A central composite design for the optimizing lipase and protease production from Bacillus subtilis PTCC 1720

2015 ◽  
Vol 4 (3) ◽  
pp. 349-354 ◽  
Author(s):  
Moein Esmaeili ◽  
Mahmoud Yolmeh ◽  
Ahmad Shakerardakani ◽  
Hamid Golivari
2019 ◽  
Vol 17 ◽  
pp. 43-50 ◽  
Author(s):  
Maysa E. Moharam ◽  
Magda A. El-Bendary ◽  
Fawkia El-Beih ◽  
Saadia M. Hassanin Easa ◽  
Mostafa M. Abo Elsoud ◽  
...  

2019 ◽  
Vol 11 (12) ◽  
pp. 6529-6539 ◽  
Author(s):  
Fareeha Nadeem ◽  
Tahir Mehmood ◽  
Muhammad Naveed ◽  
Shazia Shamas ◽  
Tasmia Saman ◽  
...  

2019 ◽  
Vol 365 ◽  
pp. 883-894 ◽  
Author(s):  
Adel Al-Gheethi ◽  
Efaq Noman ◽  
Radin Maya Saphira Radin Mohamed ◽  
Norli Ismail ◽  
Abd Halid Bin Abdullah ◽  
...  

Author(s):  
Mohandas Bhat S ◽  
A. Prabhakar ◽  
Rama Koteswara Rao R ◽  
Madhu G.M ◽  
Rao G. H

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.


2009 ◽  
Vol 00 (00) ◽  
pp. 090721051030036-8
Author(s):  
Jaleh Varshosaz ◽  
Solmaz Ghaffari ◽  
Mohammad Reza Khoshayand ◽  
Fatemeh Atyabi ◽  
Shirzad Azarmi ◽  
...  

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