Near Infrared Hyperspectral Imaging Applied to Mapping Chemical Composition in Wood Samples

Abstract

This paper describes a method for the two-dimensional mapping of chemical composition on the transverse face of cross-sectional discs from trees. The method uses an imaging spectrograph coupled to a near infrared (NIR) camera (900–1700 nm) to obtain NIR hyperspectral data sets which are processed using partial least squares regression to visualise the distribution and variation of lignin, galactose and glucose in Pinus radiata discs with R2/standard error of performance values of 0.84/1.48 (lignin), 0.87/0.68 (galactose) and 0.87/0.95 (glucose). The hardware design and software control are described along with a method for calibration based on one dimension spatially resolved predictions of chemical composition from conventional NIR spectroscopy. The NIR imaging system was designed as a rapid and cost-effective means of mapping chemical composition over the entire disc at a spatial resolution of ∼4mm2/pixel. The resulting maps of chemical composition clearly indicate, at high spatial resolution, the extent of heterogeneity that occurs in logs.