Spectroscopy and Spectral Analysis, Volume. 40, Issue 11, 3542(2020)

Study on Extracting Characteristic Wavelength of Soybean Physiological Information Based on Hyperspectral Technique

Shuang LIU... Hai-ye YU, Zhao-jia PIAO, Mei-chen CHEN, Tong YU, Li-juan KONG, Lei ZHANG, Jing-min DANG and Yuan-yuan SUI |Show fewer author(s)
Author Affiliations
  • School of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
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    Figures & Tables(5)
    Characteristic wavelengths selected by CARS algorithm(a): Chlorophyll content (D1); (b): Chlorophyll content(D2);(c): Light energy utilization (D1); (d): Light energy utilization(D2)
    Characteristic wavelengths selected by SPA algorithm(a): Chlorophyll content (D1); (b): Chlorophyll content(D2);(c): Light energy utilization (D1); (d): Light energy utilization(D2)
    Characteristic wavelengths selected by CC algorithm(a): Chlorophyll content (D1); (b): Chlorophyll content(D2);(c): Light energy utilization (D1); (d): Light energy utilization(D2)
    • Table 1. Optimization results from hyperspectral pre-processing methods

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      Table 1. Optimization results from hyperspectral pre-processing methods

      建模对象日期预处理方法RcRp建模对象日期预处理方法RcRp
      叶绿素含量D1RAW0.8420.828光能利用率D1RAW0.8620.825
      MSC0.8690.846MSC0.8870.850
      SNV0.8670.839SNV0.8910.854
      SG0.8550.838SG0.8940.821
      FD0.8580.824FD0.8850.856
      SD0.8590.818SD0.8620.827
      MSC-SG-FD0.9090.882MSC-SG-FD0.9000.878
      MSC-SG-SD0.8930.833MSC-SG-SD0.8910.887
      SNV-SG-FD0.8960.870SNV-SG-FD0.9130.894
      SNV-SG-SD0.9030.838SNV-SG-SD0.9070.862
      D2RAW0.8750.730D2RAW0.8690.838
      MSC0.9030.876MSC0.8810.856
      SNV0.9070.867SNV0.8820.857
      SG0.8870.869SG0.8890.787
      FD0.8830.814FD0.8860.833
      SD0.8730.788SD0.8700.823
      MSC-SG-FD0.9090.880MSC-SG-FD0.8960.808
      MSC-SG-SD0.8990.873MSC-SG-SD0.9000.865
      SNV-SG-FD0.9090.816SNV-SG-FD0.9020.869
      SNV-SG-SD0.8970.869SNV-SG-SD0.9000.866
    • Table 2. Soybean physiological information inversion model results

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      Table 2. Soybean physiological information inversion model results

      建模对象日期建模方法变量
      保留数
      PcsRcRp建模对象日期建模方法变量
      保留数
      PcsRcRp
      叶绿素含量D1PLS512100.9090.882光能利用率D1PLS512100.9130.894
      CC-PLS22190.9110.906CC-PLS23490.9190.902
      CARS-PLS4190.9270.892CARS-PLS4690.9210.909
      SPA-PLS2070.9440.911SPA-PLS2770.9290.912
      D2PLS512100.9090.880D2PLS512100.9020.869
      CC-PLS9790.9020.898CC-PLS22490.9070.885
      CARS-PLS9690.9140.899CARS-PLS3290.9120.898
      SPA-PLS2370.9410.903SPA-PLS3770.9250.907
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    Shuang LIU, Hai-ye YU, Zhao-jia PIAO, Mei-chen CHEN, Tong YU, Li-juan KONG, Lei ZHANG, Jing-min DANG, Yuan-yuan SUI. Study on Extracting Characteristic Wavelength of Soybean Physiological Information Based on Hyperspectral Technique[J]. Spectroscopy and Spectral Analysis, 2020, 40(11): 3542

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    Paper Information

    Category: Research Articles

    Received: Sep. 21, 2019

    Accepted: --

    Published Online: Jun. 18, 2021

    The Author Email:

    DOI:10.3964/j.issn.1000-0593(2020)11-3542-07

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