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dc.contributor.authorNoor Hafizah, Mukhlis
dc.date.accessioned2013-08-22T01:59:31Z
dc.date.available2013-08-22T01:59:31Z
dc.date.issued2012-06
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/27525
dc.descriptionAccess is limited to UniMAP community.en_US
dc.description.abstractThe first objective for this project is to study the profiling yeast by drawn the yeast growth profile. Then the second is to optimize the critical parameters in order to get high yield of bioethanol production. The production of bioethanol was produce from rice husk. The rice husk was done physical pretreatment by using grinder and molecular sieve. Then, the rice husk undergoes alkali pretreatment to remove the lignin. The lignin removal for the 250 μm of size is the highest compared to size of 750 μm and 500 μm which is 8.97 %. After that, the treated rice husk was goes enzymatic hydrolysis by using cellulase enzyme. Production of glucose from enzymatic hydrolysis produced 4.54 mg/mL of glucose. The glucose produces from enzymatic hydrolysis was further used in fermentation process. The critical parameters which are initial pH, substrate concentration and agitation speed were optimized by using Design of Expert (DOE) software with coupled Response Surface Methodology (RSM). The experiment plan was based on Central Composite Design (CCD) with 20 runs that have 6 central point. Based on the software, there found that 20 runs with different condition is the solution to achieved the high yield of bioethanol. It is found that, the optimum pH, substrate concentration, and agitation speed that produce the maximum bioethanol concentration are 3.54, 10% and 146.7 rpm respectively. The maximum bioethanol concentration obtained from the experiment is 9.347 mg/L which is slightly similar to the value predicted.en_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Perlis (UniMAP)en_US
dc.subjectBioethanolen_US
dc.subjectRice husken_US
dc.subjectYeasten_US
dc.subjectBiofuelen_US
dc.titleOptimization of Bioethanol from Rice Husken_US
dc.typeLearning Objecten_US
dc.contributor.advisorSaleha Shamsudinen_US
dc.publisher.departmentSchool of Bioprocess Engineeringen_US


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