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首页> 外文期刊>Holzforschung >Calibration of SilviScan data of Cryptomeria japonica wood concerning density and microfibril angles with NIR hyperspectral imaging with high spatial resolution
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Calibration of SilviScan data of Cryptomeria japonica wood concerning density and microfibril angles with NIR hyperspectral imaging with high spatial resolution

机译:利用高空间分辨率的近红外高光谱成像对日本柳杉木材的密度和微纤维角度进行SilviScan数据校准

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摘要

Wood density and microfibril angle (MFA) are strongly correlated with wood stiffness, swelling/shrinkage, and its anisotropy. Understanding the spatial distribution of these data is critical for solid timber applications. In this study, near-infrared (NIR) hyperspectral imaging has been calibrated for evaluation of wood density and MFA in an effective manner. Briefly, five wood samples collected from both normal wood (NW) and compression wood (CW) moieties of two different Cryptomeria japonica trees were analyzed. Partial least squares (PLS) regression analysis was performed to determine the relationship between X-ray densitometry data obtained by SilviScan and NIR spectra, and cross-validation (leave-one-out) approach served for prediction performances. The validation coefficient of determination (r(2)) between the predicted densities by the NIR technique and the X-ray data was 0.83 with a root mean squared error of cross-validation (RMSECV) of 105.2 kg m(-3). Regarding MFA, the r(2) was 0.77 and RMSECV 5.36 degrees. Wood density was successfully maped as well as the MFA at a high spatial resolution. As a result, the detection of annual growth ring features and evaluation of aspects of heterogeneous wood quality has been facilitated. The mapping results were visually checked by looking at the difference between earlywood (EW) and latewood (LW) for density and by means of the Maule color reaction indicating high lignin contents in CW in terms of MFA validation as CWs have high MFA values.
机译:木材密度和微纤丝角(MFA)与木材刚度,膨胀/收缩及其各向异性密切相关。了解这些数据的空间分布对于实木应用至关重要。在这项研究中,已对近红外(NIR)高光谱成像进行了校准,以有效地评估木材密度和MFA。简而言之,分析了从两种不同柳杉属的普通木材(NW)和压缩木材(CW)部分收集的五个木材样品。进行偏最小二乘(PLS)回归分析,以确定通过SilviScan获得的X射线光密度测定数据与NIR光谱之间的关系,以及交叉验证(留一法)方法可用于预测性能。 NIR技术和X射线数据在密度预测值上的确定系数(r(2))为0.83,交叉验证的均方根误差(RMSECV)为105.2 kg m(-3)。关于MFA,r(2)为0.77,RMSECV为5.36度。木材密度以及MFA在高空间分辨率下均已成功绘制。结果,促进了年轮特征的检测和异质木材质量方面的评估。通过观察早木(EW)和晚木(LW)之间的密度差异并通过Maule显色反应,通过MFA验证表明CW中木质素含量高,因为CW具有较高的MFA值,通过目测检查了映射结果。

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