基于三种木材表面记录的近红外光谱,并进行不同的数学处理,评估基本密度校准

IF 1.5 4区 农林科学 Q2 FORESTRY
Evelize Aparecida Amaral, Luana Maria dos Santos, P. R. Hein, Emylle Veloso Santos Costa, S. C. S. Rosado, P. F. Trugilho
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引用次数: 3

摘要

背景:近红外(NIR)光谱已经成功地应用于评估各种生物材料的化学、物理和机械性能,包括木材。本研究的目的是评估基于三种木材表面近红外光谱的基本密度校准,并进行不同的数学处理。方法:采用积分球法对278株尾巨桉(Eucalyptus urophylla x Eucalyptus grandis)木材样品的横向、径向和切向漫反射近红外光谱进行记录。在室内用浸渍法测定了木材试样的基本密度,并用偏最小二乘回归与近红外光谱进行了相关性分析。然后对数据进行不同的统计处理,包括标准正态变量、乘法散点校正、一阶导数和二阶导数、归一化、Autoscale和MeanCenter转换。结果:基于横向表面近红外光谱的预测模型效果最好(R²cv = 0.85, RMSE = 25.5 kg/m³),而基于切向表面近红外光谱的预测模型效果最差(R²cv = 0.53, RMSE = 46.8 kg/m³)。基于原始(未经处理)和数学处理的光谱的模型之间的性能差异很小。结论:拟合近红外光谱的多变量模型可以有效地预测桉树木材的基本密度,特别是基于横向表面测量的光谱。对于该数据集,基于原始光谱和经过数学处理的光谱的模型具有相似的性能。研究结果表明,数学变换并不总是能够从近红外光谱中提取更多的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating basic density calibrations based on NIR spectra recorded on the three wood faces and subject to different mathematical treatments
Background: Near infrared (NIR) spectroscopy has been successfully applied to estimate the chemical, physical and mechanical properties of various biological materials, including wood. This study aimed to evaluate basic density calibrations based on NIR spectra collected from three wood faces and subject to different mathematical treatments. Methods: Diffuse reflectance NIR spectra were recorded using an integrating sphere on the transverse, radial and tangential surfaces of 278 wood specimens of Eucalyptus urophylla x Eucalyptus grandis. Basic density of the wood specimens was determined in the laboratory by the immersion method and correlated with NIR spectra by Partial Least Squares regression. Different statistical treatments were then applied to the data, including Standard Normal Variate, Multiplicative Scatter Correction, First and Second Derivatives, Normalization, Autoscale and MeanCenter transformations. Results: The predictive model based on NIR spectra measured on the transverse surface performed the best (R²cv = 0.85 and RMSE = 25.5 kg/m³) while the model developed from the NIR spectra measured on the tangential surface had the poorest performance (R²cv = 0.53 and RMSE = 46.8 kg/m³). The difference in performance between models based on original (untreated) and mathematically-treated spectra was minimal. Conclusions: Multivariate models fitted to NIR spectra were found to be efficient for predicting the basic density of Eucalyptus wood, especially when based on spectra measured on the transversal surface. For this data set, models based on the original spectra and mathematically treated spectra had similar performance. The reported findings show that mathematical transformations are not always able to extract more information from the spectra in the NIR.
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来源期刊
CiteScore
2.20
自引率
13.30%
发文量
20
审稿时长
39 weeks
期刊介绍: The New Zealand Journal of Forestry Science is an international journal covering the breadth of forestry science. Planted forests are a particular focus but manuscripts on a wide range of forestry topics will also be considered. The journal''s scope covers forestry species, which are those capable of reaching at least five metres in height at maturity in the place they are located, but not grown or managed primarily for fruit or nut production.
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