Factors Affecting Enzymatic Hydrolysis from Pretreated Fibre Pressed Oil Palm Frond Using Sacchariseb C6

In this study, fibre pressed oil palm frond (FPOPF) was introduced as the raw material for the production of glucose using Sacchariseb C6 to maximise the utilisation of oil palm waste. Sacchariseb C6 is a commercial cellulase blended enzyme from Advanced Enzymes Technology. In order to achieve maxim...

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Main Authors: Fatin Syazwana, Hashim, Wan Mohd Hafizuddin, Wan Yussof, Mah, Kah Hong, Nurul Fatihah, Mahamad Roli, Syed Mohd Saufi, Tuan Chik, Mazrul Nizam, Abu Seman, Abdul Wahab, Mohammad
格式: Article
語言:English
出版: Penerbit Universiti Sains Malaysia 2017
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在線閱讀:http://umpir.ump.edu.my/id/eprint/17499/1/fkksa-2017-hafizuddin-Factors%20Affecting%20Enzymatic%20Hydrolysis%20from%20Pretreated.pdf
http://umpir.ump.edu.my/id/eprint/17499/
https://doi.org/10.21315/jps2017.28.s1.19
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總結:In this study, fibre pressed oil palm frond (FPOPF) was introduced as the raw material for the production of glucose using Sacchariseb C6 to maximise the utilisation of oil palm waste. Sacchariseb C6 is a commercial cellulase blended enzyme from Advanced Enzymes Technology. In order to achieve maximum glucose production, a factorial analysis 25–1 using response surface methodology (RSM) was employed to screen the best enzymatic hydrolysis condition by varying the parameters such as agitation speed, enzyme loading, glucan loading, temperature and hydrolysis time. FPOPF was treated with 4.42% (w/v) of sodium hydroxide at 100°C prior to the enzymatic hydrolysis. Raw FPOPF consists of 40.7% glucan, 26.1% xylan, 26.2% lignin, 1.8% ash and 4.5% extractives. On the other hand, pretreated FPOPF consists of 61.4% glucan, 20.4% xylan, 13.3% lignin, 1.3% ash and 0.3% extractives. From this study, it was found that the best enzymatic hydrolysis condition yielded 33.01 ± 0.73 g/L of glucose when performed at 200 rpm of agitation speed, 60 FPU/mL of enzyme loading, 4% (w/w) of glucan loading, temperature at 55°C and 72 h of reaction time. The model obtained from RSM was significant with p-value <0.0001. It is suggested that this model had a maximum point which is likely to be the optimum point and possible for the optimisation process.