1. Annual ASA Meeting, Indianapolis
Adjusting Mid-Season Nitrogen Fertilizer Using a Sensor-Based Optimization Algorithm to Increase Use Efficiency in Corn
B. Tubana, R. Teal, K. Freeman, B. Arnall, B. Chung, O. Walsh, K. Lawles, C. Mack and W. Raun
Annual ASA Meeting, Indianapolis
9:30 am, Nov. 15, 2006

2. Presentation Outline Technology Developed by OSU
Background of the Study
Components of the Algorithm
Methodology
Results
Conclusion

3. Need to Improve NUE Cereal grain NUE averages only 33% worldwide
Rise in the price of fuel and N fertilizer
Increase environmental risk

4. Applications

5. Success of the Technology
A 15 % increase in wheat NUE was achieved compared with conventional methods (OSU 2002, Agronomy Journal 94:815).

6. Yield Potential Equation
(Teal et al., 2006)

7. Algorithm Components
Nitrogen Fertilization Optimization Algorithm (NFOA)
YP Estimates of corn grain yield potential using NDVI and cumulative GDD
RI N Responsiveness estimated using NDVI in the N Rich Strip and NDVI in the farmer practice or check
CV Coefficient of variation determined from NDVI sensor readings collected in each plot

8. Components of Algorithm
YPN = (YP0*RI)
N Rate =

9. Capability of Algorithm
YP0 does not rely on historical data but rather is a simple predictive model. This approach uses seasonally dependent data capable of predicting differing yield potentials and adjusting N rates accordingly.
YP0 changes every year as does RI.

10. YP0 and RI are independent of one another (on-farm trials 2002-2005)

11. RICV-NFOA Spatial variability can be masked by larger plants
Do these areas have the same yield potential?
NDVI= 0.60
NDVI= 0.60
CV= 23
CV= 10

12. RI-NFOA and RICV-NFOA RI-NFOA RICV-NFOA YPmax YPN YPN YP0 CV CV
Grain Yield
INSEY
YP0
RI-NFOA
RICV-NFOA CV
YPN
YPN
RI = 1.5 CV
RI = 2.0
RI = 2.0
YPmax

13. Description of NFOA RI-NFOA – consists of YP0 and RI YPN = YP0*RI
RICV-NFOA – consists of YP0, RI and CV

15. Objectives
To evaluate different nitrogen fertilization optimization algorithms for prescribing mid-season fertilizer N.
To determine the optimum resolution for treating spatial variability in corn.

16. Methodology
Established in 2004 at 3 sites (1-irrigated, 2-rainfed system) in Oklahoma.
Employed RCB Design with 3 replications

17. Mid-Season Topdress Rate kg ha-1
Treatment Structure
TRT
Preplant N
kg ha-1
Mid-Season Topdress Rate kg ha-1
Resolution m2 1 - 2 67 3
134 4 5 6 7
RICV- NFOA
0.34 8
RICV-NFOA 9
Flat RICV-NFOA 10 11
2.32 12
RI-NFOA 13

18. Results With Preplant Nitrogen
Common Flat Rate versus Algorithms at Efaw site from
With Preplant Nitrogen
Treatment
Preplant
kg ha-1
Topdress
Grain Yield
Mg ha-1
Nitrogen Use Efficiency %
2004
2005
2006
Check
9.5
6.2
5.6 -
Common Flat Rate 67
13.4
10.3
9.6 48 57 38
67-RICV 25
127 52
13.9
12.0
11.1 31
67-RICV flat
13.3
11.5 35 49
67-RI 13 66 24
14.0
12.4
11.9 77 74 79

19. Results
Common Flat Rates versus Algorithms at Efaw site from
Without Preplant Nitrogen
Treatment
Topdress
kg ha-1
Grain Yield
Mg ha-1
Nitrogen Use Efficiency %
2004
2005
2006
Check
9.5
6.2
5.6 -
Common Flat Rate 67
13.1
9.9
9.4 71 69 73
134
11.8
10.2
8.8 35 44 34
0-RICV 59
100 58
11.2
8.6
6.9 32 50 37
0-RICV flat
13.5
9.1 51
0-RI 17 66 48
12.9
10.1
9.2 79 83

20. Nitrogen Use Efficiency
Results
RICV- versus RI-NFOA at Efaw from
With Preplant N
Algorithm
Resolution m2
Total N Applied
Kg ha-1
Grain Yield
Mg ha-1
Nitrogen Use Efficiency %
2004
2005
2006
Check -
9.5
6.2
5.6
RICV-NFOA
0.34 25
127 52
13.9
12.0
11.1 31 57
flat
13.3
11.5
10.3 35 49 48
2.32
132 56
11.4
10.1 46 54
RI-NFOA 13 66 24
14.0
12.4
11.9 77 74 79

21. Results On-average * CFR : Common Flat Rate TRT Description
Total N Applied
kg ha-1
Grain Yield
Mg ha-1
NUE, % 1
Check
5.5 - 2
*CFR-topdress 67
8.2 59 3
134
8.5 40 4
*CFR-split
9.3 48 5
*CFR-preplant
8.0 56 6
9.1 44 7
RICV-NFOA 66
7.5 49 8
131 43 9
Flat RICV-NFOA
7.8 51 10
8.9 42 11
RICV-NFOA-2.32
133
8.8 46 12
RI-NFOA 61
8.3 63 13
119
9.6
* CFR : Common Flat Rate

22. Summary
NUE was generally higher when mid-season N rates were generated by NFOA compared with flat farmer rates.
Increased NUE was attributed to the lower N rates applied.

23. Summary
Use of RI NFOA resulted in a higher increase in NUE than RICV NFOA.
There was limited benefit of treating spatial variability at the high resolution (0.34 m2, RICV algorithm).
NFOA approaches didn’t project high N rates that did not affect increased yields.

24. Conclusions
Functional N rate algorithm developed for corn can increase NUE.
Applications
- Sensor Based N Rate Calculator
- Variable Rate Technology (0.4m2)

25. THANK YOU!