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Dr. Newell Kitchen - Tools For Managing Nitrogen
The document discusses the challenges of nitrogen management in corn production, highlighting the over-application of nitrogen fertilizers and the resulting losses. It evaluates various nitrogen recommendation tools, emphasizing the benefits of using soil and crop measurements for improved accuracy. Additionally, it underscores the importance of adaptive tool development that can address variability in weather and soil conditions for better decision-making in nitrogen applications.
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Dr. Newell Kitchen - Tools For Managing Nitrogen
- 1. Tests, Models, and SensingTools: Which is Best for Corn Nitrogen Decisions? Newell R. Kitchen USDA-ARS Cropping Systems and Water Quality Research Unit Columbia, Missouri
- 2. What is ina Decision? โข The average number of remotely conscious decisions an adult makes each day is ~35,000 โข Grower surveys often list N fertilizer management among the more challenging decisions of modern corn production
- 3. Nitrogen Cycle inAgriculture Fields
- 4. How much Nthis year?
- 5. What happens ifwe are not close to the right rate? N Rate โ EONR (lb N/a) โข When applications are >30 lbs N/ac over EONR, every lb N applied = N lb lost โข 20-40% of US corn acres have N over- application >30 lbs N/ac โข 90 m US corn ac/year โข Mean over-application of 60 lbs N/ac โข 405,000 tons of N lost/yr Chris Bandura University of Wisconsin
- 6. 585 barges ofurea-N
- 7. PPNT Pre-Plant SoilNitrate Test SDNT Side-Dress Soil Nitrate Test Crop Growth Models Empirical-Based Models Canopy Sensing Soil Tests Encirca N Service Maize-N Climate: Nitrogen Advisor Adapt-N Which is the Most Reliable Corn Nitrogen Recommendation Tool?
- 8. Maximum Return toNitrogen (MRTN)
- 9. 9 30 0 50 100 150 200 250 300 350 0 50 100150 200 250 300 Yield,bu/acre N rate, lb N/acre 35 on-farm trials Soy-Corn 2015 Optima MRTN Courtesy of Emerson Nafziger, UI
- 10. PPNT Pre-Plant SoilNitrate Test SDNT Side-Dress Soil Nitrate Test Crop Growth Models Empirical-Based Models Soil Tests Encirca N Service Maize-N Climate: Nitrogen Advisor Adapt-N Side-by-Side Comparison Canopy Sensing
- 12. Public-Private Partnering for ImprovingPerformance of Corn Nitrogen Fertilization Tools James Camberato Purdue University Emerson Nafziger University of Illinois Carrie Laboski University of Wisconsin Fabiรกn Fernรกndez University of Minnesota David Franzen North Dakota St. University John Sawyer Iowa State University Richard Ferguson University of Nebraska Newell Kitchen USDA-ARS University of Missouri Paul R. Carter
- 13. Project Data Evaluate DuPont Pioneer proprietary products and decisionaids Evaluate public-domain decision aid tools, develop agronomic science for improved crop N management, train new scientists, and publish results University
- 14. Research Locations 16Locations/Year Total 49 Temperature Precipitation
- 15. โฆ. a widearray of weather and soils conditions.
- 16. N Treatments (lbs/acre) Measurements Crop PlantN (VT & R6) Canopy reflectance (V9) Grain yield and moisture Soil EC mapping (VerisTM) Soil sampling (3x) Soil moisture ( TRT 3+16) Climate Precipitation Temperature Solar radiation Standardized Design Planting Split (plt+V9) 0 40+40 40 40+80 80 40+120 120 40+160 160 40+200 200 40+240 240 80+80 280 80+160
- 17. What was thecorrect N rate? Best-fit model for Economic Optimal N Rate (EONR)
- 18. Variation in EconomicOptimal N Rate 2014 2015 2016
- 19. Economic Optimal NitrogenRate (EONR)
- 20. Tools Tested โข AtPlanting โ State-Specific Yield Goal โ Pre-plant Soil Nitrogen Test (PPNT) โ Maximum Return to Nitrogen (MRTN) โ Crop model (Maize-N) โข Split (40lbs/a at planting + top dress) โ State-Specific Yield Goal โ Side-dress Soil Nitrogen Test (PSNT) โ Maximum Return to Nitrogen (MRTN) โ Crop model (Maize-N) โ Canopy Reflectance - MU algorithm
- 21. r2 = 0.01r2= 0.01 r2 = 0.16 r2 = 0.23
- 22.
