Amylases are enzymes which assist hydrolysis (to break down carbohydrates and starches into sugar). These are the most vital enzymes which are being utilized in biotechnology. Various sources (plants, animals and microorganisms) are present to obtain amylases but; the microbial amylases are the extensively used enzymes in food, biofuels and detergents industries. Natural fermented media (foods, soils and wastes) provides a foundation to isolate many microorganism strains producing amylases1.
Usually, two techniques (classical and statistical methods) are being utilized for optimization. Classical method provides mostly unreliable outcomes because interactions between the factors can’t be investigated2. Whereas, the statistical method (response surface methodology) can overcome the limitations of the classical method and uses the data from a few sets of experiments to evaluate equations. This technique has already been efficiently applied during optimization of different media and culture conditions for the production of microbial metabolites including the improvement of biomass production and glucoamylase activity by Candida famata3 and in the optimization of α-amylase production by Aspergillus niger4 and by Aspergillus oryzae5.
Lagzouli Mohamed and colleagues conducted an experiment to assess optimum conditions for growth and glucoamylase (crucial enzyme in biotechnology) production by Candida guilliermondii and to developing cost effective medium by applying Box-Behnken design with one central point and response surface methodology. Scientists used Box-Behnken factorial design based on three levels to attain better medium combination of five independent variables such as initial pH, soluble starch, CH4N2O, yeast extract and MgSO4. They incubated 41 randomized mediums in flask on a rotary shaker at 105 rpm for 72 hours at 30°C.
Scientists noted that production of biomass depends on pH and starch. While, maximum production was observed at starch concentration (8 g L–1) and at initial pH 6. Whereas; glucoamylase exhibited highest production at 6.5 of initial pH, 4 g L–1 yeast extract and 6 g L–1 starch, but yeast extract and urea were interacted negatively showing lofty significance, Box-Behnken factorial design exhibited a second-order polynomial regression model with R2 = 0.976 for Biomass and R2 = 0.981 for glucoamylase.
Conclusively, the final biomass and glucoamylase activity was very close to the calculated parameters according to the p-values (p<0.001) as well as the predicted optimal parameters were confirmed. This investigation encourages further researches regarding baking additives and in the assessment of starch waste products.
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17 November, 2019