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Appl. Sci. 2018, 8(12), 2602; https://doi.org/10.3390/app8122602

Prediction of Douglas-Fir Lumber Properties: Comparison between a Benchtop Near-Infrared Spectrometer and Hyperspectral Imaging System

1
Wood Science and Engineering, Oregon State University, Corvallis, OR 97331, USA
2
Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA 30602, USA
3
Agricultural Research Service, United States Department of Agriculture, Athens, GA 30605, USA
4
Benchmark International, Eugene, OR 97402, USA
*
Author to whom correspondence should be addressed.
Received: 16 November 2018 / Revised: 5 December 2018 / Accepted: 10 December 2018 / Published: 13 December 2018
(This article belongs to the Special Issue Application of Hyperspectral Imaging for Nondestructive Measurement)
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Abstract

Near-infrared (NIR) spectroscopy and NIR hyperspectral imaging (NIR-HSI) were compared for the rapid estimation of physical and mechanical properties of No. 2 visual grade 2 × 4 (38.1 mm by 88.9 mm) Douglas-fir structural lumber. In total, 390 lumber samples were acquired from four mills in North America and destructively tested through bending. From each piece of lumber, a 25-mm length block was cut to collect diffuse reflectance NIR spectra and hyperspectral images. Calibrations for the specific gravity (SG) of both the lumber (SGlumber) and 25-mm block (SGblock) and the lumber modulus of elasticity (MOE) and modulus of rupture (MOR) were created using partial least squares (PLS) regression and their performance checked with a prediction set. The strongest calibrations were based on NIR spectra; however, the NIR-HSI data provided stronger predictions for all properties. In terms of fit statistics, SGblock gave the best results, followed by SGlumber, MOE, and MOR. The NIR-HSI SGlumber, MOE, and MOR calibrations were used to predict these properties for each pixel across the transverse surface of the scanned samples, allowing SG, MOE, and MOR variation within and among rings to be observed. View Full-Text
Keywords: bending stiffness; bending strength; NIR; nondestructive testing; Pseudotsuga menziesii; wood and fiber quality bending stiffness; bending strength; NIR; nondestructive testing; Pseudotsuga menziesii; wood and fiber quality
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Schimleck, L.; Dahlen, J.; Yoon, S.-C.; Lawrence, K.C.; Jones, P.D. Prediction of Douglas-Fir Lumber Properties: Comparison between a Benchtop Near-Infrared Spectrometer and Hyperspectral Imaging System. Appl. Sci. 2018, 8, 2602.

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