Utilization of Crop Sensors to Detect Cotton Growth and N Nutrition
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Transcript Utilization of Crop Sensors to Detect Cotton Growth and N Nutrition
UTILIZATION OF CROP SENSORS
TO DETECT COTTON GROWTH
AND N NUTRITION
Tyson B. Raper, Jac J. Varco, Ken J. Hubbard,
and Brennan C. Booker
Plant and Soil Science Department
Mississippi State University
INTRODUCTION
N in cotton production
– Recent increase in fertilizer costs
– Deficiency limits yield and lowers quality
– Excess N causes
rank growth
boll rot
difficulty in harvesting
increased need for growth regulators, insecticides, and defoliants
Variable Rate N
– Increase Nitrogen Use Efficiency (NUE)
– Decrease environmental pollution
INTRODUCTION
Ground-Based Sensors
– Provide real-time cotton biomass and greenness
– Fertilize response to crop reflectance
Need
a more thorough understanding of
relationship between canopy reflectance, cotton
growth, and N nutrition.
OBJECTIVE
Examine the effectiveness of a ground-based
sensor to predict cotton
– Plant growth
– Leaf N
METHODS
Location
– Plant Science Research Farm, Mississippi State, MS
– Randomized complete block design
– 4 Treatments x 4 Replications
12 rows
125’ long
3 10’ alleys
38” row spacing
4 sub-locations
Courtesy: Web Soil Survey 2009
METHODS (CONT.)
Treatment
– 0, 40, 80, and 120 lb N/acre in a split-application
Planting (50%)
Early square (50%)
Cultural
–
–
–
–
No-till on beds
DPL BG/RR 445
No growth regulator applied
Low pest thresholds established and maintained
METHODS (CONT.)
Data Collection
– Reflectance
YARA N Sensor (YARA International ASA, Oslo, Norway)
METHODS (CONT.)
YARA N Sensor
–
–
–
–
–
–
–
–
–
Tractor mounted spectrometer
Wavelength Channels: 5, user selectable*
Wavelength range: 450-900 nm
Optical inputs: 4 reflectance, 1 irradiance
Acquisition interval: 1 second
Area scanned: 50-100 m²/s
Positioning Data: Trimble Pro XR
Speed: 3.5 mph
Bandwidth= ±5 nm
Source: YARA (Hydro Agri), tec5Hellma
METHODS (CONT.)
2009 EARLY FLOWER
0 lb N/Acre
40 lb N/Acre
80 lb N/Acre
120 lb N/Acre
YARA N Sensor
REFLECTANCE, %
60
40
20
0
400
500
600
700
WAVELENGTH, nm
800
900
METHODS (CONT.)
Data Collection
– Reflectance (cont.)
YARA N Sensor
– Set 76” above soil
– Sense entire field
– Views rows 2, 3, 4, 9, 10, 11
– Data Processing
Sub-plot locations
– Center of 15’ buffer
– 4 points selected
METHODS (CONT.)
Data Collection
– Sub-Location Plant Data
Plant Height
– 5 measured per sub-location
Leaf Sample
– 5 recently matured per sublocation
– % Leaf N
Whole Plant Sample
– Prior to defoliation
– Yield, total N uptake
METHODS (CONT.)
Sensing / Sampling Stages
Physiological Stages
–
–
–
–
–
–
–
Pre-Square
Early Square
2nd Week of Square
3rd Week of Square
Early Flower
2nd Week of Flowering
Peak flower
RESULTS
2009 SEASON N UPTAKE
2008 SEASON N UPTAKE
140
140
TOTAL N UPTAKE, lb N/acre
TOTAL N UPTAKE, lb N/acre
160
120
100
r ²=0.947
80
60
40
120
100
80
60
r ²=0.871
40
20
0
20
40
60
80
100
FERTILIZER RATE, lb N/acre
120
140
0
20
40
60
80
100
FERTILIZER RATE, lb N/acre
120
140
RESULTS
LINT YIELD 2009 MISSISSIPPI STATE
LINT YIELD 2008 MISSISSIPPI STATE
650
1100
r ²=0.97
LINT YIELD, lb/acre
LINT YIELD, lb/acre
600
1000
900
800
y=
r ²=0.98
550
500
450
400
700
0
40
80
FERTILIZER N RATE, lb/acre
120
350
0
20
40
60
80
100
FERTILIZER N RATE, lb/acre
120
140
RESULTS
2009 RAINFALL
300
300
250
250
200
200
1/100 in.
1/100 in.
