refinement of the missouri corn nitrogen algorithm using canopy reflectance newell kitchen, ken...
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Refinement of the Missouri Corn Nitrogen Algorithm Using Canopy Reflectance
Refinement of the Missouri Corn Nitrogen Algorithm Using Canopy Reflectance
Newell Kitchen, Ken Sudduth, and Scott DrummondNewell Kitchen, Ken Sudduth, and Scott Drummond
USDA-Agricultural Research ServiceUSDA-Agricultural Research Service
Peter Scharf, Harlan Palm, and Kent ShannonPeter Scharf, Harlan Palm, and Kent Shannon
University of MissouriUniversity of Missouri
Newell Kitchen, Ken Sudduth, and Scott DrummondNewell Kitchen, Ken Sudduth, and Scott Drummond
USDA-Agricultural Research ServiceUSDA-Agricultural Research Service
Peter Scharf, Harlan Palm, and Kent ShannonPeter Scharf, Harlan Palm, and Kent Shannon
University of MissouriUniversity of Missouri
Active-light Reflectance Sensing
Objective: To assess on different Missouri Objective: To assess on different Missouri soils the use of active crop-canopy soils the use of active crop-canopy reflectance sensors for assessing corn N reflectance sensors for assessing corn N need and developing algorithms for need and developing algorithms for optimizing economic returns with variable-optimizing economic returns with variable-rate N fertilizer application.rate N fertilizer application.
Methods• A total of 16 field-scale experiments were conducted A total of 16 field-scale experiments were conducted
over four growing seasons (2004-2007)over four growing seasons (2004-2007)
• These fields represented three major soil areas of These fields represented three major soil areas of Missouri: river alluvium, deep loess, and claypan. Missouri: river alluvium, deep loess, and claypan.
• Multiple blocks of N randomized rate response plots Multiple blocks of N randomized rate response plots were arranged end-to-end so that blocks traversed the were arranged end-to-end so that blocks traversed the length of each field. Each block consisted of 8 N length of each field. Each block consisted of 8 N treatments from 0 to 235 kg N/ha on 34 kg N/ha treatments from 0 to 235 kg N/ha on 34 kg N/ha increments, top-dressed sometime between vegetative increments, top-dressed sometime between vegetative growth stages V7 and V11growth stages V7 and V11
• For 2006 and 2007, a complete second set of field-length blocks were also established where 67 kg N/ha was uniformly applied over the set of blocks shortly after corn emergence.
• Adjacent to and on both sides of the response blocks, N-rich (235 kg N/ha) reference strips were also established. These ran the full length of the field and were treated shortly after corn emergence.
• An AGCO Spra-Coupe (AGCO Corp., Duluth, GA) high-clearance applicator equipped with an AGCO FieldStar Controller was used to top-dress between corn rows solution UAN (28 or 32% N) fertilizer for the N rate treatments.
• Crop canopy reflectance sensor (Crop Circle model ACS-210, Holland Scientific, Inc., Lincoln, NE) measurements were obtained from the corn canopy of the N response blocks at the same time the Spra-Coupe was used to apply N rate treatments.
• On the same day reflectance sensor measurements were also obtained from the N-rich reference strips.
• Data analysis for these field studies included four major steps:
1) Determining optimal N with quadratic-plateau modeling
2) Processing of canopy reflectance senor data from response plots and the N-rich reference areas
3) Relating modeled optimal N from step 1 with sensor measurements from step 2
4) Developing optimized-profit algorithms relative to conventional producer N rates
Results
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3002004 Ben 2004 C op 2004 D ie 2004 H ay
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3002004 Pet 2004 Sch 2004 W il 2005 G eb
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3002005 L ic 2006 Ben 2006 C op 2006 G eb
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3002006 R ie
0.4 0.6 0.8 1
2007 G eb
0.4 0.6 0.8 1
2007 H ac
0.4 0.6 0.8 1
2007 San
Suffic iency Index
Opt
ima
l N (
kg h
a-1)
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3002004 Ben 2004 C op 2004 D ie 2004 H ay
