title: Biochemical methane potential prediction of plant biomasses: Comparing chemical composition versus near infrared methods and linear versus non-linear models.
abstract: The reliability of different models to predict the biochemical methane potential (BMP) of various plant biomasses using a multispecies dataset was compared. The most reliable prediction models of the BMP were those based on the near infrared (NIR) spectrum compared to those based on the chemical composition. The NIR predictions of local (specific regression and non-linear) models were able to estimate quantitatively, rapidly, cheaply and easily the BMP. Such a model could be further used for biomethanation plant management and optimization. The predictions of non-linear models were more reliable compared to those of linear models. The presentation form (green-dried, silage-dried and silage-wet form) of biomasses to the NIR spectrometer did not influence the performances of the NIR prediction models. The accuracy of the BMP method should be improved to enhance further the BMP prediction models.
authors.affiliation: Walloon Agricultural Research Center - CRA-W, Valorisation of Agricultural Products Department - Biomass, Bioproducts and Energy Unit, Chaussée de Namur, 146, B-5030 Gembloux, Belgium. Electronic address: b.godin@cra.wallonie.be.
authors.forename: Bruno
authors.initials: B
authors.lastname: Godin
authors.affiliation: Centre de Recherche Public - Gabriel Lippmann, Environment and Agro-Biotechnologies Department, Rue du Brill, 41, L-4422 Belvaux, Luxembourg; Université catholique de Louvain, Earth & Life Institute - Bioengineering Group, Croix du Sud, 2 Box L7.05.19, B-1348 Louvain-la-Neuve, Belgium.
authors.forename: Frédéric
authors.initials: F
authors.lastname: Mayer
authors.affiliation: Walloon Agricultural Research Center - CRA-W, Valorisation of Agricultural Products Department - Biomass, Bioproducts and Energy Unit, Chaussée de Namur, 146, B-5030 Gembloux, Belgium.
authors.forename: Richard
authors.initials: R
authors.lastname: Agneessens
authors.affiliation: Université catholique de Louvain, Earth & Life Institute - Bioengineering Group, Croix du Sud, 2 Box L7.05.19, B-1348 Louvain-la-Neuve, Belgium.
authors.forename: Patrick
authors.initials: P
authors.lastname: Gerin
authors.affiliation: Walloon Agricultural Research Center - CRA-W, Valorisation of Agricultural Products Department - Biomass, Bioproducts and Energy Unit, Chaussée de Namur, 146, B-5030 Gembloux, Belgium.
authors.forename: Pierre
authors.initials: P
authors.lastname: Dardenne
authors.affiliation: Centre de Recherche Public - Gabriel Lippmann, Environment and Agro-Biotechnologies Department, Rue du Brill, 41, L-4422 Belvaux, Luxembourg.
authors.forename: Philippe
authors.initials: P
authors.lastname: Delfosse
authors.affiliation: Walloon Agricultural Research Center - CRA-W, Valorisation of Agricultural Products Department - Biomass, Bioproducts and Energy Unit, Chaussée de Namur, 146, B-5030 Gembloux, Belgium.
authors.forename: Jérôme
authors.initials: J
authors.lastname: Delcarte
mesh_terms: D018533:Biomass; D016014:Linear Models; D008697:Methane / Q000378:metabolism*; D008962:Models, Theoretical; D017711:Nonlinear Dynamics; D010944:Plants / Q000737:chemistry*; D015203:Reproducibility of Results; D012820:Silage / Q000032:analysis; D019265:Spectroscopy, Near-Infrared
chemical_list: D008697:Methane
keywords: Anaerobic digestion; Biogas; Chemometrics; Multivariate data analysis; Prediction