Using Remote Sensing to Characterize Yield Loss due to Water and N stress in Corn. - PowerPoint PPT Presentation

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Using Remote Sensing to Characterize Yield Loss due to Water and N stress in Corn.

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Using Remote Sensing to Characterize Yield Loss due to Water and N stress in Corn. David E. Clay, K. Kim, J. Chang, S.A. Clay, C.G. Carlson, and K. Dalsted – PowerPoint PPT presentation

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Title: Using Remote Sensing to Characterize Yield Loss due to Water and N stress in Corn.


1
Using Remote Sensing to Characterize Yield Loss
due to Water and N stress in Corn.
  • David E. Clay, K. Kim, J. Chang, S.A. Clay, C.G.
    Carlson, and K. Dalsted

2
N and water stress
  • NASA
  • North Central Soybean Board
  • SD Corn Utilization Council
  • USDA-CSREES
  • PPI
  • SD Soybean Research and Promotion council.

3
We also know that multiple factors interact to
influence reflectance
  • Reflectance
  • f(water, nutrients, light,
  • energy, diseases, insects,
  • other)

4
Bare soil, 2001
August 24, 2001
5
Objectives
  • Determine the influence of water and N stress on
    yields and reflectance.

6
Field experiment
  • N and water experiment was conducted between 2002
    and 2004.
  • Remote sensing was measured with a crop scan.
  • Carbon and N budgets were determined

7
Need to separate N and water stress from each
other
  • 13C natural abundance approach was used to
    quantify N and water stress in the plants

8
N and water response
Natural irrigation
Natural
9
N budget
Soil yield zone Yield Mg/ha N min. Kg/ha WUE Kg/ha cm N from soil (kg N/ha)
Low 8500 72.0 218 80
High 9600 86.0 190 92
P-value 0.004 0.062 0.006 0.027
10
N effects
N rate Yield (Mg/ha) WUE kg/ha cm N from soil
0 7510 170 80
56 9040 204 99
112 9890 223 96
168 9800 219 70
P value 0.001 0.001 0.001
11
Sampling        
date Parameter Yield YLNS YLWS
12 July NDVI 0.24 -0.41 0.20
 V8-V9 GNDVI 0.67 -0.73 0.02
  Green -0.22 0.24 -0.02
  Red -0.14 0.23 -0.11
  NIR 0.19 -0.48 0.34
12
Sampling        
date Parameter Yield YLNS YLWS
Aug. 1-4 NDVI 0.65 -0.22 -0.61
 R1 GNDVI 0.63 -0.65 -0.04
  Green -0.55 0.49 -0.14
  Red -0.48 0.05 0.58
  NIR 0.16 0.27 0.12
13
Summary
  • Stuff changes
  • Early on reflectance sensitive to N but not water
  • At R1 (silking) water and N both impacted
    reflectance
  • Green N
  • Red water

14
Models
       
Sampling date Model RMSE N needed ModelYLNS
 V8-V9
12-14 July N stress 16.2 26.4 29000
  Yield model 21.6 30.2 32500
  Yield water stress 21.7 23.6 46400
15
Summary
  • Water and N stress both impact reflectance.
  • N stress early, water stress later
  • 13C discrimination can be used separate the
    factors.

16
Summary
  • Remote sensing models can be used to develop
    corrective treatments.
  • The models can be developed using a variety of
    approaches.

17
Summary
  • The model based on N stress had lowest lost
    opportunity and RMSE.
  • Attributed to the water and N cycles being
    interrelated and that the low and high water
    regimes had similar optimum N rates.
  • Water increased N mineralization and N increased
    water use efficiency. A sandy soil may have
    different results.
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