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 .

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Abstract

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

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