Annual ASA Meeting, Indianapolis

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Presentation transcript:

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

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

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

Applications

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

Yield Potential Equation (Teal et al., 2006)

Algorithm Components Nitrogen Fertilization Optimization Algorithm (NFOA) YP0 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

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

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.

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

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

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

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

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.

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

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

Results With Preplant Nitrogen Common Flat Rate versus Algorithms at Efaw site from 2004-2006 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

Results Common Flat Rates versus Algorithms at Efaw site from 2004-2006 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

Nitrogen Use Efficiency Results RICV- versus RI-NFOA at Efaw from 2004-2006. 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

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

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.

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.

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

THANK YOU! www.nue.okstate.edu