- 23.
- 24. 0 lbs N/A40 lbs N/A PSNT Tools
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- 28. Courtesy of IowaState Extension
- 31. 31 Encircaโข Nitrogen ManagementService. Cronus Crop Model Target N Level Current and forecast (Soil N to date) Multi-year historical (Potential N outcomes) Local Weather Cronus Crop Model N Recommendation Planned Application Date N Source/application method Current Soil N per DZ Target N RequiredERU -Soil Yield Goal O.M. Soil Criteria Productivity Soil Water Hybrid Seeding Rate Initial N Manure N applications Inhibitor Residue Credit Tillage Tile Irrigation Management Decision Zone
- 32. 32 Environmental Response Units (ERU) ERUโsImprove Correlation to Measured Yield 300%! โข ERUโs developed using high resolution digital elevation models (e.g. LIDAR) Watershed Information, SSURGO Data โข Are key input to defining field management zones โข Process continues to be improved as new data sources emerge
- 33. 33 Cronus Crop Modelโ soil nitrogen dynamics V T V T Models are a potential tool to improve nitrogen management Good agreement between model and measured soil NO3 But models alone are not perfect! Representative response graphs (of graphs from 360+ sampled blocks ) โ PRNT sites
- 34. An Objective, Science-basedAssessment & Education Program for Nutrient-Use Efficiency Tools & Products Courtesy of Dr. James Schepers
- 35. 2015 Encirca NitrogenInnovation Trials 124 Locations Application Timing 2015 EncircaSM Nitrogen Innovation Trials
- 36. Managing Variability with EncircaSMNitrogen Service Good Mineralization / High N Loss Good Mineralization / Low N Loss
- 37. $100 $50 $0 $50 $100 $150 $200 $250 1 11 2131 41 51 61 71 81 91 101 111 PartialProfitability($/A) Field Trials Adapt โ N . . . Partial Profitability 2011-2014 ~5 bu/A
- 38. Which tool shouldI use? โข Many of the current publicly-available N recommendation tools donโt work well when EONR is low (< 100 lbs N/ac) or high (> 220 lbs N/ac). โข Tools that use soil and/or crop measurements on the fields of interest generally work better (e.g., PPNT/PSNT, canopy reflectance). โข Fields that historically show variation in greenness on wet years (look at Google Earth), deserve a tool that can address spatial soil variation. โข Tool development and validation are needed that are adaptive to weather and soil interactions (e.g., modeling, canopy reflectance). โข Using on-farm strip trials over several years is an excellent ways to judge your current tool (e.g., strips with ยฑ 30 lbs N/ac + current). โข If both ยฑ strips are within 5 bu/ac of the current tool, then you are close to EONR and your tool is working fairly well โข If you donโt see a yield increase with +30 and donโt see a yield decrease with -30, then youโre likely over-applying (tool failure) โข If you see a yield increase with +30, then you are under-applying (tool failure)
- 39. N Application >>Corn Crop Need From Benton/Tama Nutrient Reduction Project
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- 41. Questions? Newell R. Kitchen 573-882-1114 KitchenN@Missouri.edu orNewell.Kitchen@ars.usda.gov
- 42. PPNT Pre-Plant SoilNitrate Test SDNT Side-Dress Soil Nitrate Test Crop Growth Models Empirical-Based Models Proximal Canopy Sensing Soil Tests Encirca N Services Maize-N Climate: Nitrogen Advisor Adapt-N Fusion