Proceedings of the 3 rd Annual Nitrogen: Minnesota s Grand Challenge & Compelling Opportunity Conference

Transcription

1 Proceedings of the 3 rd Annual Nitrogen: Minnesota s Grand Challenge & Compelling Opportunity Conference Do not reproduce or redistribute without the written consent of author(s)

2 Upgrade Your Corn Nitrogen Management Using Precision Agriculture Newell R. Kitchen USDA-ARS Cropping Systems and Water Quality Columbia, Missouri

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4 Yield, bu/acre on-farm trials Soy-Corn 2015 Optima MRTN N rate, lb N/acre 30 Courtesy of Emerson Nafziger, UI 4

5 5 Courtesy of Emerson Nafziger, UI

6 Soil Resource Interactions of the 3 Management Weather

7 Abundant and Well-Distributed Rainfall (Tremblay et al., 2012)

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10 Photo courtesy of Peter Scharf

11 courtesy of Peter Scharf

12 Photo courtesy of Peter Scharf

13 EONR for Indiana Sand Sites EONR (lbs N/Ac) Sand- Plant Sand- Topdress

14 The Soil Factor (Tremblay et al., 2012)

15 N N Fertilizer N Fertilizer 180 lbs 40 lbs

16 When looking at the within-field corn N fertilizer need from numerous Missouri fields: The average field ranged 88 lbs N/acre. 32% of fields had within-field needs that varied by more than 100 lbs N/acre. With all this uncertainty, how do we know how much N to apply, when, and where?

17 Crop Growth Modeling Courtesy of DuPont Pioneer

18 Crop Simulation Models (G x E x M) E G E M 18

19 What decision tools perform best for making corn N fertilizer rate recommendations? Where do they work best? When do they work best? Empirical-Based Models Proximal Canopy Sensing Crop Growth Models Encira Maize-N Climate: Nitrogen Advisor Adapt-N Remote Imagery Soil Tests PPNT Pre-Plant Soil Nitrate Test SDNT Side-Dress Soil Nitrate Test

20 Performance and Refinement of In-season Corn Nitrogen Fertilization Tools David Franzen North Dakota St. University Fabián Fernández University of Minnesota John Sawyer Iowa State University Richard Ferguson University of Nebraska Newell Kitchen USDA-ARS University of Missouri Carrie Laboski University of Wisconsin Emerson Nafziger University of Illinois James Camberato Purdue University Paul R. Carter John Shanahan

21 Data from Performance and Refinement of In-season Corn Nitrogen Fertilization Tools Evaluate DuPont Pioneer proprietary products and decision aids University Evaluate public-domain decision aid tools, develop agronomic science for improved crop N management, train new scientists, and publish results

22 What is needed? Datasets over a wide range of soil and weather scenarios that allow for calibration and/or validation of decision-support tools used in making corn N fertilizer recommendations.

23 Standarized Design 16 Locations/Year Total 49 N Treatments (lbs/acre) Planting Split (plt+v9) Climate Precipitation Temperature Solar radiation Measurements Soil EC mapping (Veris TM ) Soil sampling (3x) Soil moisture ( TRT 3+16) Crop Plant N (VT & R6) Canopy reflectance (V9) Grain yield and moisture

24 Precipitation Temperature

25 49 Research Sites over 8 States

26 What Tools were Evaluated? Farmer s Historical Practice Generic Yield Goal - (1.2 * YG) State Recommendation Yield Goal Maximum Return to Nitrogen (MRTN) Pre-plant Soil Nitrogen Test (PPNT) Side-dress Soil Nitrogen Test (PSNT) Maize-N Canopy Reflectance - different algorithms

27 EONR and Yield at EONR (49 PRNT sites) EONR (lbs N/Ac) Yield at EONR (Bu/Ac) At Planting Topdress At Planting Topdress

28 EONR Agronomic Efficiency (46/49 PRNT sites) EONR Agronomic Efficiency (Bu/lb N) At Planting Topdress

29 140 At Side-Dress N Tools Improved by Soil Information 120 Tool Unadjusted Tool + Soil (TN) RMSE, lbs N ac MRTN IL PSNT WI PSNT MN YG IN YG MO YG

30 140 At Side-Dress N Tools Improved by Soil Information 120 Tool Unadjusted Tool + Soil (TN) RMSE, lbs N ac % 45% 45% 46% 55% 45% 39% 39% 29% 7% 48% 42% 0 MRTN IL PSNT WI PSNT MN YG IN YG MO YG

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32 Sensor Algorithm Performance N Rec (lbs N ac -1 )

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35 RMSE: 68 RMSE: RMSE: 54 RMSE: 48 Unadjusted SDI SDI + SSURGO SDI + Measured

36 100 % of Sites within 27 lbs ac -1 of EONR

37 Tool s Strengths are at Different Scales Model Soil and Weather Canopy Sensor Photo courtesy of Henrietta Christensen

38 Empirical-Based Models Crop Growth Models Encira Maize-N Climate: Nitrogen Advisor Adapt-N Tool Fusion Proximal Canopy Sensing Soil Tests PPNT Pre-Plant Soil Nitrate Test SDNT Side-Dress Soil Nitrate Test

39 Traditional N Tools vs Precision Agriculture Tools

40 Acknowledgements / Questions

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