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OSU Corn Algorithm

OSU Corn Algorithm. Can Yield Potential (similar to “yield goals”) be Predicted MID-SEASON? Is it better than a preplant N decision?. NDVI at F5. =. INSEY. Days from planting to sensing, GDD>0. Winter Wheat. Units: biomass, kg/ha/day, where GDD>0. Predicting Yield Potential in Corn.

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OSU Corn Algorithm

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  1. OSU Corn Algorithm

  2. Can Yield Potential (similar to “yield goals”) be Predicted MID-SEASON?Is it better than a preplant N decision?

  3. NDVI at F5 = INSEY Days from planting to sensing, GDD>0 Winter Wheat Units: biomass, kg/ha/day, where GDD>0

  4. Predicting Yield Potential in Corn NDVI, V8 to V10 = INSEY Days from planting to sensing CORN

  5. Long-Term Winter Wheat Grain Yields, Lahoma, OK

  6. Response to Fertilizer N, Long-Term Winter Wheat Experiment, Lahoma, OK “After the FACT” N Rate required for “MAX Yields” Ranged from 0 to 140 lbs N/ac

  7. Can RI be Predicted in Wheat?.... YES

  8. Can RI Be Predicted in Corn?... YES MullenAgronomy Journal 95:347-351 (2003)Winter Wheat

  9. Improved Prediction of Yield PotentialSuperPete to the Rescue

  10. All GDD Class Yield Prediction Equations for Corn

  11. RI-NFOAYPN=YP0 * RI YP0 YPN YPN YPMAX RI=1.5 RI=2.0 Grain yield INSEY (NDVI/days from planting to sensing) Nf = (YP0*RI) – YP0))/Ef • The mechanics of how N rates are computed are really very simple • Yield potential is predicted without N • The yield achievable with added N is #1 times the RI • Grain N uptake for #2 minus #1 = Predicted Additional N Need • Fertilizer Rate = #3/ efficiency factor (usually 0.5 to 0.7)

  12. INSEY works, but needs to be more robust • Problems: • Extremely early season prediction of yield can be overestimated • (Feekes 4, wheat) • (V6, corn) • Inability to reliably predict yield potential at early stages of growth should be accompanied by more risk averse prediction models (small slope)

  13. Combined • RI = (NDVI-N Rich Strip/NDVI-Farmer Practice) • CoefA = (0.323123*Gdd2 - 77.8* Gdd + 5406) • CoefB = -0.0003469*Gdd2 + 0.08159*Gdd - 2.73372 • YP0 = (CoefA * exp(CoefB * NDVI-FP)) • If ((NDVI-N Rich Strip/NDVI-FP)< 1.72) • RI = (NDVI-N Rich Strip/NDVI-FP)*1.69 - 0.7 • If (RI<1) RI=1 • YPN = YP0*RI; • NRate = ((YPN-YP0)*0.0239/0.6) • Determine based on %N in the grain

  14. Variable Rate TechnologyTreat Temporal and Spatial Variability Returns are higher but require larger investment

  15. Just remember boys, you can always trust SuperPete!

  16. 3H2 + N2 2NH3 HABER BOSCH (1200°C, 500 atm) MICROBIAL/PLANT SINK GLOBAL WARMING ATMOSPHERE 15-40 kg/ha N2O NO N2 INDUSTRIAL FIXATION LIGHTNING, RAINFALL N2 FIXATION PLANT AND ANIMAL RESIDUES SYMBIOTIC NON-SYMBIOTIC MESQUITE RHIZOBIUM ALFALFA SOYBEAN BLUE-GREEN ALGAE AZOTOBACTER CLOSTRIDIUM MATERIALS WITH N CONTENT > 1.5% (COW MANURE) MATERIALS WITH N CONTENT < 1.5% (WHEAT STRAW) FERTILIZATION 10-80 kg/ha PLANT LOSS AMINO ACIDS MICROBIAL DECOMPOSITION 0-50 kg/ha NH3 AMMONIA VOLATILIZATION IMMOBILIZATION AMINIZATION HETEROTROPHIC ORGANIC MATTER R-NH2 + ENERGY + CO2 BACTERIA (pH>6.0) FUNGI (pH<6.0) pH>7.0 R-NH2 + H2O FIXED ON EXCHANGE SITES AMMONIFICATION NH2OH IMMOBILIZATION R-OH + ENERGY + 2NH3 N2O2- Pseudomonas, Bacillus, Thiobacillus Denitrificans, and T. thioparus 2NH4+ + 2OH- MINERALIZATION + NITRIFICATION +O2 NO2- Nitrosomonas DENITRIFICATION NO3- POOL NITRIFICATION 2NO2- + H2O + 4H+ OXIDATION STATES Nitrobacter + O2 DENITRIFICATION LEACHING LEACHING VOLATILIZATION NITRIFICATION ADDITIONS NH3 AMMONIA -3 NH4+ AMMONIUM -3 N2 DIATOMIC N 0 N2O NITROUS OXIDE 1 NO NITRIC OXIDE 2 NO2- NITRITE 3 NO3- NITRATE 5 Joanne LaRuffa Wade Thomason Shannon Taylor Heather Lees Department of Plant and Soil Sciences Oklahoma State University TEMP 50°F LEACHING LEACHING LOSSES OXIDATION REACTIONS LEACHING REDUCTION REACTIONS pH 7.0 0-40 kg/ha

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