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Prediction of non-recoverable collapse in Eucalyptus globulus from near infrared scanning of radial wood samples

机译:从放射状木材样品的近红外扫描预测桉树的不可恢复的塌陷

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摘要

Near infrared (NIR) spectroscopy calibrations was used to predict radial profiles of cellulose content, wood density, cellulose microfibril angle (MFA) and modulus of elasticity (MOE) in 20-year-old plantation Eucalyptus globulus to identify non-recoverable collapse zones associated with tension wood. Radial (cambium-to-pith) wood cores were extracted at a height of 1.0 m from trees selected to represent a range of silvicultural treatments. NIR spectra were measured at 1 mm intervals along the radial-longitudinal face of each core after drying to 12 % equilibrium moisture content (EMC) at 40 °C. Tangential shrinkage was measured at eight points along each core, following steam reconditioning and re-drying to 12 % EMC. Additional cores from 20 of the sample trees were collected. Radial profiles of density, MFA and MOE were obtained for wood strips prepared from these cores, using the SilviScan 3 wood assessment system. Trait profiles were matched to radial NIR scans of these cores, enabling the development of NIR calibrations using partial least squares (PLS) regression. These, and an existing NIR calibration for cellulose content, were used to predict the radial profiles of the four wood properties for the first set of cores. Predicted wood properties were then related to actual tangential shrinkage measurements and the occurrence of visible bands of non-recoverable collapse. A regression model was developed to reliably predict regions of non-recoverable collapse from NIR-predicted cellulose content and MOE. Micrography of stained wood sections indicated that the collapse was caused by the presence of tension wood.
机译:近红外(NIR)光谱校准用于预测20岁人工林桉树球茎中纤维素含量,木材密度,纤维素微纤丝角(MFA)和弹性模量(MOE)的径向轮廓,以识别相关的不可恢复的塌陷区用张力木。从选择代表一系列造林方法的树木中以1.0 m的高度提取木(成虫到成虫)的木芯。在40°C下干燥至12%平衡水分含量(EMC)后,沿每个芯的径向-纵向面以1mm的间隔测量NIR光谱。蒸汽修复并重新干燥至12%EMC之后,沿每个芯在八个点测量切向收缩率。从20个样本树中收集了其他核心。使用SilviScan 3木材评估系统,从这些岩心制备的木板可获得密度,MFA和MOE的径向分布图。性状特征与这些核的径向NIR扫描相匹配,从而可以使用偏最小二乘(PLS)回归来开发NIR校准。这些以及纤维素含量的现有NIR校准用于预测第一组芯材的四种木材性能的径向轮廓。然后,将预测的木材性能与实际切向收缩率测量值以及不可恢复的塌陷可见带的发生相关。开发了一种回归模型,可以根据NIR预测的纤维素含量和MOE可靠地预测不可恢复的塌陷区域。染色木材切片的显微照片表明,塌陷是由张力木材的存在引起的。

著录项

  • 来源
    《European Journal of Wood and Wood Products》 |2013年第6期|755-768|共14页
  • 作者单位

    Department of Forest and Ecosystem Science Melbourne School of Land and Environment The University of Melbourne">(1);

    Cooperative Research Centre for Forestry">(4);

    Department of Forest and Ecosystem Science Melbourne School of Land and Environment The University of Melbourne">(1);

    Cooperative Research Centre for Forestry">(4);

    CSIRO Ecosystem Sciences">(2);

    Cooperative Research Centre for Forestry">(4);

    CSIRO Ecosystem Sciences">(2);

    Cooperative Research Centre for Forestry">(4);

    CSIRO Materials Science and Engineering">(3);

    Department of Forest and Ecosystem Science Melbourne School of Land and Environment The University of Melbourne">(1);

    Department of Forest and Ecosystem Science Melbourne School of Land and Environment The University of Melbourne">(1);

    Cooperative Research Centre for Forestry">(4);

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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