• Spectroscopy and Spectral Analysis
  • Vol. 41, Issue 1, 236 (2021)
Li-juan KONG*, Hai-ye YU, Mei-chen CHEN, Zhao-jia PIAO, Shuang LIU, Jing-min DANG, Lei ZHANG, and Yuan-yuan SUI
Author Affiliations
  • School of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
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    DOI: 10.3964/j.issn.1000-0593(2021)01-0236-07 Cite this Article
    Li-juan KONG, Hai-ye YU, Mei-chen CHEN, Zhao-jia PIAO, Shuang LIU, Jing-min DANG, Lei ZHANG, Yuan-yuan SUI. Analyze on the Response Characteristics of Leaf Vegetables to Particle Matters Based on Hyperspectral[J]. Spectroscopy and Spectral Analysis, 2021, 41(1): 236 Copy Citation Text show less
    Schematic diagram of experimental chamber device
    Fig. 1. Schematic diagram of experimental chamber device
    ESEM image of particle matters
    Fig. 2. ESEM image of particle matters
    Spectral characteristics of three kinds of leaves under PM (eg) and non-PM (cg)b: Pakchoi; y: Brassica napus; s: Italian lettuce; cg: The control group; eg: Experimental group. The same below
    Fig. 3. Spectral characteristics of three kinds of leaves under PM (eg) and non-PM (cg)
    b: Pakchoi; y: Brassica napus; s: Italian lettuce; cg: The control group; eg: Experimental group. The same below
    First derivative hyperspectral characteristics of three kinds of leaves
    Fig. 4. First derivative hyperspectral characteristics of three kinds of leaves
    First derivative spectra of three kinds of leaves in the yellow aod blue light ranges(a): Yellow light range; (b): Blue light range
    Fig. 5. First derivative spectra of three kinds of leaves in the yellow aod blue light ranges
    (a): Yellow light range; (b): Blue light range
    Correlation between original spectrum, first derivative spectra and net photosynthetic rates of three kinds of leaf vegetables(a): Italian lettuce leaves; (b): Pakchoi leaves; (c): Oilseed rape leaves
    Fig. 6. Correlation between original spectrum, first derivative spectra and net photosynthetic rates of three kinds of leaf vegetables
    (a): Italian lettuce leaves; (b): Pakchoi leaves; (c): Oilseed rape leaves
    叶菜品种红边位置/nm红边蓝移/nm
    对照组试验组
    生菜6976961
    小白菜7117101
    小油菜7257169
    Table 1. Red edge position (REP) of vegetables
    叶菜原始提取
    /nm
    FD提取/nmMSC提取
    /nm
    相关分析法提取/nm最优特征
    波长/nm
    生菜554520/598/609/633/696555530/586/626/681530
    小白菜557593/613/532/629/710558557/584584
    小油菜553525/598/613/628553592/598/668598
    Table 2. Optimal characteristic wavelength
    高光谱特征参数及植被指数参数说明相关系数
    生菜小白菜小油菜
    红边幅值(Dr)红边内最大一阶微分值-0.878*-0.383-0.625
    红边位置(λr)红边幅值对应的波长位置0.395-0.2530.743*
    红边面积(SDr)红边内一阶微分的总和0.726*-0.874*-0.519
    黄边幅值(Dy)黄边内最大一阶微分值-0.148-0.857*-0.517
    黄边面积(SDy)黄边内一阶微分的总和0.216-0.302-0.753*
    蓝边幅值(Db)蓝边内最大一阶微分值-0.5450.498-0.541
    蓝边面积(SDb)蓝边内一阶微分的总和-0.2530.246-0.522
    绿峰反射率(Rg)可见光绿光区(490~560 nm)内的最大高光谱反射率-0.4360.368-0.382
    红谷反射率(Rr)可见光红光区(620~780nm)内的最小高光谱反射率-0.5760.283-0.338
    近红外峰值(NIRRP)近红外短波区(780~1 075 nm)内的最大高光谱反射率0.548-0.796*0.473
    SDr/SDb红边面积与蓝边面积的比值0.771*-0.228-0.218
    SDr/Sdy红边面积与黄边面积的比值-0.754*0.3680.442
    (SDr-SDb)/(SDr+SDb)红边面积与蓝边面积的归一化值0.547-0.4310.569
    (SDr-SDy)/(SDr+SDy)红边面积与黄边面积的归一化值-0.4830.727*0.715*
    Table 3. The correlation coefficients of spectral characteristic parameters and net photosynthetic rate of leaves polluted by PM
    叶菜光谱特征变量建模方法及拟合模型相关性
    RcRp
    生菜ρ'(530)y=48 201.0+55 116.8lnx+20 996.6(lnx)2+2 664.1(lnx)3R2=0.712
    Dry=58.615+936.78lnx+3 823.7(lnx)2+4 437.1(lnx)3R2=0.771
    ρ'(498~550)CLS0.439 80.485 6
    PLS0.897 80.876 5
    PCR0.874 30.876 1
    SMLR0.753 10.692 6
    ρ'(555~656)CLS0.308 60.392 4
    PLS0.889 60.855 2
    PCR0.851 00.794 8
    SMLR0.698 10.599 4
    ρ'(681~717)CLS0.381 90.486 6
    PLS0.912 20.907 0
    PCR0.881 70.850 1
    SMLR0.710 60.725 9
    小白菜ρ'(584)y=19.975-16 395.4lnx-3.911 9(lnx)2-2.184 9(lnx)3R2=0.819
    Dyy=10 886+9 638.9x+2 841.4x2+278.30x3R2=0.679
    ρ'(583~619)PLS0.952 80.914 4
    PCR0.919 20.901 7
    SMLR0.891 60.896 8
    小油菜ρ'(598)y=14.252+6 877.4x+7.5266x2-8.534 0x3R2=0.802
    ρ'(525~557)PLS0.528 70.558 4
    PCR0.634 50.501 4
    SMLR0.875 40.898 6
    ρ'(592~631)PLS0.384 50.357 5
    PCR0.765 60.750 4
    SMLR0.896 40.875 1
    Table 4. Inversion models of net photosynthetic rate under PM
    Li-juan KONG, Hai-ye YU, Mei-chen CHEN, Zhao-jia PIAO, Shuang LIU, Jing-min DANG, Lei ZHANG, Yuan-yuan SUI. Analyze on the Response Characteristics of Leaf Vegetables to Particle Matters Based on Hyperspectral[J]. Spectroscopy and Spectral Analysis, 2021, 41(1): 236
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