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Open AccessArticle

Chemical and Enzymatic Treatment of Hemp Biomass for Bioethanol Production

Department of Innovative Biomaterials and Nanotechnologies, Institute of Natural Fibres and Medicinal Plants, Wojska Polskiego 71B, 60-630 Poznan, Poland
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Appl. Sci. 2019, 9(24), 5348; https://doi.org/10.3390/app9245348
Received: 10 October 2019 / Revised: 18 November 2019 / Accepted: 3 December 2019 / Published: 6 December 2019
(This article belongs to the Special Issue Cellulose Conversion Technology)
In this study chemical and enzymatic treatment of hemp biomass were optimized to obtain maximum ethanol production. In the first stage, physical and chemical pretreatment of hemp biomass was carried out. It was found that the Tygra variety is susceptible to alkaline treatment at an optimum concentration of 2% NaOH. Next, the effect of NaOH on the value of reducing sugars and the chemical composition of the solid fraction before and after the treatment was determined. Hemp biomass before and after the chemical treatment was analysed by FTIR spectra and SEM. The effect of enzymatic hydrolysis, i.e., substrate content, temperature, time, pH and dose of enzyme by means of Response Surface Methodology on glucose content was determined. The highest glucose value was observed at 50 °C, in time process between 48 and 72 h, and the dose of enzyme was not less than 20 FPU·g−1. After the optimization of enzymatic hydrolysis two processes of ethanol fermentation from hemp biomass, SHF and SSF, were carried out. In the SHF process a 40% higher concentration of ethanol was obtained (10.51 g/L). In conclusion, hemp biomass was found to be an interesting and promising source to be used for bioethanol production. View Full-Text
Keywords: bioethanol; hemp biomass; lignocellulose; pretreatment; enzymatic hydrolysis; ethanol fermentation bioethanol; hemp biomass; lignocellulose; pretreatment; enzymatic hydrolysis; ethanol fermentation
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Wawro, A.; Batog, J.; Gieparda, W. Chemical and Enzymatic Treatment of Hemp Biomass for Bioethanol Production. Appl. Sci. 2019, 9, 5348.

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