Optimization of Growth Conditions for the Production of Bacillus subtilis Using Central Composite Design and Its Antagonism Against Pathogenic Fungi

2022 ◽  
Author(s):  
Meyrem Vehapi ◽  
Benan İnan ◽  
Selma Kayacan-Cakmakoglu ◽  
Osman Sagdic ◽  
Didem Özçimen
Keyword(s):  
Bacillus Subtilis ◽  
Central Composite Design ◽  
Pathogenic Fungi ◽  
Growth Conditions ◽  
Central Composite

Optimization of fibrinolytic enzyme production by newly isolated Bacillus subtilis Egy using central composite design

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 ◽  
...  
Keyword(s):  
Bacillus Subtilis ◽  
Central Composite Design ◽  
Enzyme Production ◽  
Fibrinolytic Enzyme ◽  
Central Composite

scholarly journals OPTIMASI PERMUKAAN RESPON MEDIUM FERMENTASI Streptomyces prasinopilosus SEBAGAI ANTIFUNGI TERHADAP PATOGEN Ganoderma boninense

2019 ◽  
Vol 6 (2) ◽  
pp. 164
Author(s):  
Rofiq Sunaryanto ◽  
Diana Nurani
Keyword(s):  
Central Composite Design ◽  
Yeast Extract ◽  
Active Compound ◽  
Carbon Sources ◽  
Pathogenic Fungi ◽  
Medium Composition ◽  
Quadratic Model ◽  
Active Compounds ◽  
Area Unit ◽  
Central Composite

Response Surface Optimization of Medium Fermentation for Streptomyces prasinopilosus as An Antifungal against Ganoderma boninenseGanoderma boninense is one of the pathogenic fungi that cause basal stem rot (BPB) on oil palm plants. This research aims to study the effect of carbon sources, nitrogen sources, and minerals on the production of Streptomyces prasinopilosus active compounds. Lactose, yeast extract, and minerals are medium components that show a real influence on the production of S. prasinopilosus active compounds. Optimization of the factors that have significant influence was predicted by the second-order model, statistically through a central composite design (CCD). The highest S. prasinopilosus active compound production, with a medium composition of 44.77 g L-1 lactose, 13.02 g L-1 yeast extract, and 15.95 mL L-1 mineral solution, was predicted by the quadratic model to reach 32269366.338 peak area unit on high-performance liquid chromatography (HPLC). The verification of the mathematical model of the production of the active compounds through experiments in the laboratory was 27,203,907.310 peak area unit. This result was 15.7% lower compared to the result of the quadratic model. Optimization increased S. prasinopilosus active compound 9-fold compared to that before optimization.Keywords: active compound; G. boninense; optimization; RSM; S. prasinopilosus ABSTRAKGanoderma boninense merupakan salah satu jamur patogen yang menyebabkan penyakit busuk pangkal batang atau biasa disebut BPB pada tanaman kelapa sawit. Penelitian bertujuan mempelajari pengaruh sumber karbon, sumber nitrogen, dan mineral terhadap produksi senyawa aktif S. prasinopilosus. Laktosa, yeast extract, dan mineral adalah komponen medium yang menunjukkan pengaruh nyata terhadap produksi senyawa aktif S. prasinopilosus. Optimasi terhadap faktor yang berpengaruh nyata diprediksi dengan model orde dua melalui rancangan statistis central composite design (CCD). Produksi senyawa aktif S. prasinopilosus tertinggi diprediksi oleh model kuadratik mencapai 32269366,338 luasan puncak kromatografi cair kinerja tinggi (KCKT) dengan komposisi medium laktosa 44,77 g L-1, yeast extract 13,02 g L-1, dan larutan mineral 15,95 mL L-1. Verifikasi model matematis produksi senyawa aktif yang dihasilkan melalui percobaan di laboratorium adalah sebesar 27.203.907,310 luasan puncak kromatogram KCKT. Hasil ini lebih rendah 15,7% dibandingkan dengan model kuadratik hasil optimasi. Optimasi meningkatkan senyawa aktif S. prasinopilosus 9 kali lipat dibandingkan sebelum optimasi.

Optimizing of pharmaceutical active compounds biodegradability in secondary effluents by β-lactamase from Bacillus subtilis using central composite design

2019 ◽  
Vol 365 ◽  
pp. 883-894 ◽  
Author(s):  
Adel Al-Gheethi ◽  
Efaq Noman ◽  
Radin Maya Saphira Radin Mohamed ◽  
Norli Ismail ◽  
Abd Halid Bin Abdullah ◽  
...  
Keyword(s):  
Bacillus Subtilis ◽  
Central Composite Design ◽  
Active Compounds ◽  
Secondary Effluents ◽  
Central Composite

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
Keyword(s):  
Bacillus Subtilis ◽  
Central Composite Design ◽  
Protease Production ◽  
Central Composite

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

2010 ◽  
Vol 6 (4) ◽  
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 (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.

Development and optimization of solid lipid nanoparticles of amikacin by central composite design

2009 ◽  
Vol 00 (00) ◽  
pp. 090721051030036-8
Author(s):  
Jaleh Varshosaz ◽  
Solmaz Ghaffari ◽  
Mohammad Reza Khoshayand ◽  
Fatemeh Atyabi ◽  
Shirzad Azarmi ◽  
...  
Keyword(s):  
Central Composite Design ◽  
Solid Lipid Nanoparticles ◽  
Lipid Nanoparticles ◽  
Solid Lipid ◽  
Central Composite
Sign in / Sign up

Export Citation Format

Share Document