近红外光谱
含水量
水分
材料科学
偏最小二乘回归
积分球
纤维
光谱学
桉树
复合材料
无水的
分析化学(期刊)
数学
光学
化学
色谱法
植物
地质学
有机化学
岩土工程
物理
统计
生物
量子力学
作者
Luana Maria dos Santos,Evelize Aparecida Amaral,Érick Martins Nieri,Emylle Veloso Santos Costa,Paulo Fernando Trugilho,Natalino Calegário,Paulo Ricardo Gherardi Hein
标识
DOI:10.1080/17480272.2020.1768143
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI