scholarly journals OPTIMIZATION OF PROCESS PARAMETERS FOR ENHANCED THERMOSTABLE LIPASE PRODUCTION BY BACILLUS SUBTILIS SHVSC04

2019 ◽  
Vol 7 (11) ◽  
pp. 211-221
Author(s):  
Leena Ambasana ◽  
◽  
Neepa Pandhi ◽  
Keyword(s):  
Bacillus Subtilis ◽  
Process Parameters ◽  
Lipase Production ◽  
Thermostable Lipase ◽  
Optimization Of Process Parameters

Optimization of Process Parameters for Production of Pectinase using Bacillus Subtilis MF447840.1

2019 ◽  
Vol 13 (1) ◽  
pp. 69-73 ◽  
Author(s):  
Ram Balak Mahto ◽  
Mukesh Yadav ◽  
Soumya Sasmal ◽  
Biswnath Bhunia
Keyword(s):  
Bacillus Subtilis ◽  
Process Parameters ◽  
Volume Ratio ◽  
Optimum Process ◽  
Agitation Rate ◽  
Fermentation Condition ◽  
Optimization Of Process Parameters ◽  
Food And Beverage ◽  
Pectinase Production ◽  
Sterile Product

Background: Pectinase enzyme has immense industrial prospects in the food and beverage industries. </P><P> Objective: In our investigation, we find out the optimum process parameters suitable for better pectinase generation by Bacillus subtilis MF447840.1 using submerged fermentation. </P><P> Method: 2% (OD600 nm = 0.2) of pure Bacillus subtilis MF447840.1 bacterial culture was inoculated in sterile product production media. The production media components used for this study were 1 g/l of pectin, 2 g/l of (NH4)2SO4, 1 g/l of NaCl, 0.25 g/l of K2HPO4, 0.25 g/l of KH2PO4 and 1 g/l of MgSO4 for pectinase generation. We reviewed all recent patents on pectinase production and utilization. The various process parameters were observed by changing one variable time method. </P><P> Results: The optimum fermentation condition of different parameters was noticed to be 5% inoculums, 25% volume ratio, temperature (37°C), pH (7.4) and agitation rate (120 rpm) following 4 days incubation. </P><P> Conclusion: Maximum pectinase generation was noticed as 345 ± 12.35 U following 4 days incubation.

Enhancement of Thermostable Lipase Production by a Genotypically Identified Extremophilic Bacillus subtilis NS 8 in a Continuous Bioreactor

2011 ◽  
Vol 20 (2) ◽  
pp. 105-115 ◽  
Author(s):  
Akanbi Taiwo Olusesan ◽  
L. Kamaruzaman Azura ◽  
Fatimah Abubakar ◽  
Abdul Karim Sabo Mohamed ◽  
Son Radu ◽  
...  
Keyword(s):  
Bacillus Subtilis ◽  
Lipase Production ◽  
Thermostable Lipase ◽  
Continuous Bioreactor

Statistical Optimization and Neural Modeling of Amylase Production from Banana Peel Using Bacillus subtilis MTCC 441

2010 ◽  
Vol 6 (4) ◽  
Author(s):  
Mohandas Bhat S ◽  
A. Prabhakar ◽  
Rama Koteswara Rao R ◽  
Madhu G.M ◽  
Rao G. H
Keyword(s):  
Bacillus Subtilis ◽  
Central Composite Design ◽  
Process Parameters ◽  
Fermentation Process ◽  
Optimization Technique ◽  
Inoculum Size ◽  
Banana Peel ◽  
Advantages And Disadvantages ◽  
Optimization Of Process Parameters ◽  
Central Composite

Optimization of process parameters is of critical task in developing an industrial fermentation process for various reasons. Many techniques are available for experimental design and optimization of fermentation process parameters, i.e., fermentation medium composition and conditions, each having its own advantages and disadvantages. In this work response surface methodology (RSM) with central composite design (CCD) of experiments and artificial neural network (ANN) coupled with global optimization technique (TOMLAB’s Direct Alogoritm—gblSolve) are used for optimization of process parameters for the production of alpha amylase using banana peel as the substrate and bacterial source Bacillus subtilis MTCC 441. A 46 run central composite design was used to plan the experiment with six parameters (banana peel concentration, peptone concentration, pH, temperature, incubation time and inoculum size) with five levels. The maximum amylase activity predicted by CCD and ANN is in good agreement with the experimental values at the optimized levels. The present work shows the better optimization and prediction capacity of ANN techniques compared to RSM technique.

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