Statistical Optimization of α-Galactosidase Production in Submerged Fermentation by Streptomyces griseoloalbus Using Response Surface Methodology

α-Galactosidase production by a novel actinomycete strain Streptomyces griseoloalbus in shake flask culture was optimized using response surface methodology. Screening of variables to find their relative effect on α-galactosidase production was done using Plackett-Burman design. Out of the eleven fa...

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Main Authors: Grace Sathyanesan Anisha, Rajeev Kumar Sukumaran, Parukuttyamma Prema
Format: Article
Language:English
Published: University of Zagreb 2008-01-01
Series:Food Technology and Biotechnology
Subjects:
Online Access:http://hrcak.srce.hr/file/38469
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spelling doaj-e14da1475a164b2888f266cbdbb6b2812020-11-25T02:21:02ZengUniversity of ZagrebFood Technology and Biotechnology1330-98621334-26062008-01-01462171177Statistical Optimization of α-Galactosidase Production in Submerged Fermentation by Streptomyces griseoloalbus Using Response Surface MethodologyGrace Sathyanesan Anisha0Rajeev Kumar Sukumaran1Parukuttyamma Prema2Biotechnology Division, National Institute for Interdisciplinary Science and Technology, IN-695 019 Trivandrum, IndiaBiotechnology Division, National Institute for Interdisciplinary Science and Technology, IN-695 019 Trivandrum, IndiaBiotechnology Division, National Institute for Interdisciplinary Science and Technology, IN-695 019 Trivandrum, Indiaα-Galactosidase production by a novel actinomycete strain Streptomyces griseoloalbus in shake flask culture was optimized using response surface methodology. Screening of variables to find their relative effect on α-galactosidase production was done using Plackett-Burman design. Out of the eleven factors screened, salinity, magnesium sulphate and temperature were found to influence the enzyme production significantly. The optimal levels of these variables and the effect of their mutual interactions on enzyme production were determined using Box-Behnken design. The interaction between salinity and magnesium sulphate concentration was found to enhance α-galactosidase production, whereas temperature exhibited an influence independent of the other two factors. Using this statistical optimization method, the α-galactosidase production was increased from 17 to 50 U/mL.http://hrcak.srce.hr/file/38469α-galactosidaseresponse surface methodologyStreptomyces griseoloalbussubmerged fermentation
collection DOAJ
language English
format Article
sources DOAJ
author Grace Sathyanesan Anisha
Rajeev Kumar Sukumaran
Parukuttyamma Prema
spellingShingle Grace Sathyanesan Anisha
Rajeev Kumar Sukumaran
Parukuttyamma Prema
Statistical Optimization of α-Galactosidase Production in Submerged Fermentation by Streptomyces griseoloalbus Using Response Surface Methodology
Food Technology and Biotechnology
α-galactosidase
response surface methodology
Streptomyces griseoloalbus
submerged fermentation
author_facet Grace Sathyanesan Anisha
Rajeev Kumar Sukumaran
Parukuttyamma Prema
author_sort Grace Sathyanesan Anisha
title Statistical Optimization of α-Galactosidase Production in Submerged Fermentation by Streptomyces griseoloalbus Using Response Surface Methodology
title_short Statistical Optimization of α-Galactosidase Production in Submerged Fermentation by Streptomyces griseoloalbus Using Response Surface Methodology
title_full Statistical Optimization of α-Galactosidase Production in Submerged Fermentation by Streptomyces griseoloalbus Using Response Surface Methodology
title_fullStr Statistical Optimization of α-Galactosidase Production in Submerged Fermentation by Streptomyces griseoloalbus Using Response Surface Methodology
title_full_unstemmed Statistical Optimization of α-Galactosidase Production in Submerged Fermentation by Streptomyces griseoloalbus Using Response Surface Methodology
title_sort statistical optimization of α-galactosidase production in submerged fermentation by streptomyces griseoloalbus using response surface methodology
publisher University of Zagreb
series Food Technology and Biotechnology
issn 1330-9862
1334-2606
publishDate 2008-01-01
description α-Galactosidase production by a novel actinomycete strain Streptomyces griseoloalbus in shake flask culture was optimized using response surface methodology. Screening of variables to find their relative effect on α-galactosidase production was done using Plackett-Burman design. Out of the eleven factors screened, salinity, magnesium sulphate and temperature were found to influence the enzyme production significantly. The optimal levels of these variables and the effect of their mutual interactions on enzyme production were determined using Box-Behnken design. The interaction between salinity and magnesium sulphate concentration was found to enhance α-galactosidase production, whereas temperature exhibited an influence independent of the other two factors. Using this statistical optimization method, the α-galactosidase production was increased from 17 to 50 U/mL.
topic α-galactosidase
response surface methodology
Streptomyces griseoloalbus
submerged fermentation
url http://hrcak.srce.hr/file/38469
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AT rajeevkumarsukumaran statisticaloptimizationofagalactosidaseproductioninsubmergedfermentationbystreptomycesgriseoloalbususingresponsesurfacemethodology
AT parukuttyammaprema statisticaloptimizationofagalactosidaseproductioninsubmergedfermentationbystreptomycesgriseoloalbususingresponsesurfacemethodology
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