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Effect of surface roughness on near infrared models for wood density analysis

机译:表面粗糙度对用于木材密度分析的近红外模型的影响

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摘要

The near-infrared spectroscopy (NIR) coupled with multivariate analysis to predict density of wood samples with two surface roughness levels was analyzed in order to investigate the effect of surface roughness on NIR predicting wood density in this paper. The main results were described as follows: (1) The predicting results of density model based on samples with smooth surface performed better than that based on samples with coarse surface. The correlation coefficients of calibration model and validation model of samples with coarse surface based on the NIR which were obtained from cross section of samples were 0.81 and 0.74, and that of the samples with smooth surface were 0.94 and 0.88 respectively. (2) The NIR with wavelength ranges of 350∼500 nm and 2 350 ∼ 2 500 nm showed significant spectral response to wood surface roughness. (3) It was suggested that the surface roughness of prediction samples should be same to that of the calibration samples.
机译:为了研究表面粗糙度对NIR预测木材密度的影响,分析了近红外光谱法(NIR)与多变量分析相结合来预测具有两个表面粗糙度水平的木材样品的密度。主要结果如下:(1)基于光滑表面样品的密度模型预测结果优于基于粗糙表面样品的密度模型预测结果。从样品的横截面得到的基于NIR的粗糙表面样品的校准模型和验证模型的相关系数分别为0.81和0.74,而光滑表面样品的相关系数分别为0.94和0.88。 (2)波长范围为350〜500 nm和2350〜2500 nm的NIR对木材表面粗糙度显示出明显的光谱响应。 (3)建议预测样品的表面粗糙度应与校准样品的表面粗糙度相同。

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