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World Journal of Engineering Research and Technology

( An ISO 9001:2015 Certified International Journal )

An International Peer Reviewed Journal for Engineering Research and Technology

An Official Publication of Society for Advance Healthcare Research (Reg. No. : 01/01/01/31674/16)

ISSN 2454-695X

Impact Factor : 7.029

ICV : 79.45

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Abstract

OPTIMIZATION OF GUINEA GRASS PRETREATMENT FOR THE PRODUCTION OF BIOETHANOL USING RESPONSE SURFACE METHODOLOGY

Akpali Emmanuel* and Engr. C. O. Okieimen

ABSTRACT

Increasing demand for energy and shortage of energy have been major challenges facing the world. The development of new technologies for producing fuel from renewable sources is a possible solution to the challenges. In this study, we investigated the optimal conditions for pretreating guinea grass (Panicum maximum) used as a feedstock for bioethanol production. Compositional analysis of the sample was performed using the gravimetric method with the following results obtained: 25.8% cellulose, 50.2% hemicellulose, and 24% lignin. The samples were pretreated with a mixed solution of NaOH and H2SO4 at pH = 2–12. The pretreatment was performed at different times, temperatures, and pH values (as designed by design expert 13 software) to assess the optimum point of delignification, meaning the operational conditions that could effectively maximize the enzymatic hydrolysis stage. The reducing sugar yield for each run at different conditions was analyzed using DNS. The optimal yield of the sugar was achieved at a temperature of 120.08? and pH of 2.02 after a pretreatment time of 80.56 min. After the validation of the model with the actual experiment at the same conditions, 1109.25 mg/L of reducing sugar was obtained. The high ????2 values of 0.9986 obtained from the model indicated that the fitted models could predict reasonably precise outcomes. The predicted R² value of 0.9880 was in reasonable agreement with the adjusted R² of 0.9967. Therefore, our findings show that guinea grass meets the requirement as a second-generation bioethanol production feedstock.

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