1. Use of Alternative Concepts for Determining Preplant and Mid-Season N rates

2. Hodgen and Schepers 2007 Late emerging corn plants were non- responsive to different N fertilizer management strategies employed in this study. Managing N inputs per plant can increase NUE by 23% over broadcast applications of 168 kg N/ha applied either preplant or midseason (V9) and maintain yield and grain production per plant.

3. Hodgen and Schepers, 2007 Opportunities may exist to increase N use efficiency by capitalizing on detecting the variability of N demand per plant as indicated by differences in grain production within commercial fields. Ultrafine spatial N management schemes that are aimed at increasing NUE should operate at a resolution which reflects the horizontal diameter at which plants obtain the majority of their N supply.

5. Hodgen and Schepers, 2007 Similar N management techniques that attempt to capitalize on detecting differences in biomass (leaf area) production midseason could be used to estimate the relative yield differences between plants because of corn plants’ characteristic ability to maintain a harvest index of 50 to 55%

6. Hodgen and Schepers, 2007 The results of this study indicate that producers need to be aware of agronomic management practices that lead to uneven emergence can result in lower yield potential as 5% of yield was lost by just one day of delayed emergence. Results from this study indicate the early emerging corn plants produce more kernels per plant and are thus higher yielding and more competitive than late emerging plants. The economic impact from even small differences, such as four days, in uniformity of emergence between corn plants can contribute to lower yields of late emerging plants. The loss in yield would then lower the potential return to investment of not only seed expenditures but potential response to applied N fertilizer.

8. Hodgen, PhD Dissertation

9. Real-Time Use of Mesonet Weather Data for Refined GreenSeeker Sensor Based N Recommendations in Winter Wheat

10. On-Line N Recommendations 21 algorithms on-line, Sensor Based Nitrogen Rate Calculator (SBNRC) that are being used in Oklahoma, many Mid-Western States, Australia, India, Mexico, China, Argentina, and Canada. Algorithms now included on our OSU site encumber winter wheat, spring wheat, corn, canola, bermudagrass, sorghum, rice, and cotton (http://www.soiltesting.okstate.edu/SBNRC/SBN RC.php).http://www.soiltesting.okstate.edu/SBNRC/SBN RC.php

11. Figure 1. Digitized Mesonet maps of fractional water index for November 27, 2005 (left) and November 27, 2006 (right), at the 24 inch depth, Oklahoma (brown- dry, green-wet). Campbell Scientific, 229-L

13. Average Response to Applied N

14. Cubic Mg/hakg/ha NDVI FPNDVI N RichSum GDDCoefACoefBPred. Yield Fert CostGrain PriceNUE 0.50.717504.8935250.9881258.020296598020.296590.54.50.372 CoefACoefA = 6E-08x3 - 0.0002x2 + 0.1122x - 18.731 CoefBCoefB = -5E-08x3 + 0.0001x2 - 0.1183x + 31.78 YP0 = (CoefA * EXP (CoefB * NDVI)) x = cummulative GDD 40% NUE Olga12.6 kg grain/ kg N applied topdress0.828 lb N/bu27.05 lb loss for 1.0 lb N rate error OFIT29.5 kg grain/ kg N applied preplant Varvel24.2 kg grain/ kg N applied preplantOSU dataUNL data Yield Loss due to YP0 Rate Reductionerror % ErrorYP0YPNN Fert. RecDue to Errorbu/ac N Fert. ExpenseGrain RevenueGross Profit 0.0127.9230.1119.30.0 59.61035.4975.8 5.0121.5218.6113.36.01.32.756.61023.4966.7 10.0115.1207.1107.311.92.75.453.71011.3957.7 15.0108.7195.6101.417.94.08.050.7999.3948.6 20.0102.3184.195.423.95.410.747.7987.2939.5 25.095.9172.689.429.86.713.444.7975.2930.5 30.089.5161.183.535.88.016.141.7963.1921.4 35.083.1149.677.541.79.418.738.8951.1912.3 40.076.7138.171.647.710.721.435.8939.0903.3 45.070.3126.665.653.712.124.132.8927.0894.2 50.063.9115.059.6 13.426.829.8914.9885.1