![Page 1: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/1.jpg)
Missouri algorithm for N in corn
Peter Scharf, Newell Kitchen, and John Lory
University of Missouri and USDA-ARS
![Page 2: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/2.jpg)
Missouri Algorithm Based on direct empirical relationship
between measured reflectance and measured optimal N rate Site characteristics
Very compatible with current sensor group approach We will likely use the algorithms that will be
developed from group activities
![Page 3: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/3.jpg)
Missouri Algorithm Original calibration: Cropscan passive at V6
Green, Red edge, Blue-green best Green/Infrared best combination
Optimal N rate = 330 * (G/NIR)target/(G/NIR)high N – 270 Works with either 0 or 100 N applied preplant
Tentatively applied with Crop Circle active sensor Subsequent research agrees fairly well
![Page 4: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/4.jpg)
Relationship between optimal N rate and sensor measurements
0
50
100
150
200
250
0.9 1.1 1.3 1.5 1.7
Green/near infrared relative to high-N plots
Op
tim
um
sid
ed
ress
N ra
te
Y = 330(X) – 270
![Page 5: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/5.jpg)
Greenseeker Values swing more widely than Crop Circle
over the same range of corn N status Need equation with smaller slope
June 20 Ratio Comparison
y = 0.801x + 0.0723
R2 = 0.9450.10
0.15
0.20
0.25
0.30
0.10 0.15 0.20 0.25 0.30
GS Red/NIR ratio
CC
Am
ber
/NIR
ra
tio
![Page 6: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/6.jpg)
Growth stages Original calibration was for V6
Also use for V7 Chlorophyll meter, sensor research show that
slope decreases as season progresses Decreased slope to 3/4 for V8 to V10
![Page 7: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/7.jpg)
Current Missouri Algorithms
SensorGrowth stage Equation
Crop Circle V6-V7 330 * (V/NIR)t/(V/NIR)hiN - 270
Crop Circle V8-V10 250 * (V/NIR)t/(V/NIR)hiN - 200
Greenseeker V6-V7 220 * (V/NIR)t/(V/NIR)hiN - 170
Greenseeker V8-V10 170 * (V/NIR)t/(V/NIR)hiN - 120
![Page 8: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/8.jpg)
On-farm demos using Missouri algorithms
7 in 200412 in 200519 in 200628 in 2007
![Page 9: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/9.jpg)
21 with USDA Spra-Coupe
![Page 10: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/10.jpg)
35 with producer-owned applicators35 with producer-owned applicators
![Page 11: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/11.jpg)
10 with retailer-owned applicators
![Page 12: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/12.jpg)
Kansas producer 2006: 4000 Kansas producer 2006: 4000 acres of corn fertilized in six acres of corn fertilized in six days using high-clearance days using high-clearance spinner, sensors, & Missouri spinner, sensors, & Missouri algorithmalgorithm
![Page 13: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/13.jpg)
On-farm demonstrations 32 on-farm demonstrations 2004-2006 with
producer rate & sensor variable-rate side-by-side and replicated
Average N savings = 31 lb N/acre Average yield loss = 1.7 bu/acre Yield & N economics
$2 to $10/ac benefit depending on prices used Doesn’t count technology & management costs
![Page 14: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/14.jpg)
On-farm demonstrations Complication: sensor values change during
the day Probably mainly due to changes in:
Canopy architecture Internal leaf properties External leaf properties
![Page 15: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/15.jpg)
Leaf wetness effect on sensor values
0.6
0.65
0.7
0.75
0.8
0.85
0.9
6:2
7
6:5
5
7:2
3
7:5
1
8:1
9
8:4
7
9:1
5
9:4
3
10
:11
10
:39
11
:07
11
:35
12
:03
12
:31
12
:59
13
:27
13
:55
14
:23
14
:51
15
:19
15
:47
16
:15
16
:43
17
:11
17
:39
18
:07
18
:35
19
:03
19
:31
19
:59
20
:41
Time on 10 July 2006
ND
VI
40 inch
10 inch
20 inch
RainDew
RainDew
![Page 16: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/16.jpg)
Why diurnal changes in sensor values?Leaf wetness is the only reason we’re
sure ofWet leaves are darkerNeed to re-measure high-N reference
when leaf wetness changesReference strips perpendicular to rows
can make this feasible
![Page 17: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/17.jpg)
Reference stripsPerpendicular to rows?
Tried in on-farm demo in 2007 Real-time update of high-N reference
value Worked great
Apply with 4-wheeler + spinner?Aerial?
![Page 18: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/18.jpg)
Diurnal changes: other impacts
We may consider changing to an algorithm based on NDVI Especially Greenseeker
Less sensitive to diurnal changes in sensor values
![Page 19: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/19.jpg)
Diurnal sensitivity of N recs: Greenseeker/cotton example
N RATE BASED ON NDVI (REF= 8- 8:10)
0
20
40
60
80
100
120
140
5:00 7:24 9:48 12:12 14:36 17:00 19:24
TIME
N R
AT
E
N RATE BASED ON VIS/NIR (REF= 8- 8:10)
0
20
40
60
80
100
120
140
5:00 7:24 9:48 12:12 14:36 17:00 19:24
TIME
N R
AT
E
NDVI-based
VIS/NIR-based
![Page 20: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/20.jpg)
Diurnal sensitivity of N recs: Crop Circle/cotton example
NDVI-based
VIS/NIR-based
NRATE BASED ON NDVI (REF= 8-8:10)
0
20
40
60
80
100
120
140
5:00 7:24 9:48 12:12 14:36 17:00 19:24
TIME
N R
AT
E
NRATE BASED ON VIS/NIR (REF= 8-8:10)
0
20
40
60
80
100
120
140
5:00 7:24 9:48 12:12 14:36 17:00 19:24
TIME
N R
AT
E
![Page 21: Missouri algorithm for N in corn Peter Scharf, Newell Kitchen, and John Lory University of Missouri and USDA-ARS](https://reader035.vdocuments.us/reader035/viewer/2022062515/56649c9b5503460f949596fc/html5/thumbnails/21.jpg)