BioEnergy Research

, Volume 9, Issue 2, pp 610–623 | Cite as

Can Biomethane Potential (BMP) Be Predicted from Other Variables Such As Biochemical Composition in Lignocellulosic Biomass and Related Organic Residues?

  • Rémy BayardEmail author
  • Xun Liu
  • Hassen Benbelkacem
  • Pierre Buffiere
  • Rémy Gourdon


The potential of methane production by anaerobic digestion of lignocellulosic biomass depends not only on the availability of the resources in the considered territory, but also on their physico-chemical characteristics. Relevant methods of characterization are, therefore, needed to select and possibly combine the most appropriate biomass substrates in order to optimize energy recovery through anaerobic digestion processes. The objective of the present study was to determine whether biomethane potential of such substrates could be predicted from a limited number of variables more rapidly or determined more easily. A set of 36 biomass substrates and organic residues from a variety of origins was analyzed for total and easily hydrosoluble organic matter fractions (volatile solid, VS and soluble chemical oxygen demand, SCOD), neutral detergent soluble fraction (SOL), hemicelluloses (HEM), cellulose (CELL), and lignin-like residual fractions (RES). Bioreactivity of all samples was also measured by experimental assays (biochemical oxygen demand, BOD and biochemical methane potential, BMP). The whole set of data thereby obtained was analyzed statistically considering one dependent variable (BMP), and six independent variables (SCOD, SOL, HEM, CELL, RES, and BOD). Partial least square (PLS) analysis revealed very clearly a positive correlation between BMP and BOD, which were both anti-correlated with RES. On the other hand, no correlations were observed between BMP, SCOD, HEM, and CELL contents. PLS analysis showed that BMP was significantly correlated to the six independent variables. The most influential variables were found to be RES and BOD, and a polynomial model was successfully validated for the prediction of BMP from RES and BOD.


Biochemical methane potential Biodegradation Anaerobic digestion Biomass Organic waste Lignocellulose Cellulose Lignin Correlation Statistical analysis 



Anaerobic digestion


Bioconversion yield under aerobic condition


Bioconversion yield under anaerobic condition


Biological oxygen demand after 28 days of incubation as mass of oxygen consumed by TS or VS in 28 days of incubation at 30 °C (g kg−1)


Biochemical methane production after 60 days of incubation by VS in 60 days of incubation at 35 °C (L kg−1)


Cellulose-like content from Van Soest sequential extraction by VS (g kg−1)


Cellulose content from NREL extraction procedure by VS (g kg−1)


Total chemical oxygen demand by TS (gO2 kg−1)


Hemicellulose-like content from Van Soest sequential extraction by VS (g kg−1)


Partial least square analysis


Predicted residual sum of squares


Correlation coefficient


Residual lignin-like content from Van Soest sequential extractions by VS (g kg−1)


Residual municipal solid waste


Relative root mean square error


Soluble chemical oxygen demand by VS in leachate collected from leaching test at a L/S ratio of 10 (gO2 kg−1)


Soluble fraction from Van Soest sequential extractions by VS (g kg−1)


Total organic carbon by TS (g kg−1)


Total solid


Variable importance in projection


Volatile solid (g kg−1)


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Rémy Bayard
    • 1
    Email author
  • Xun Liu
    • 1
  • Hassen Benbelkacem
    • 1
  • Pierre Buffiere
    • 1
  • Rémy Gourdon
    • 1
  1. 1.Université de Lyon, INSA Lyon, LGCIE-DEEP, EA4126Villeurbanne cedexFrance

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