Protein Enrichment of Sweet Potato Beverage Residues Mixed with Peanut Shells by Aspergillus oryzae and Bacillus subtilis Using Central Composite Design

The preparation of sweet potato distarch phosphates which possess low digestibility was optimized in this study. A central composite design of response surface methodology involving STMP concentration, pH, phosphorylation temperature and time was used, and second-order model for starch digestibility was employed to generate the response surface. The optimum condition for preparation of sweet potato distarch phosphates was as follows: STMP concentration 3%, pH 10, phosphorylation temperature 40°C, and phosphorylation time 3h. The starch digestibility of sweet potato distarch phosphates was yield of 0.5508±0.0003 (n=3) under these conditions.

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

Biocatalysis and Agricultural Biotechnology ◽

10.1016/j.bcab.2015.05.002 ◽

2015 ◽

Vol 4 (3) ◽

pp. 349-354 ◽

Cited By ~ 10

Author(s):

Moein Esmaeili ◽

Mahmoud Yolmeh ◽

Ahmad Shakerardakani ◽

Hamid Golivari

Keyword(s):

Bacillus Subtilis ◽

Central Composite Design ◽

Protease Production ◽

Central Composite

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Optimizing of Microcystis aeruginosa inactivation in freshwater using algicidal Bacillus subtilis by central composite design

10.5004/dwt.2020.25117 ◽

2020 ◽

Vol 181 ◽

pp. 228-238

Author(s):

Ahmed A. Al-Hakimi ◽

Fahad Alminderej ◽

Efaq Noman

Keyword(s):

Bacillus Subtilis ◽

Central Composite Design ◽

Microcystis Aeruginosa ◽

Central Composite

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AMEDMENT STABLE KOJIC ACID PRODUCED BY NON-TOXINOGENIC ASPERGILLUS ORYZAE USING FIVE LEVELS CENTRAL COMPOSITE DESIGN OF RESPONSE SURFACE METHODOLOGY

Journal of Microbiology Biotechnology and Food Sciences ◽

10.15414/jmbfs.2683 ◽

2021 ◽

Vol 10 ◽

Author(s):

Ghada Abd-Elmonsef Mahmoud

Keyword(s):

Response Surface Methodology ◽

Central Composite Design ◽

Response Surface ◽

Aspergillus Oryzae ◽

Kojic Acid ◽

Central Composite

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

International Journal of Food Engineering ◽

10.2202/1556-3758.1980 ◽

2010 ◽

Vol 6 (4) ◽

Cited By ~ 2

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 (TOMLABs Direct AlogoritmgblSolve) 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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