Non-destructive estimation of Pinus taeda L tracheid morphological characteristics for samples from a wide range of sites in Georgia

Tracheid coarseness, specific surface, wall thickness, perimeter, and radial and tangential diameter from 119 radial strips of Pinus taeda L. (loblolly pine) trees grown on 14 sites in three physiographic regions of Georgia (USA) were measured by SilviScan. NIR spectra were also collected in 10 mm i...

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Veröffentlicht in:Wood science and technology 2005-10, Vol.39 (7), p.529-545, Article 529
Hauptverfasser: Jones, P.D, Schimleck, L.R, Peter, G.F, Daniels, R.F, Clark, A III
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container_end_page 545
container_issue 7
container_start_page 529
container_title Wood science and technology
container_volume 39
creator Jones, P.D
Schimleck, L.R
Peter, G.F
Daniels, R.F
Clark, A III
description Tracheid coarseness, specific surface, wall thickness, perimeter, and radial and tangential diameter from 119 radial strips of Pinus taeda L. (loblolly pine) trees grown on 14 sites in three physiographic regions of Georgia (USA) were measured by SilviScan. NIR spectra were also collected in 10 mm increments from the radial longitudinal surface of each strip and split into calibration (9 sites, 729 spectra) and prediction sets (6 sites, 225 spectra). NIR spectra (untreated and mathematically treated first and second derivative and multiplicative scatter correction) were correlated with tracheid properties to develop calibrations for the estimation of these properties. Strong correlations were obtained for properties related to density, the strongest R ² being 0.80 (coarseness), 0.78 (specific surface) and 0.84 (wall thickness). When applied to the test set, good relationships were obtained for the density-related properties (R p ² ranged from 0.68 to 0.86), but the accuracy of predictions varied depending on math treatment. The addition of a small number of cores from the prediction set (one core per new site) to the calibration set improved the accuracy of predictions and, importantly, minimized the differences obtained with the various math treatments. These results suggest that density related properties can be estimated by NIR with sufficient accuracy to be used in operational settings.
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(loblolly pine) trees grown on 14 sites in three physiographic regions of Georgia (USA) were measured by SilviScan. NIR spectra were also collected in 10 mm increments from the radial longitudinal surface of each strip and split into calibration (9 sites, 729 spectra) and prediction sets (6 sites, 225 spectra). NIR spectra (untreated and mathematically treated first and second derivative and multiplicative scatter correction) were correlated with tracheid properties to develop calibrations for the estimation of these properties. Strong correlations were obtained for properties related to density, the strongest R ² being 0.80 (coarseness), 0.78 (specific surface) and 0.84 (wall thickness). When applied to the test set, good relationships were obtained for the density-related properties (R p ² ranged from 0.68 to 0.86), but the accuracy of predictions varied depending on math treatment. The addition of a small number of cores from the prediction set (one core per new site) to the calibration set improved the accuracy of predictions and, importantly, minimized the differences obtained with the various math treatments. 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The addition of a small number of cores from the prediction set (one core per new site) to the calibration set improved the accuracy of predictions and, importantly, minimized the differences obtained with the various math treatments. 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(loblolly pine) trees grown on 14 sites in three physiographic regions of Georgia (USA) were measured by SilviScan. NIR spectra were also collected in 10 mm increments from the radial longitudinal surface of each strip and split into calibration (9 sites, 729 spectra) and prediction sets (6 sites, 225 spectra). NIR spectra (untreated and mathematically treated first and second derivative and multiplicative scatter correction) were correlated with tracheid properties to develop calibrations for the estimation of these properties. Strong correlations were obtained for properties related to density, the strongest R ² being 0.80 (coarseness), 0.78 (specific surface) and 0.84 (wall thickness). When applied to the test set, good relationships were obtained for the density-related properties (R p ² ranged from 0.68 to 0.86), but the accuracy of predictions varied depending on math treatment. 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subjects Accuracy
anatomy and morphology
Applied sciences
Calibration
Coarseness
Density
Evergreen trees
Exact sciences and technology
near-infrared spectroscopy
nondestructive methods
Pine trees
Pinus taeda
Polymer industry, paints, wood
Properties (attributes)
Properties and testing
Specific surface
Spectra
tracheids
Wall thickness
Wood
wood density
wood properties
Wood. Paper. Non wovens
title Non-destructive estimation of Pinus taeda L tracheid morphological characteristics for samples from a wide range of sites in Georgia
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