Statistical Optimization of Cellulase and Xylanase Enzyme Production by Penicillium Crustosum Using Sugar Beet Peel Substrate by Response Surface Methodology.

dc.contributor.authorMushimiyimana, Isaie
dc.date.accessioned2018-11-27T13:29:21Z
dc.date.available2018-11-27T13:29:21Z
dc.date.issued2015
dc.descriptionJournal Articleen_US
dc.description.abstractResponse Surface Methodology (RSM) is a powerful and efficient mathematical approach widely applied in the optimization process of selected variables. Cellulase and xylanase enzyme production by Penicillium crustosum using agrowaste substrate (sugar beet peel) was investigated by optimizing various process parameters such as carbon and nitrogen source, pH and inoculum size. In the present study optimization was based on statistical design and employed to enhance the production of cellulase and xylanase enzyme production through submerged fermentation. A fractional factorial design (24 ) was applied to elucidate the process parameters that significantly affect cellulase and xylanase production. Carbon and nitrogen source, pH, inoculum size were identified as important process parameters effecting cellulase and xylanase enzyme production. The optimum yield of cellulase and xylanase activity was (5.56 U/ml), (36.14 U/ml) respectively.en_US
dc.identifier.citationhttps://www.researchgate.net/publication/274562802_Statistical_Optimization_of_Cellulase_and_Xylanase_Enzyme_Production_by_Penicillium_Crustosum_Using_Sugar_Beet_Peel_Substrate_by_Response_Surface_Methodologyen_US
dc.identifier.issn0975-8585
dc.identifier.urihttp://hdl.handle.net/123456789/356
dc.language.isoenen_US
dc.publisherResearch Journal of Pharmaceutical, Biological and Chemical Sciencesen_US
dc.relation.ispartofseries;RJPBCS 6(1)
dc.subjectCellulaseen_US
dc.subjectXylanaseen_US
dc.subjectSugar beet peelen_US
dc.subjectResponse surface methodology (RSM)en_US
dc.titleStatistical Optimization of Cellulase and Xylanase Enzyme Production by Penicillium Crustosum Using Sugar Beet Peel Substrate by Response Surface Methodology.en_US
dc.typeArticleen_US

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