Spectroscopy and Spectral Analysis, Volume. 42, Issue 5, 1607(2022)

Relationships Between the Leaf Respiration of Soybean and Vegetation Indexes and Leaf Characteristics

Jin WANG1,1; 2;... Shu-tao CHEN1,1; 2; *;, Si-cheng DING1,1; 2;, Xue-wen YAO1,1; 2;, Miao-miao ZHANG1,1; 2; and Zheng-hua HU2,2; |Show fewer author(s)
Author Affiliations
  • 11. Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
  • 22. School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
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    Figures & Tables(5)
    Seasonal changes in the respiration of a single leaf and leaf respiration coefficient(a): Reasonal of a single leaf; (b): Leaf respriration coefficient
    Seasonal changes in the NDVI (a), DVI (b), RVI (c), EVI (d), PRI (e) and RECI (f)
    Relationships between the observedrespiration of a single leaf and respiration coefficient and the modeled respiration of a single leaf and respiration coefficient(a): Reasonal of a single leaf; (b): Leaf respriration coefficient
    • Table 1. Functions to compute vegetation indexes

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      Table 1. Functions to compute vegetation indexes

      公式文献
      NDVI=(R800-R670)/(R800+R670)[16]
      DVI=R800-R670[14, 17]
      RVI=R800/R670[14, 17]
      EVI=2.5(R800- R670)/(1+R800+6 R670-7R479)[18]
      PRI=(R531-R570)/(R531+R570)[14, 17]
      RECI=R750/R710-1[14]
    • Table 2. Pearson's correlation between the leaf respiration and air temperature, NDVI, DVI, RVI, EVI, PRI and RECI, SPAD value, fresh mass, dried mass, water content, area, specific leaf area and nitrogen content of leaf

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      Table 2. Pearson's correlation between the leaf respiration and air temperature, NDVI, DVI, RVI, EVI, PRI and RECI, SPAD value, fresh mass, dried mass, water content, area, specific leaf area and nitrogen content of leaf

      单片叶片
      呼吸
      呼吸系数气温NDVIDVIRVIEVIPRIRECISPAD值鲜重干重含水量叶面积比叶面积
      呼吸系数r0.671
      p0.002
      气温r0.5950.554
      p0.0090.017
      NDVIr0.0160.1960.669
      p0.9500.4360.002
      DVIr-0.0760.0140.0780.003
      p0.7630.9560.7590.991
      RVIr0.0470.2200.6550.9390.139
      p0.8530.3810.0030.0000.583
      EVIr-0.0650.0330.1410.0830.9880.195
      p0.7960.8970.5780.7420.0000.437
      PRIr0.5970.2750.6240.2340.1630.3900.169
      p0.0090.2700.0060.3500.5180.1100.503
      RECIr0.5290.3290.8010.6080.0390.6980.0800.891
      p0.0240.1830.0000.0070.8770.0010.7520.000
      SPAD值r0.099-0.537-0.061-0.271-0.180-0.305-0.2050.1050.022
      p0.6960.0220.8090.2770.4760.2180.4140.6780.932
      鲜重r-0.337-0.693-0.2140.149-0.1210.054-0.093-0.234-0.1090.417
      p0.1710.0010.3930.5550.6310.8300.7140.3500.6670.085
      干重r-0.196-0.757-0.244-0.100-0.224-0.206-0.215-0.144-0.1200.7500.893
      p0.4350.0000.3290.6930.3720.4120.3910.5690.6360.0000.000
      含水量r-0.2900.0450.0920.6020.1420.5920.200-0.1860.068-0.5850.399-0.050
      p0.2430.8610.7160.0080.5750.0100.4370.4610.7880.0110.1010.843
      叶面积r0.161-0.3810.2710.221-0.0840.157-0.0380.3260.3710.5060.7670.7680.180
      p0.5220.1190.2770.3770.7420.5330.8800.1860.1290.0320.0000.0000.474
      比叶面积r0.2240.7360.4590.4270.2290.4940.2630.2480.335-0.860-0.509-0.7920.497-0.298
      p0.3710.0000.0550.0770.3610.0370.2910.3220.1740.0000.0310.0000.0360.230
      氮含量r0.5640.1910.4350.002-0.356-0.148-0.3100.2980.3290.4500.0580.288-0.3720.502-0.166
      p0.0150.4480.0710.9940.1470.5570.2110.2290.1830.0610.8200.2460.1280.0340.511
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    Jin WANG, Shu-tao CHEN, Si-cheng DING, Xue-wen YAO, Miao-miao ZHANG, Zheng-hua HU. Relationships Between the Leaf Respiration of Soybean and Vegetation Indexes and Leaf Characteristics[J]. Spectroscopy and Spectral Analysis, 2022, 42(5): 1607

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    Paper Information

    Category: Research Articles

    Received: Apr. 18, 2021

    Accepted: --

    Published Online: Nov. 10, 2022

    The Author Email:

    DOI:10.3964/j.issn.1000-0593(2022)05-1607-07

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