Bioethanol production from the plant Impatiens tinctoria A. Rich. tuber by using Saccharomyces cerevisiae fermentation method

A Community-Based Cross-Sectional Study

Authors

  • Birhanu Ayalew Tebeje University of Gondar
  • Ayalew Temesgen University of Gondar
  • Getnet Masresha University of Gondar
  • Mulugeta Legesse University of Gondar
  • Zemenay Zewdu University of Gondar

DOI:

https://doi.org/10.20372/ejncs.v3i2.782

Keywords:

bioethanol, fermentation, lignocellulosic, Impatiens tinctoria, Saccharomyces cerevisiae,

Abstract

The possibility of using bioethanol as an alternative fuel has piqued the interest of biotechnological ethanol production. It's critical to look into the possibilities of using new energy sources that are efficient like oil and that could be utilized instead of or in addition to present fuels and the bioethanol potential from the cellulosic material obtained from the plant Impatiens tinctoria A. Rich. tuber was investigated. For the plant I. tinctoria tuber, the impacts of several parameters that determine the concentration of bioethanol were examined. Pre-treated lignocellulosic material was treated with 2% diluted H2SO4 at 350°C, resulting in a 76.73% w/w carbohydrate concentration. The carbohydrate concentrations were determined by the phenolsulfuric acid method. The optimized sample was fermented at a pH of 6.0, a reaction temperature of 32.5°C, and a fermentation time of 4 days, yielding a maximum ethanol level of 10.38% v/v as measured by Pycnometer. Under optimum conditions, I. tinctoria produced a very promising amount of bioethanol (10.38%), which suggests that it might be used as a lignocellulosic feedstock for bioethanol production instead of food crops.

Published

2023-08-20

How to Cite

Birhanu Ayalew Tebeje, Ayalew Temesgen, Getnet Masresha, Mulugeta Legesse and Zemenay Zewdu (2023) “Bioethanol production from the plant Impatiens tinctoria A. Rich. tuber by using Saccharomyces cerevisiae fermentation method: A Community-Based Cross-Sectional Study”, Ethiopian Journal of Natural and Computational Sciences , 3(2), pp. 483–491. doi: 10.20372/ejncs.v3i2.782.