A comparative study on the performance of terahertz, near-infrared, and hyperspectral spectroscopy for wood identification

被引：0

作者：

Wang, Yuan ^{[1
,2
,3
]}

He, Yihao ^{[1
]}

Qu, Renhe ^{[1
]}

Avramidis, Stavros ^{[4
]}

机构：

[1] School of Technology, Beijing Forestry University, Beijing, China

[2] Research Center for Biodiversity Intelligent Monitoring, Beijing Forestry University, Beijing, China

[3] Joint International Research Institute of Wood Nondestructive Testing and Evaluation, Beijing Forestry University, Beijing, China

[4] Department of Wood Science, Faculty of Forestry, University of British Columbia, Vancouver, Canada

来源：

Wood Material Science and Engineering | 2025年 / 20卷 / 02期

关键词：

Cost effectiveness - Discriminant analysis - Infrared devices - Least squares approximations - Terahertz spectroscopy - Wood;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Wood species identification is of paramount significance in wood products manufacturing and applications. In contrast to traditional wood identification methods, spectroscopy-based technology offers a rapid, cost-effective, and efficient alternative. This study focuses on five wood species as experimental materials and aims to obtain three distinct wood spectra for each: near-infrared (NIR) spectra, hyperspectral image spectral information, and terahertz (THz) spectra. These spectra underwent pre-processing techniques such as Savitzky–Golay smoothing (SG), normalization, multiple scattering correction (MSC), and standard normalized variate (SNV), followed by dimensionality reduction through principal component analysis (PCA). Subsequently, the processed data were input into a partial least squares discriminant analysis (PLS-DA) for recognition. The results demonstrate the best recognition accuracy of 99.8% for THz spectra, 98.7% for NIR spectra, and 97.3% for hyperspectral image spectral information. The THz spectra exhibited the highest recognition accuracy, particularly with the SG-preprocessed THz spectra. These preprocessed spectra effectively removed noise and smoothed the spectral curves compared to the raw spectra. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

引用

页码：382 / 393