Comparative study on modeling by neural networks and response surface methodology for better prediction and optimization of fermentation parameters: Application on thermo-alkaline lipase production by Nocardiopsis sp. strain NRC/WN5

2020 ◽  
Vol 25 ◽  
pp. 101619 ◽  
Author(s):  
Mohamed M. Abdel Aziz ◽  
Eman W. Elgammal ◽  
Roba G. Ghitas
Keyword(s):  
Neural Networks ◽  
Response Surface Methodology ◽  
Comparative Study ◽  
Response Surface ◽  
Lipase Production ◽  
Alkaline Lipase ◽  
Fermentation Parameters ◽  
Optimization Of Fermentation

Optimization of fermentation parameters in phage production using response surface methodology

2012 ◽  
Vol 39 (10) ◽  
pp. 1515-1522 ◽  
Author(s):  
Sung-Hye H. Grieco ◽  
Ann Y. K. Wong ◽  
W. Scott Dunbar ◽  
Ross T. A. MacGillivray ◽  
Susan B. Curtis
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Phage Production ◽  
Fermentation Parameters ◽  
Optimization Of Fermentation

scholarly journals Optimization of fermentation conditions for producing Indian rock bee (Apis dorsata) mead using response surface methodology

2014 ◽  
Vol 6 (2) ◽  
pp. 366-370 ◽  
Author(s):  
N. Srimeena ◽  
S. Gunasekaran ◽  
R. Murugesan
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Ethanol Yield ◽  
Soluble Solids ◽  
P Value ◽  
Yeast Saccharomyces Cerevisiae ◽  
Fermentation Time ◽  
Fermentation Parameters ◽  
Optimization Of Fermentation ◽  
Central Composite

Mead is a traditional drink which results from the alcoholic fermentation of diluted honey carried out by yeast (Saccharomyces cerevisiae KF233529). The present investigation was carried out for the optimization of fermentation parameters for maximizing the yield of ethanol. Response Surface Methodology (RSM) based central composite design was employed to obtain best combination of temperature, fermentation time and total soluble solids (TSS). The optimum conditions for ethanol yield were temperature 28°C, TSS 15°Brix and 6 days after fermentation. The model showed that the value of R2 (0.9998) was high and p- value of interaction of variance was <0.0001. Hence the model can be said to be of highly significant.

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