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Statistical media optimization and production of ITS alpha-amylase from Aspergillus oryzae in a bioreactor by Paresh Gigras; Vikram Sahai; Rani Gupta is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

What is Statistical media optimization and production of ITS alpha-amylase from Aspergillus oryzae in a bioreactor about?

The production of an intermediate temperature-stable (ITS) alpha-amylase from Aspergillus oryzae was studied by using a central composite design with three independent variables, viz., starch, yeast extract, and K(2)HPO(4). The model equation provided a suitable model for the response surface for alpha-amylase production, and, from the optimal concentrations of the medium components, a model was predicted, which was then used for enzyme production in a 150-L bioreactor. In the bioreactor studies, the enzyme yields (161 U/ml) were similar to that of the shake flask (133 U/ml); however, the time required for maximum alpha-amylase production in the bioreactor was reduced to 48 h compared with 120 h in shake flask cultures. An increased level of phosphate in the medium and low inoculum size were necessary to control the excessive foaming in the bioreactor; however, control of the pO(2) level and agitation was not mandatory for enzyme production. The peak enzyme production coincided with the increase in pH of the fermentation broth and was maximal when the pH of the system was above 7.5. Thus, in the present study, pH acted as an indicator of the initiation or end of the enzyme synthesi

Who reads Statistical media optimization and production of ITS alpha-amylase from Aspergillus oryzae in a bioreactor?

It is typically read by researchers, students, and practitioners in Biochemistry, Genetics and Molecular Biology.

Author
Paresh Gigras; Vikram Sahai; Rani Gupta
Publisher
Springer; Springer-Verlag; Springer Verlag; Springer Science and Business Media LLC; Springer Nature (ISSN 0343-8651)
Published
2002
Language
EN
Field
Biochemistry, Genetics and Molecular Biology (Life Sciences)

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