ABSTRACT

Moisture is one of the most important wood properties because its variation directly influences the material strength and density. Thus, the aim of this study was to develop near infrared (NIR) spectroscopic models in order to estimate the moisture content in wood specimens. Moreover, predictive models built from NIR signatures recorded by different acquisition methods and on wood surfaces were compared and discussed. Mass and NIR spectra were measured on forty (40) Eucalyptus wood specimens in 10 steps during drying from the fiber saturated point to anhydrous condition. NIR spectra were recorded by means of an integrating sphere and optical fiber probe on four surface. Thus, wood moisture values were correlated with the corresponding NIR spectra by Partial Least Squares (PLS) Regression. The best models for estimating wood moisture were developed from NIR spectra recorded on the transverse surface produced with the band saw by integrating sphere method (R²p = 0.96 and RMSEP = 8.56%) and fiber optic probe (R²p = 0.83 and RMSEP = 20.09%). Therefore, NIR spectrum recorded by integrating sphere taken on transverse or radial wood surface cut by band saw are the most suitable for generating NIR models for estimating the moisture content in Eucalyptus wood.

摘要

水分是最重要的木材特性之一，因为水分的变化直接影响材料的强度和密度。因此，本研究的目的是开发近红外 (NIR) 光谱模型，以估计木材样品中的水分含量。此外，比较和讨论了根据不同采集方法和木材表面记录的 NIR 特征建立的预测模型。在从纤维饱和点到无水条件的干燥过程中，分 10 个步骤对四十 (40) 棵桉树木材样品测量了质量和 NIR 光谱。近红外光谱是通过积分球和光纤探头在四个表面上记录的。因此，木材水分值通过偏最小二乘 (PLS) 回归与相应的 NIR 光谱相关联。R ²p = 0.96 和 RMSEP = 8.56%）和光纤探头（R ²p = 0.83 和 RMSEP = 20.09%）。因此，通过在带锯切割的横向或径向木材表面上获取的积分球记录的 NIR 光谱最适合生成 NIR 模型，以估计桉树木材中的水分含量。