2008 RAINFALL
150
150
100
100
50
50
0
Apr
May
Jun
Planting
N Application
Sensing
Jul
Aug
DATE
Sep
Oct
Nov
0
Apr
May
Jun
Planting
N Applications
Sensing
Jul
Aug
DATE
Sep
Oct
Nov
GNDVI vs PLANT HEIGHT
2008
2009
0.9
0.9
r ²=0.96
r ²=0.97
0.8
0.8
GNDVI
GNDVI
0.7
0.7
0.6
0.6
0.5
0.5
0.4
0.3
0.4
20
40
60
PLANT HEIGHT, cm
80
100
0
20
40
60
80
PLANT HEIGHT, cm
100
120
GNDVI vs LEAF N
2008 EARLY SQUARE
2009 EARLY SQUARE
0.54
0.52
0.58
0.56
r ²=0.22
r ²=0.67
0.54
0.52
0.50
GNDVI
GDNVI
0.50
0.48
0.46
0.48
0.46
0.44
0.44
0.42
0.40
0.42
0.38
0.40
0.36
3.6
3.8
4.0
4.2
LEAF N, %
4.4
4.6
4.8
3.2
3.4
3.6
3.8
4.0
LEAF N, %
4.2
4.4
4.6
GNDVI vs LEAF N
2008 EARLY FLOWER
2009 EARLY FLOWER
0.76
0.80
0.78
0.74
r ²=0.84
r ²=0.08
0.72
GNDVI
GNDVI
0.76
0.74
0.70
0.68
0.66
0.72
0.64
0.70
0.68
2.4
0.62
2.6
2.8
3.0
3.2
3.4
LEAF N, %
3.6
3.8
4.0
0.60
3.0
3.2
3.4
3.6
3.8
4.0
LEAF N, %
4.2
4.4
4.6
GNDVI vs LEAF N
2008 PEAK FLOWER
2009 PEAK FLOWER
0.80
0.82
0.78
r ²=0.90
r ²=0.87
0.80
GNDVI
GNDVI
0.76
0.74
0.78
0.76
0.72
0.74
0.70
2.6
2.8
3.0
3.2
3.4
LEAF N, %
3.6
3.8
4.0
4.2
0.72
2.8
3.0
3.2
3.4
3.6
3.8
LEAF N, %
4.0
4.2
4.4
GNDVI vs LEAF N
2008/2009 PEAK FLOWERING
0.84
r ²=0.86
0.82
GNDVI
0.80
0.78
0.76
0.74
0.72
0.70
0.68
2.5
3.0
3.5
LEAF N, %
4.0
4.5
RED EDGE INFLECTION
First Derivative of Reflectance Signature
2009 EARLY FLOWER
2009 EARLY FLOWER
0 lb N/Acre
40 lb N/Acre
80 lb N/Acre
120 lb N/Acre
0 lb N/Acre
40 lb N/Acre
80 lb N/Acre
120 lb N/Acre
1.1
dR/dl REFLECTANCE
dR/dl REFLECTANCE
1.0
0.8
0.6
0.4
0.2
1.0
0.9
0.0
0.8
500
600
700
WAVELENGTH, nm
800
700
710
720
WAVELENGTH, nm
730
RED EDGE INFLECTION
REIP calculated on a per plot basis
– Gaussian 4 Parameter Peak Equation
2nd WEEK OF SQUARE
– Utilize l
PLOT 3
700
710
720
740
1 July 2009
f=y0+a*exp(-.5*((x-x0)/b)^2)
0.45
0.40
dR/dlREFLECTANCE
0.35
0.30
0.25
0.20
0.15
0.10
690
700
710
720
730
WAVELENGTH, nm
740
750
REIP vs LEAF N
EARLY SQUARE
25 June 2009
2nd WEEK OF SQUARE
1 July 2009
710
713
WAVELENGTH, nm
WAVELENGTH, nm
712
708
706
r ²=0.864
704
711
710
r ²=0.695
709
708
707
702
3.2
3.4
3.6
3.8
4.0
LEAF N, %
4.2
4.4
4.6
706
3.2
3.4
3.6
3.8
4.0
LEAF N, %
4.2
4.4
4.6
4.8
REIP vs LEAF N
3rd WEEK OF SQUARE
8 July 2009
PEAK FLOWER
25 July 2009
715
716
714
WAVELENGTH, nm
WAVELENGTH, nm
714
713
712
r ²=0.805
711
710
712
r ²=0.731
710
708
709
708
3.4
706
3.6
3.8
4.0
4.2
LEAF N, %
4.4
4.6
4.8
5.0
3.2
3.4
3.6
3.8
LEAF N, %
4.0
4.2
REIP and NDVI
EARLY SQUARE
25 June 2009
EARLY SQUARE
25 June 2009
710
0.60
WAVELENGTH, nm
0.55
NDVI
0.50
r ²=0.650
0.45
0.40
708
706
r ²=0.864
704
0.35
702
0.30
3.2
3.4
3.6
3.8
4.0
LEAF N, %
4.2
4.4
4.6
3.2
3.4
3.6
3.8
4.0
LEAF N, %
4.2
4.4
4.6
CONCLUSIONS
GNDVI relationships with leaf N and plant height improve
through to peak flower.
Consistency across growing seasons supports the utility of
crop reflectance.
GNDVI and NDVI have the potential to be effective
measurements of plant growth in cotton.
REIP has the potential to be an effective measurement of N
status in cotton.
These results support previous REIP publications
(Buscaglia et al., 2002; Fridgen et al., 2004).
Questions?