ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

Statistical clustering of biomass to predict biogas yields

Dhavaleswarapu, RK and Narayana Hoysall, C and Srinivasaiah, D (2023) Statistical clustering of biomass to predict biogas yields. In: Bioresource Technology Reports, 23 .

[img] PDF
bio_tec_rep_23_2023.pdf - Published Version
Restricted to Registered users only

Download (4MB) | Request a copy
Official URL: https://doi.org/10.1016/j.biteb.2023.101557


A priori prediction of biogas yields from the biomass composition is difficult owing to the inter and intra variation in the biomass composition. A statistical clustering based on the composition of the biomass has been attempted in this study. Twenty-five biomass feedstocks were clustered into three groups; group 1, rich in extractives; group 2, having a high concentration of holocellulose and group 3, predominantly lignin-rich feedstock. Based on the clustering, two multiple linear regression equations were obtained. The correlations had an R2 > 0.95, showing a good statistical fit. Concentrations of lignin and extractives (L/E) play an important role in the overall biogas yields. Segregation of biomass based on L/E can be used to differentiate feedstocks for efficient biogas production.

Item Type: Journal Article
Publication: Bioresource Technology Reports
Publisher: Elsevier Ltd
Additional Information: The copyright for this article belongs to the Elsevier Ltd.
Keywords: Biomass composition and biogas; Lignin: extractives; Prediction of biogas yields; Statistical clustering.
Department/Centre: Division of Mechanical Sciences > Centre for Sustainable Technologies (formerly ASTRA)
Date Deposited: 29 Nov 2023 09:13
Last Modified: 29 Nov 2023 09:13
URI: https://eprints.iisc.ac.in/id/eprint/82896

Actions (login required)

View Item View Item