Optimizing Saccharification of Barley Malt by Response Surface Methodology
Naveet R.P. Phutela
Abstract
Open-access reader
Naveet R.P. Phutela
Abstract
Open-access reader
Barley malt has its own saccharifying enzymes whose activity and stability was characterized at varying pH, temperature and substrate concentration. The response surface methodology (RSM) two level full factorial central composite design (CCD) model was employed to optimize the said process parameters which affect the kinetics of the enzyme- catalysed starch hydrolysis. The results predicted by the design were found in good agreement (R2 = 0.9326) with the experimental results indicating the applicability of the model. The multiple regression analysis showed the individual and cumulative effect of pH, temperature and substrate concentration on the enzyme activity indicating that the activity increased with the increase of pH to 5.0 and temperature to 65 C. The RSM was successful in determining the optimum reaction conditions for hydrolysis of barley malt.
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Barley malt has its own saccharifying enzymes whose activity and stability was characterized at varying pH, temperature and substrate concentration. The response surface methodology (RSM) two level full factorial central composite design (CCD) model was employed to optimize the said process parameters which affect the kinetics of the enzyme- catalysed starch hydrolysis. The results predicted by the design were found in good agreement (R2 = 0.9326) with the experimental results indicating the applicability of the model. The multiple regression analysis showed the individual and cumulative effect of pH, temperature and substrate concentration on the enzyme activity indicating that the activity increased with the increase of pH to 5.0 and temperature to 65 C. The RSM was successful in determining the optimum reaction conditions for hydrolysis of barley malt.
Key concepts: Response surface methodology, Central composite design, Factorial experiment, Hydrolysis, Substrate (aquarium), Chemistry, Starch, Fractional factorial design