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Near-infrared spectroscopy (NIRS) has the potential to advance the productivity of the forest bio-refinery process by rapid identification of process bio-products, including the liquid extract and woody biomass. The potential exists so that composition identification via NIRS can be performed as an in-line process control operation. Before this technology is applied to the forest bio-refinery process, a NIR spectral database of solid wood chips and liquid extract solutions must be collected, developed and analyzed. Along with spectral data, physical differences of the woody biomass, including surface color, grain size and thickness were considered. The effects of viscosity, the amount of liquid scanned and the type of solvent used in solution were also investigated.

After developing the database of spectra, partial least squares (PLS) techniques were used in combination with selected pretreatments to develop calibration models. The calibration models were tested by scanning actual wood chips and liquid extracts removed during a laboratory-scale bio-refining process.

Wood chip spectra prior to pretreatment showed the most variation within the 1000-1350 nm range. Variation in the liquid extract spectra (high water content) was evident in the same range. Significant differences were seen when a water spectrum was subtracted from the liquid extract spectra. Initial calibrations based on known woody biomass components indicate positive validation results. These outcomes confirm the possibility for identification of extract components via NIRS, leading to the development of techniques that can be further tested in industry.

Keywords: Biofuels, Chemometrics, Data Analysis, Near Infrared

This research was supported by the NSF grants EPS-05-54545 and EEC-0734288.