s points and then utilized for generating extra−simulated data. Data simulated by theRSM/ANNmethod were used to fit power law kinetic rate expressions for the reactions. The coefficient of determination (R2) was obtained 0.998 and 0.973 for anisole conversion model and benzene selectivity model which represented the high accuracy of model predictions. The correlation coefficient (R) and mean square error (MSE) ofANNmodel equaled to 0.97 and 8.3 × 10−12respectively means high accuracy of the developed model. The results of kinetic modeling with simulated data from theANNandRSMmodels revealed that the highest reaction order during the upgrading process of anisole belongs to hydrogenolysis of anisole to phenol. Also the activation energy of hydrogenolysis reaction was lower thanHDO.

Download Full-text

Biodegradation of orange G by a novel isolated bacterial strain Bacillus megaterium ITBHU01 using response surface methodology

AFRICAN JOURNAL OF BIOTECHNOLOGY ◽

10.5897/ajb11.2560 ◽

2012 ◽

Vol 11 (7) ◽

Cited By ~ 11

Author(s):

A. Tripathi

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Bacillus Megaterium ◽

Bacterial Strain ◽

Orange G

Download Full-text

Optimization of Fermentation Conditions and Media for Production of Glucose Isomerase fromBacillus megateriumUsing Response Surface Methodology

Scientifica ◽

10.1155/2018/6842843 ◽

2018 ◽

Vol 2018 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Hoang-Yen Thi Nguyen ◽

Gia-Buu Tran

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Bacillus Megaterium ◽

Large Scale ◽

Glucose Isomerase ◽

Culture Conditions ◽

Inoculum Size ◽

Medium Components ◽

High Fructose ◽

Optimization Of Fermentation

Glucose isomerase is an enzyme widely used in food industry for producing high-fructose corn syrup. Many microbes, includingBacillus megaterium, have been found to be able to produce glucose isomerase. However, the number of studies of glucose isomerase production fromBacillus megateriumis limited. In this study, we establish the optimal medium components and culture conditions forBacillus megateriumglucose isomerase production by evaluating the combined influence of multiple factors and different parameters via Plackett–Burman design and response surface methodology in Modde 5.0 software. The optimized conditions, which were experimentally confirmed as follows: D-xylose (1.116%), K2HPO4(0.2%), MgSO4·7H2O (0.1%), yeast extract (1.161%), peptone (1%), pH 7.0, inoculum size 20% (w/v), shaking 120 rpm at 36.528°C for 48 hours, give rise to production of highest activity of glucose isomerase (0.274 ± 0.003 U/mg biomass). These results provide additional important information for future development of large-scale glucose isomerase production byBacillus megaterium.

Download Full-text