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3002004 Pet 2004 Sch 2004 W il 2005 G eb
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3002005 L ic 2006 Ben 2006 C op 2006 G eb
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3002006 R ie
0.4 0.6 0.8 1
2007 G eb
0.4 0.6 0.8 1
2007 H ac
0.4 0.6 0.8 1
2007 San
Suffic iency Index
Optimal N (kg ha-1
)
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3002004 Ben 2004 C op 2004 D ie 2004 H ay
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3002004 Pet 2004 Sch 2004 W il 2005 G eb
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3002005 L ic 2006 Ben 2006 C op 2006 G eb
0.4 0.6 0.8 1
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3002006 R ie
0.4 0.6 0.8 1
2007 G eb
0.4 0.6 0.8 1
2007 H ac
0.4 0.6 0.8 1
2007 San
Sufficiency Index
Op
tima
l N (
kg h
a-1
)
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3002004 Ben 2004 C op 2004 D ie 2004 H ay
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3002005 L ic 2006 Ben 2006 C op 2006 G eb
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3002006 R ie
0.4 0.6 0.8 1
2007 G eb
0.4 0.6 0.8 1
2007 H ac
0.4 0.6 0.8 1
2007 San
Suffic iency Index
Opt
ima
l N (
kg h
a-1)
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3002004 Ben 2004 C op 2004 D ie 2004 H ay
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3002004 Pet 2004 Sch 2004 W il 2005 G eb
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3002005 L ic 2006 Ben 2006 C op 2006 G eb
0.4 0.6 0.8 1
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3002006 R ie
0.4 0.6 0.8 1
2007 G eb
0.4 0.6 0.8 1
2007 H ac
0.4 0.6 0.8 1
2007 San
Suffic iency Index
Optimal N (kg ha-1
)
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3002004 Ben 2004 C op 2004 D ie 2004 H ay
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3002004 Pet 2004 Sch 2004 W il 2005 G eb
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3002005 L ic 2006 Ben 2006 C op 2006 G eb
0.4 0.6 0.8 1
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3002006 R ie
0.4 0.6 0.8 1
2007 G eb
0.4 0.6 0.8 1
2007 H ac
0.4 0.6 0.8 1
2007 San
Sufficiency Index
Op
tima
l N (
kg h
a-1
)
0 0.5 1.0
Optimal N Rate as a Function of Canopy Reflectance
SI =
VISNIR (N ref)
VISNIR (target)
SI =
VISNIR (N ref)
VISNIR (target)
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3002004 Ben 2004 Cop 2004 D ie 2004 Hay
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3002004 Pet 2004 Sch 2004 W il 2005 G eb
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3002005 Lic 2006 Ben 2006 Cop 2006 G eb
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0.4 0.6 0.8 1
2007 G eb
0.4 0.6 0.8 1
2007 Hac
0.4 0.6 0.8 1
2007 San
Suffic iency Index
Opt
imal
N (
kg h
a-1)
Optimal N Rate as a Function of Canopy Reflectance
Developing Optimized-profit Algorithms Relative To Conventional Producer N Rates Inputs:
• Values and quadratic response curves from optimal N rate modeling
• Field-measured SI values for each response block
• A set price of corn grain and N fertilizer
• A producer prescribed N rate for each site-year
Variables that were optimized during the iterative phase included:
• Slope and intercept values for the N recommendation, based on the equation: Nrec = a(1/SI) + b (SI = sufficiency index)
• The minimum N rate to be applied by the algorithm
• The maximum N rate to be applied by the algorithm
The analysis was repeated on 12 subsets of data, based upon factorial combinations of the following two variables:
• Three soil types & all soils combined
• N applied at planting (0 kg N/ha, 67 kg N/ha, both combined)
corn grain price ($ kg-1) N fertilizer cost 0.08 0.12 0.16 0.20 0.24 0.28 0.32 N fertilizer cost ---- $ kg-1 ---- ------------------------FGR ----------------------- ---- $ lb-1 ----
0.44 6 4 4 3 3 2 2 0.20 0.66 8 7 6 5 4 4 3 0.30 0.88 11 9 7 6 6 5 4 0.40 1.10 14 11 9 8 7 6 6 0.50 1.32 17 13 11 10 8 7 7 0.60 1.54 20 16 13 11 10 9 8 0.70 1.76 22 18 15 13 11 10 9 0.80 1.98 25 20 17 14 13 11 10 0.90 2.21 28 22 19 16 14 12 11 1.00
2.00 3.00 4.00 5.00 6.00 7.00 8.00 corn grain price ($ bushel-1)
Fertilizer To Grain Ratio (FGR) Using SI Units For Various Combinations Of N
Fertilizer And Corn Grain Prices
0.4 0.6 0.8 1Suffic iency Index
0
50
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N R
