Near infrared spectroscopy for the discrimination between different residues of the wood processing industry in the pellet sector. (1st April 2018) - Mancini, M.; Rinnan, Å.; Pizzi, A.; Mengarelli, C.; Rossini, G.; Duca, D.; Toscano, G.
Highlights: EN ISO 17, 225-2 requires information about the origin and source of the pellet. Italian national legislation considers wood-based composite materials as waste. Virgin wood and residues of wood processing industry were collected and analysed. FT-NIRS coupled with PLS-DA has been evaluated as a suitable screening tool. Variables selection enhances the classification performance. Abstract: The increasing concern regarding energy supply and the consequent rapid growth of the pellet market lead to the need to classify the product quality. To this aim, chemical-physical parameters and qualitative attributes are defined by the technical standards EN ISO 17, 225 to classify the quality of biofuels, but, while the former can be determined by traditional chemical analysis, no methodologies have been set for the latter one. Hence, near-infrared spectroscopy was tested to obtain information about the origin and the source of the pellet, at the moment only declared by the producers and difficult to be achieved by conventional analysis. In fact, the great strength of the technique is based on the fact that biomass features could be read simultaneously with a rapid and cheap NIR measurement. Checking the presence of treated wood (e.g. residues from wood processing industry) especially in densified products, such as pellets and briquettes, is particular important since in several European countries, e.g. Italy, these materials are considered as waste. In this study more than a hundred samples of virgin and treated wood (residues from wood processing industries) were analysed by means of FT-NIR. Partial Least Square regression – Discriminant Analysis was used in order to classify samples between the two classes and different variables selection methods were tested in order to improve the classification performance of the models. The results obtained demonstrated that near infrared analysis coupled with multivariate analysis can be used in screening applications to classify virgin wood from glue-laminated wood and treated wood. In particular, the model for the discrimination of treated wood (except glue-laminated samples) from virgin wood performs 100% correct classification and the model for the discrimination between virgin wood and glue-laminated wood only has a 3.6% misclassification rate. The methodology can be considered as the first one able to provide information about the origin of the biomass in a rapid and cheap way.