Volume 7, Issue 1     January - March, 2019
Research Article
Factors affecting enzymatic hydrolysis of oil palm frond bagasse using cellic HTec2 for xylooligosaccharides production

Anis Surayani Mat Yaacob1, Nurul Aishah Mazlan1, Kamaliah Abdul Samad1, Syed Mohd Saufi1, Hafizuddin Wan Yussof1*, Jamaliah Jahim2

1Faculty of Chemical and Natural Resources Engineering, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300, Gambang, Kuantan, Pahang, Malaysia

2Department of Chemical and Process Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia


Enzymatic hydrolysis has become outstanding technology in converting lignocellulosic biomass to its xylose monomer for xylooligosaccharides (XOS) production. The present work involves an investigation on the effects of enzyme loading, agitation speed, substrate loading, temperature and hydrolysis time on enzymatic hydrolysis for XOS production. Pretreated oil palm frond bagasse by dilute nitric acid was used for enzymatic hydrolysis using Cellic HTec2. The effects of factors were analyzed by half fractional factorial design 25-1 using Design Expert with Response Surface Methodology (RSM) to achieve maximum XOS production. The results revealed that the best enzymatic hydrolysis condition yielded 4.13 mg/L of XOS when conducted at 5% (w/v) of substrate loading, 50 U/mL enzyme loading with 200 rpm agitation speed and 55°C for 4 hours of hydrolysis time.  Two factors that contributed to the highest production of XOS were substrate loading and enzyme loading. The model obtained in this present research is significant with p-value < 0.0001 and R-squared of 0.9545. It is recommended that model had a maximum point which is possible for the optimization process later. Overall, the findings of this study suggest that Cellic HTec2 is a suitable candidate for enzymatic hydrolysis of pretreated OPFB for higher XOS production.

Keywords: Oil palm frond bagasse, Enzymatic hydrolysis, Cellic HTec2, Xylooligosaccharides, Response surface methodology

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