eco
mm
enda
tion
(kg
ha
-1)
FGR16
4.7
Minimum N
Increasing N
Maximum N
General Shape of N Algorithm
Optimal N Rate as a Function of Canopy Reflectance
Profit Potential Using the Canopy SensorsAnd Derived Algorithms Relative to
Fertilizer to Grain Ratio (FGR)
Nitrogen Saved Using the Canopy SensorsAnd Derived Algorithms Relative to
Fertilizer to Grain Ratio (FGR)
N applied at Planting (kg ha-1)
Days after planting / Growth stage
0 45 246
23 DAP V4
NDVI: 0.36 ISR: 0.47 SPAD: 39.8
NDVI: 0.36 ISR: 0.47 SPAD: 41.1
NDVI: 0.36 ISR: 0.47 SPAD: 43.7
41 DAP
V7
47 DAP
V10
56 DAP
V13
N applied at Planting (kg ha-1)
Days after planting / Growth stage
0 45 246
23 DAP V4
NDVI: 0.36 ISR: 0.47 SPAD: 39.8
NDVI: 0.36 ISR: 0.47 SPAD: 41.1
NDVI: 0.36 ISR: 0.47 SPAD: 43.7
41 DAP
V7
NDVI: 0.53 ISR: 0.31 SPAD: 48.6
NDVI: 0.53 ISR: 0.31 SPAD: 52.8
NDVI: 0.57 ISR: 0.28 SPAD: 58.8
47 DAP
V10
56 DAP
V13
N applied at Planting (kg ha-1)
Days after planting / Growth stage
0 45 246
23 DAP V4
NDVI: 0.36 ISR: 0.47 SPAD: 41.1
NDVI: 0.36 ISR: 0.47 SPAD: 43.7
41 DAP
V7
NDVI: 0.53 ISR: 0.31 SPAD: 48.6
NDVI: 0.53 ISR: 0.31 SPAD: 52.8
NDVI: 0.57 ISR: 0.28 SPAD: 58.8
47 DAP
V10
NDVI: 0.64 ISR: 0.22 SPAD: 49.9
NDVI: 0.66 ISR: 0.21 SPAD: 52.8
NDVI: 0.70 ISR: 0.18 SPAD: 57.6
56 DAP
V13
N applied at Planting (kg ha-1)
Days after planting / Growth stage
0 45 246
23 DAP V4
NDVI: 0.36 ISR: 0.47 SPAD: 41.1
NDVI: 0.36 ISR: 0.47 SPAD: 43.7
41 DAP
V7
47 DAP
V10
NDVI: 0.64 ISR: 0.22 SPAD: 49.9
NDVI: 0.66 ISR: 0.21 SPAD: 52.8
NDVI: 0.70 ISR: 0.18 SPAD: 57.6
56 DAP
V13
NDVI: 0.66 ISR: 0.21 SPAD: 45.1
NDVI: 0.68 ISR: 0.19 SPAD: 52.4
NDVI: 0.73 ISR: 0.16 SPAD: 59.8
Subtle Differences from the Perspectiveof a Canopy Sensor
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4 5 6 7 10 11 13 15
Growth Stage
Sen
sor
(rat
io)
0 at planting40 at planting210 at planting
30354045505560657075
2 4 6 8 10 12 14 16Growth Stage
SP
AD
no N45 kg N ha-1246 kg N ha-1
no N
45 kg N ha-1
246 kg N ha-1
no N
45 kg N ha-1
246 kg N ha-1
Chlorophyll meterChlorophyll meterActive light sourceActive light sourcecrop sensorscrop sensors
Summary of In-Field Plant Sensingfor Nitrogen Management
• A significant relationship between canopy sensor sufficiency index and optimal N rate was observed in about half of the field studies.
• Combined across all sites meaningful algorithms were created to give assurance that these sensors could be used for variable-rate N applications.
• Algorithms should be adjusted as fertilizer and grain prices vary.
• The primary advantages of sensor-based measurements is improved accuracy to site-specific crop need.
Fields and Situations Most Suitedfor Sensor-Based Variable Rate Nitrogen Applications
• Fields with extreme variability in soil type
• Fields experiencing a wet spring or early summer (loss of applied N) and where additional N fertilizer is needed (i.e., rescue N)
• Fields that have received recent manure applications
• Fields receiving uneven N fertilization because of application equipment failure
• Fields coming out of pasture, hay, or CRP management
• Fields of corn-after-corn, particularly when the field has previously been cropped in a different rotation
• Fields following a droughty growing season
• Fields with extreme variability in soil type
• Fields experiencing a wet spring or early summer (loss of applied N) and where additional N fertilizer is needed (i.e., rescue N)
• Fields that have received recent manure applications
• Fields receiving uneven N fertilization because of application equipment failure
• Fields coming out of pasture, hay, or CRP management
• Fields of corn-after-corn, particularly when the field has previously been cropped in a different rotation
• Fields following a droughty growing season
0.4 0.6 0.8 1 1.2 1.4
Suffic iency Index
0
100
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300
EO
NR
(kg
ha
)
P rofit ($ ha )
$156.60 $100.00 $50.00 $25.00 $0.00 $-25.00 $-50.00 $-100.00
M ean P rofit = 22.98 $ ha
A ll so il typesE arly N = 0
corn = 0 .24 $ kgn itrogen = 1 .32 $ kgs lope = 416 kg hain te rcept = -348 kg ham in N = 101 kg ham ax N = 180 kg ha
-1
-1 -1
-1
-1
-1
-1
-1
-1
An Example of a N Rate Recommendation Algorithm Shown Relative to Canopy Sensor-Based Sufficiency Index (SI).