Abstract
Bioemulsifier and exopolysaccharides are two of the important biomolecules produced as secondary metabolites by many microorganisms. Bioemulsifiers emulsify hydrophobic substrates allowing their consumption by microorganisms whereas exopolysaccharides provide structural scaffold for the microorganisms to attach to any surface for biofilm formation. Both of these biomolecules have various applications in pharmaceutical and biomedical sectors and hence their production with high yield becomes important. A thermophilic bacterium, Brevibacillus borstelensis, has shown to produce bioemulsifier and exopolysaccharides simultaneously with limited yields. Central composite design-response surface methodology was employed as experimental design strategy to maximize the yields of both of these products with concentrations of glucose, monosodium glutamate, yeast extract and magnesium sulphate in the medium as process variables. The concentration of bioemulsifiers, exopolysaccharides and biomass were chosen as responses of the study. A set of 30 experiments were performed as a part of optimization study with 24 runs as non-centre points and 6 runs as centre points. The model obtained from central composite design was further optimized by genetic algorithm and naïve sorted genetic algorithm. The best results obtained from the three modelling and optimization tools were compared and the models were validated.
Tuning the parameters of an artificial neural network using central composite design and genetic algorithm