Modeling and Optimization of L-Asparaginase production from novel Bacillus stratosphericus by soft computing techniques

Order of Publishing in Issue: 
Volume :13
Issue :4
October, 2019 - December, 2019
Page No: 
Madhuri Pola, Chandrasai Potla Durthi, Satish Babu Rajulapati*
Department of Biotechnology, National Institute of Technology Warangal, Telangana, India

Feed forward Artificial Neural Network (ANN) model and global optimization by Genetic Algorithm (GA) were employed on significant variables to enhance the production of LAsparaginase from Bacillus stratosphericus. Using the experimental data, network was built with 4 inputs and 2 outputs along with 10 hidden neurons. Levenberg-Marquardt back propagation algorithm was employed to study the interactions between variables and their influence on LAsparaginase and L-Glutaminase activity. The predicted enzyme activities were compared with the experimental data. The R2 value was found to be 0.99419 from ANN and it was higher compared to Response Surface Methodology (RSM). GA optimization was employed on the quadratic equation obtained from RSM studies to find optimal solution. The optimal concentrations of L-Asparaginase and L-Glutaminase obtained from GA were 29.68 IU/ml and 0.12 IU/ml respectively. The optimal process variables were found to be Incubation time-55h, pH- 6.0 and Temperature- 24°C and L-Asparagine-2.5 g/L.

Artificial Neural Network; Genetic Algorithm; Global optimal solution; RSM; Statistical optimization.
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