Optimization of reducing sugar production from Manihot glaziovii starch using response surface methodology

Abdi Hanra Sebayang, Masjuki Haji Hassan, Hwai Chyuan Ong, Surya Dharma, Arridina Susan Silitonga, Fitranto Kusumo, Teuku Meurah Indra Mahlia, Aditiya Harjon Bahar

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Abstract

Bioethanol is known as a viable alternative fuel to solve both energy and environmental crises. This study used response surface methodology based on the Box-Behnken experimental design to obtain the optimum conditions for and quality of bioethanol production. Enzymatic hydrolysis optimization was performed with selected hydrolysis parameters, including substrate loading, stroke speed, α-amylase concentration and amyloglucosidase concentration. From the experiment, the resulting optimum conditions are 23.88% (w/v) substrate loading, 109.43 U/g α-amylase concentration, 65.44 U/mL amyloglucosidase concentration and 74.87 rpm stroke speed, which yielded 196.23 g/L reducing sugar. The fermentation process was also carried out, with a production value of 0.45 g ethanol/g reducing sugar, which is equivalent to 88.61% of ethanol yield after fermentation by using Saccharomyces cerevisiae (S. cerevisiae). The physical and chemical properties of the produced ethanol are within the specifications of the ASTM D4806 standard. The good quality of ethanol produced from this study indicates that Manihot glaziovii (M. glaziovii) has great potential as bioethanol feedstock.

Original languageEnglish
Article number35
JournalEnergies
Volume10
Issue number1
DOIs
Publication statusPublished - 01 Jan 2017

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All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology
  • Energy (miscellaneous)
  • Control and Optimization
  • Electrical and Electronic Engineering

Cite this

Sebayang, A. H., Hassan, M. H., Ong, H. C., Dharma, S., Silitonga, A. S., Kusumo, F., Mahlia, T. M. I., & Bahar, A. H. (2017). Optimization of reducing sugar production from Manihot glaziovii starch using response surface methodology. Energies, 10(1), [35]. https://doi.org/10.3390/en10010035