Response Surface Methodology: Optimisation of Antifungal Bioemulsifier from NovelBacillus thuringiensis

Abstract

An antifungal bioemulsifier compound was produced from a novel strain of Bacillus thuringiensis pak2310. To accentuate the production and as the first step to improve the yield, a central composite design (CCD) was used to study the effect of various factors like minimal salts (1X and 3X), glycerol concentration (2% and 4%), beef extract concentration (1% and 3%), and sunflower oil concentration (2% and 4%) on the production of bioemulsifier molecule and to optimize the conditions to increase the production. The E 24 emulsification index was used as the response variable as the increase in surfactant production was seen to be proportional to increased emulsification. A quadratic equation was employed to express the response variable in terms of the independent variables. Statistical tools like student's t-test, F-test, and ANOVA were employed to identify the important factors and to test the adequacy of the model. Under optimum conditions (1X concentration of minimal salts (MS), 2.6% glycerol (v/v), 1% beef extract (w/v), and 2% sunflower oil (v/v)) a 65% increase in yield was produced.

Production and statistical optimization of Paromomycin by Streptomyces rimosus NRRL 2455 in solid state fermentation

“…Moreover, ANOVA results revealed that the model term AB was significant, meaning that the interaction between pH and temperature was significant, while the other interaction terms were insignificant. A significant interaction between 2 factors means the effect of one factor is dependent on the level of the other [ 52 ]. Contour plots can reveal the significance of the interaction between two factors: an elliptical contour implies a significant interaction between the two factors, whereas a circular contour implies that the interaction between the two factors is weak [ 49 ].…”

WITHDRAWN: Simultaneous Production of Bioemulsifier and Exopolysaccharides by Thermophilic Brevibacillus Borstelensis Using Response Surface Model, Genetic Algorithm and NSGA

“…A full factorial design (2 4 ) was used to study the interaction of concentrations of urea, corn oil, potassium dihydrogen orthophosphate and ammonium sulphate for bioemulsifier production by Candida lipolytica (Albuquerque et al 2006). A central composite design with five factors were used to obtain an optimum medium for bioemulsifier production by Bacillus thuringiensis pak2310 (Rajendran et al 2014). Apart from optimization of bioemulsifier production, CCD-RSM has also been employed for the production of exopolysaccharide by microorganisms.…”

<p>Optimized Production of the Allylamine Antifungal “Terbinafine” by <em>Lysinibacillus</em> Isolate MK212927 Using Response Surface Methodology</p>

“…A significant interaction between 2 factors means the effect of one factor depends on the level of the other. 41 As shown in the equation representing the model, all factors and interactions had positive synergistic effects on antifungal yield except agitation (E) and the interactions between starch and temperature (AD), ammonium chloride and temperature (BD) and ammonium chloride and agitation (BE), which had negative antagonistic effects on antifungal production. For a better understanding of the variables' effects on the antifungal metabolite production and their interactions, the predicted model was presented as 3D-plots and contour plots.…”