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dc.contributor.authorNur Zayana Shazlin, Zaidi
dc.contributorFaculty of Engineering Technologyen_US
dc.date2023-03
dc.date.accessioned2025-02-28T05:46:11Z
dc.date.available2025-02-28T05:46:11Z
dc.date.issued2017-12
dc.identifier.urihttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/82820
dc.descriptionAccess is limited to UniMAP community.en_US
dc.description.abstractBanana peel is one of the potential biomass that contains high amount of cellulose and suitable for the production of biofuel. However, banana peel must first undergoes pretreatment process in order to obtain high yield of cellulose. Optimization of alkaline pre treatment condition for cellulose production of banana peel was performed by first characterized the surface structure of dried banana peel before and after pre treatment by using Scanning Electron Microscopy (SEM) followed by screening the condition using One-Single Factor-at-Time (OFAT) approach and lastly optimization using Response Surface Methodology (RSM) and Central Composite Design (CCD). The cellulose concentration was measured by using anthrone reagent. Based on the OFAT experiment, the range of optimum parameter to obtain higher cellulose production was found to be from 2.0 M to 3.0 M NaOH concentration, 65 oC to 75 oC of temperature and 150 minutes to 210 minutes time of reaction and these condition was proceed for optimization study by RSM and CCD. The optimize cellulose concentration obtained was 3.48 mg/mL with condition of 2.5 M NaOH concentration at 70 oC temperature with 180 minutes reaction time. The Analysis of Variance (ANOVA) test showed that the regression model generated was significant.en_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Perlis (UniMAP)en_US
dc.subject.otherBanana peelen_US
dc.subject.otherCelluloseen_US
dc.subject.otherCellulose productionen_US
dc.subject.otherAlkaline pre treatmenten_US
dc.subject.otherBiomassen_US
dc.titleOptimization of alkaline pre treatment of Banana peel for cellulose productionen_US
dc.typeOtheren_US
dc.contributor.advisorNur Zatul 'Iffah Zakaria


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