构造
偏最小二乘回归
校准
含水量
近红外光谱
光谱学
抗压强度
材料科学
数学
线性回归
红外光谱学
环境科学
分析化学(期刊)
遥感
复合材料
化学
统计
植物
地质学
光学
物理
环境化学
生物
有机化学
岩土工程
量子力学
作者
S. R. Shukla,Sanjeev Sharma
标识
DOI:10.4067/s0718-221x2021000100418
摘要
Near infrared spectroscopy is non-invasive and may be applied as a rapid and cost effective technique for assessment of quality parameters of timber. Near infrared spectra of Tectona grandis (teak) wood samples were collected before measuring physical (density, equilibrium moisture content) and strength (flexural and compressive) properties using conventional methods. Partial least squares regression was used to develop calibration models between measured wood properties and near infrared data. The best near infrared spectra pre-processing methods differed by property. Linear calibration models with high R², low error and high ratio of performance to deviation values were observed from partial least squares analysis for different wood properties. These linear models may be applied for rapid and precise estimation of the properties examined in testing and evaluation procedures for commercially valuable teak wood.
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