New insights on the estimation of the anaerobic biodegradability of plant material

Identifying valuable plants for sustainable energy production

Journal Article (2020)
Author(s)

Claudia Pabon-Pereira (Wageningen University & Research, Universidad Adolfo Ibáñez)

H. V.M. Hamelers (Wageningen University & Research, Wetsus, European Centre of Excellence for Sustainable Water Technology)

Irene Matilla (Wageningen University & Research)

J. B. van Lier (TU Delft - Sanitary Engineering, Wageningen University & Research)

Research Group
Sanitary Engineering
Copyright
© 2020 Claudia P. Pabón-Pereira, H. V.M. Hamelers, Irene Matilla, J.B. van Lier
DOI related publication
https://doi.org/10.3390/pr8070806
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Claudia P. Pabón-Pereira, H. V.M. Hamelers, Irene Matilla, J.B. van Lier
Research Group
Sanitary Engineering
Issue number
7
Volume number
8
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Abstract

Based on fifteen European plant species, a statistical model for the estimation of the anaerobic biodegradability of plant material was developed. We show that this new approach represents an accurate and cost-eective method to identify valuable energy plants for sustainable energy production. In particular, anaerobic biodegradability (Bo) of lignocellulosic material was empirically found to be related to the amount of cellulose plus lignin, as analytically assessed by the van Soest method, i.e., the acid detergent fiber (ADF) value. Apart from being theoretically meaningful, the ADF-based empirical model requires the least eort compared to the other four proposed conceptual models proposed, as individual fractions of cellulose, hemicellulose, and lignin do not need to be assessed, which also enhances the predictive accuracy of the model's estimation. The model's results showed great predictability power, allowing us to identify interesting crops for sustainable crop rotations. Finally, the model was used to predict Bo of 114 European plant samples that had been previously characterized by means of the van Soest method.