Optimization of process parameters for alpha-amylase production using Artificial Neural Network (ANN) on agricultural wastes

Order of Publishing in Issue: 
Volume :10
Issue :3
July, 2016
Page No: 
Santosh Kumar Mishra[a]
Shashi Kumar[b]
Surendra Kumar[c]
Ravi Kant Singh[d]
[a]Department of Biotechnology, IMS Engineering College, Ghaziabad, UP, India
[b,c]Chemical Engineering Department, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India
[d]*Department of Biotechnology, Noida Institute of Engineering & Technology, Gr. Noida, UP, India

Studies of α-amylase production using different solid substrates of wheat bran (WB), rice bran (RB) and mustard oil cake (MOC) were carried out using solid state fermentation (SSF) by Gliomastix indicus. All the substrate supported microbial growth and enzyme production by this microbial culture. However MOC was found best suited solid substrate for maximum production of á-amylase. MOC was further used as a solid substrate for the study of individual and combined effect of moisture content, incubation temperature, pH, incubation time, salt concentration, and choice of nitrogen source on the production of α-amylase. The Artificial Neural Network (ANN) based model was developed to optimize the process parameters and to correlate the effects of different parameters on a-amylase production. The maximum activity of α-amylase was observed 1785.71U/g with MOC as solid substrate in optimized conditions. Partial purification of crude enzyme sample was carried out using ammonium sulfate precipitation followed by size exclusion chromatography (SEC). The appearance of a single band in SDSPAGE has shown the presence of α-amylase enzyme having molecular weight ~56kDa. The specific activity of purified enzyme has been observed 6.11U/mg.

Keywords: Gliomistix indicus, Solid State Fermentation, Artificial Neural Network, Process Optimization, SDS-PAGE, Molecular Weight.

Gliomistix indicus, Solid State Fermentation, Artificial Neural Network, Process Optimization, SDS-PAGE, Molecular Weight
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