Preliminary Investigation into the Identification of Wood Species from Different Locations by Near Infrared Spectroscopy

被引:2
|
作者
Yang, Zhong [1 ]
Liu, Yana [1 ]
Pang, Xiaoyu [1 ]
Li, Kang [1 ]
机构
[1] Chinese Acad Forestry, Res Inst Wood Ind, Beijing 100091, Peoples R China
来源
BIORESOURCES | 2015年 / 10卷 / 04期
关键词
Wood; Identification; Different locations; Near-infrared spectroscopy; PLS-DA; FT-NIR SPECTROSCOPY; MICROFIBRIL ANGLE; SPECTRA; CLASSIFICATION; STIFFNESS; DENSITY; LIGNIN; TOOL;
D O I
暂无
中图分类号
TB3 [工程材料学]; TS [轻工业、手工业、生活服务业];
学科分类号
0805 ; 080502 ; 0822 ;
摘要
The feasibility of using near-infrared spectroscopy (NIR) to identify wood species was investigated in this study. Case I considers the principal component analysis scores plot of NIR spectra for three wood species. Case II considers whether NIR combined with partial least squares discriminant analyses can be used to identify the three wood species. Three wood species were studied, and each species included five randomly collected wood blocks, 21 samples for each wood block, and 315 total wood samples. In case I, the samples in the PCA analysis were clustered together. In case II, samples in the training set were classified into the correct group, and the accuracy of the test set was up to 90%.
引用
收藏
页码:8505 / 8517
页数:13
相关论文
共 50 条
  • [1] Wood species identification from Atlantic forest by near infrared spectroscopy
    Pace, Jose H. C.
    Latorraca, Joao V. F.
    Hein, Paulo R. G.
    Castro, Jonnys P.
    Carvalho, Alexandre M.
    Silva, Carlos E. S.
    FOREST SYSTEMS, 2019, 28 (03)
  • [2] Identification of Wood Species Based on Near Infrared Spectroscopy and Pattern Recognition Method
    Hao Yong
    Shang Qing-yuan
    Rao Min
    Hu Yuan
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39 (03) : 705 - 710
  • [3] Study on Artificial Neural Network Combined with Near Infrared Spectroscopy for Wood Species Identification
    Ma Ming-yu
    Wang Gui-yun
    Huang An-min
    Zhang Zhuo-yong
    Xiang Yu-hong
    Gu Xuan
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2012, 32 (09) : 2377 - 2381
  • [4] PRELIMINARY STUDY OF WOOD SPECIES IDENTIFICATION BY NIR SPECTROSCOPY
    Russ, Albert
    Fiserova, Maria
    Gigac, Juraj
    WOOD RESEARCH, 2009, 54 (04) : 23 - 32
  • [5] Identification of Five Similar Cinnamomum Wood Species Using Portable Near-Infrared Spectroscopy
    Pan, Xi
    Qiu, Jian
    Yang, Zhong
    SPECTROSCOPY, 2022, 37 (06) : 16 - +
  • [6] Rapid Prediction of Different Wood Species Extractives and Lignin Content Using Near Infrared Spectroscopy
    He, Wenming
    Hu, Huiren
    JOURNAL OF WOOD CHEMISTRY AND TECHNOLOGY, 2013, 33 (01) : 52 - 64
  • [7] DISCRIMINATION OF WOOD AND CHARCOAL FROM SIX CAATINGA SPECIES BY NEAR-INFRARED SPECTROSCOPY
    Nisgoski, Silvana
    Ribeiro Batista, Francielli Rodrigues
    Naide, Tawani Lorena
    Clivati Laube, Nadia Catarina
    Ribas Leao, Amanda Carolina
    Bolzon de Muniz, Graciela Ines
    MADERAS-CIENCIA Y TECNOLOGIA, 2018, 20 (02): : 199 - 210
  • [8] Cognitive spectroscopy for wood species identification: near infrared hyperspectral imaging combined with convolutional neural networks
    Kanayama, Hideaki
    Ma, Te
    Tsuchikawa, Satoru
    Inagaki, Tetsuya
    ANALYST, 2019, 144 (21) : 6438 - 6446
  • [9] Visible-Near Infrared Spectroscopy and Chemometric Methods for Wood Density Prediction and Origin/Species Identification
    Li, Ying
    Via, Brian K.
    Young, Tim
    Li, Yaoxiang
    FORESTS, 2019, 10 (12):
  • [10] Simultaneous Prediction of Wood Density and Wood Species Based on Visible/Near Infrared Spectroscopy
    Zhao Peng
    Li Yue
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39 (11) : 3525 - 3532