Abstract

The use of near infrared (NIR) hyperspectral imaging for the estimation of basic density (BD) and moisture content (MC) of loblolly pine (Pinus taeda L.) disks is reported. A total of 125 wood disks, ranging in age from 13 years to 19 years, were analysed. Hyperspectral images were collected using an imaging system composed of an InGaAs camera from Sensors Unlimited, Inc. (sensitive between 1000nm and 1700nm at 5nm increments) and a Liquid Crystal Tunable Filter from CRI, Inc., continuously tunable between 1000 nm and 1800 nm. Owing to noise, spectra were truncated to 1005–1645nm and smoothed using a five-point median filter prior to calibration development. Sixteen samples were detected as outliers, reducing the number of disks available for analysis to 109, which were subsequently split into calibration (85) and validation (24) sets. Successful models, based on the hyperspectral data, were obtained for disk basic density (R²_c=0.81) and moisture content (R²_c=0.77). The predictive ability of the calibrations was acceptable, with root mean square errors (RMSEP) of 23.6 kg m⁻³ for BD and 2.1% for MC. The calibrations were compared to those obtained using NIR spectra collected from the surface of the disks using a Foss XDS NIR System coupled with a Smart Probe Analyser using the same wavelength range and number of samples (each disk was represented by an average of eight spectra which had been divided into four quadrants with two spectra collected per quadrant). Probe-based calibrations were more successful; however, the hyperspectral-based calibrations were of sufficient strength to suggest that hyperspectral imaging could be used for the estimation of BD and MC of loblolly pine disks.

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