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Soft Independent Modelling of Class Analogy applied to infrared spectroscopy for rapid discrimination between hardwood and softwood

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  • Duca, D.
  • Mancini, M.
  • Rossini, G.
  • Mengarelli, C.
  • Foppa Pedretti, E.
  • Toscano, G.
  • Pizzi, A.

Abstract

European policy promotes renewable energies and sets specific targets. Solid biofuels can play a significant role and the quality is an important aspect to be checked. Quality parameters such as origin and source are also required by specific biofuel standards. Therefore it could be useful to develop a rapid and cheap tool to distinguish between hardwoods and softwoods especially in unstructured, milled or densified wood in order to check the compliance of producer's declarations. Compared to other analytical methods, infrared spectroscopy is fast, non-destructive and low cost. In this study Fourier transform infrared (FTIR) spectroscopy coupled with Soft Independent Modelling of Class Analogy (SIMCA) has been evaluated as a method for discrimination purpose. A large dataset of 110 wood samples belonging to 12 species were analysed. In addition 4 blends were also analysed to test the discrimination performance of the tool. FTIR-SIMCA has correctly classified 93% of hardwood samples and 100% of softwood samples at high significance level. Furthermore, 100% of tested blends were associated with no class, showing a discrimination ability of the technique in recognizing blends from pure material. This method could be useful to verify the compliance of producer declarations about wood origin and source.

Suggested Citation

  • Duca, D. & Mancini, M. & Rossini, G. & Mengarelli, C. & Foppa Pedretti, E. & Toscano, G. & Pizzi, A., 2016. "Soft Independent Modelling of Class Analogy applied to infrared spectroscopy for rapid discrimination between hardwood and softwood," Energy, Elsevier, vol. 117(P1), pages 251-258.
    • Handle: RePEc:eee:energy:v:117:y:2016:i:p1:p:251-258
    DOI: 10.1016/j.energy.2016.10.092
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    References listed on IDEAS

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    1. Gillespie, Gary D. & Everard, Colm D. & McDonnell, Kevin P., 2015. "Prediction of biomass pellet quality indices using near infrared spectroscopy," Energy, Elsevier, vol. 80(C), pages 582-588.
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    1. Elena Leoni & Thomas Gasperini & Nicolò Di Marzio & Rodolfo Picchio & Giuseppe Toscano & Daniele Duca, 2024. "Application of Near Infrared Spectroscopy for the Detection of Chemically Treated Pellets Unsuitable for Combustion," Energies, MDPI, vol. 17(4), pages 1-16, February.

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