Correlation between hydrolysis rate constant and chemical composition of energy crops

Vasilis Dandikas, Hauke Heuwinkel, Fabian Lichti, Thomas Eckl, Jörg E. Drewes and Konrad Koch

Renewable Energy, 2018, vol. 118, issue C, 34-42

Abstract: Besides biogas yield, the kinetic of biogas production in a biomethane potential (BMP) test also provides important information for feedstock characterization. In this study, fodder analysis and BMP tests with high temporal resolution were performed in order to identify statistical correlations between the hydrolysis rate constant (kh) and the chemical composition of various energy crops. Different species and cultivars of energy crops were analyzed in order to develop a broadly applicable regression model for the prediction of kh. Two independent datasets (222 samples in total) were used, one for the calibration of the model and one for its validation. The results indicated that the analytical parameters non-fiber carbohydrates and crude protein were statistically suitable for a multiple linear regression model for the prediction of kh. Furthermore, a first-order kinetic model and the proposed regression models can be utilized for the prediction of the biogas production in a BMP test. The proposed approach offers a fast and reliable prediction of the biogas production rate and allows a feedstock assessment according to their biogas potential.

Keywords: Biogas potential; Hydrolysis rate constant; Kinetic model; Lignocellulosic biomass; Linear regression (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148117310686
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:118:y:2018:i:c:p:34-42

DOI: 10.1016/j.renene.2017.10.100

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().