Adapt-N: An On-Line Nitrogen

Transcription

1 1 Adapt-N: An On-Line Nitrogen Management Tool. Background / Results from 2011 Strip Trials Harold van Es / Jeff Melkonian / Bianca Moebius-Clune Iowa Soybean Association, On-Farm Network Conference Ames, Iowa February 16, 2012

2 2 Control Points for Improving N Use Efficiency and Reducing N Losses 1. Input management - increased N use efficiency rate, timing, formulation, placement 2. Transport mechanism (drainage, irrigation) 3. Remedial actions (filters, buffers, wetlands)

3 Many sources of variation in N availability generalized recommendations less applicable for corn N needs Sources of Variability: Organic amendments (manure, compost, etc.) Crop rotations Soil type differences Soil organic matter contents (management- induced soil change) Soil and crop management Temperature Precipitation

4 Predicting N Needs for Corn: Precision Improves over Time Main Factors: snow cover spring rains summer drought high intervention nonintervention low fall winter spring summer fall 4

5 Nitrogen Management with Computational Tools Move from generalized to site-specific recommendations Allows for adaptive, real-time management - Weather conditions - Local soils and crop management Universal process-based approach - Incorporates system complexity through relevant processes Low cost Allows for progressive refinement 5

6 PNM model: Basis of the Adapt-N Tool Linkage of two simulation models: Crop growth/n uptake model Sinclair, T.R., and R.C. Muchow Effect of nitrogen supply on maize yield: I. modeling physiological responses. Agronomy Journal 87: Soil processes model, LEACHN Hutson, J.L., R.J. Wagenet, and M.E. Niederhofer. 2003/2010. Leaching Estimation And Chemistry Model: a process-based model of water and solute movement, transformations, plant uptake, and chemical reactions in the unsaturated zone. Version 4. Dept of Crop and Soil Sciences. Research Series No. R03-1. Cornell University, Ithaca, NY, USA.

7 Adapt-N Infrastructure High-Resolution Climate Data (4x4 km) Northeast and Iowa expanding to all of eastern USA in 2012 Daily updates 7

8 Why high resolution weather data? Precipitation is highly localized June Precipitation Iowa 8

9 9 Cloud Computing Server-based, with universal access through Web Anywhere with internet access Many platforms and operating systems (incl. tablets and phones) No software exchange with users, nor installation Easy and rapid updates Databases software Centralized processing and record keeping

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11 Adapt-N Interface: entering Mineral N/Cultivar info

12 Adapt-N Interface: entering Soil/Tillage info

13 Adapt-N Interface: entering Manure/Sod/Soybean info When done entering all field info, click Submit to run the simulation.

14 Adapt-N Results Page Example with need for sidedress N

15 N Recommendation Methodology Mass Balance Approach CropN Harvest Total crop N uptake from planting to harvest, based on "Expected Yield" input. CropN Current Crop N uptake from planting to the current/simulated date, based on growth and N uptake according to weather data. SoilN Current Crop-available N in the root zone on the current/simulated date, based on soil, N inputs, previous soy or sod crops, crop uptake and weather effects. SoybeanN Credit Estimate of contribution of N to the current corn crop from a previous season soybean crop. SoilN postsidedress Estimated crop-available N (from mineralization/urea hydrolysis estimated N losses) from the current date to harvest. Loss postapplication Estimated post-n recommendation losses from the Adapt-N recommended N application.

16 Adapt-N Results Page Downloadable pdf

17 Adapt-N Results Example Report The downloadable pdf file provides: - All user inputs listed for easy record keeping. - Recommendations from Results page on interface - Graphs describing N dynamics and relevant weather, soil water and plant parameters

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22 (for PSNT/LSNT equivalent, divide by 4) 22

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29 PNM Model testing: On-Farm Network Strip Trials - Normal Normal 50 - Manure

30 Monthly total rainfall averaged over the locations of the 2007 and 2010 strip trials 30

31 Model-simulated N loss pathways from the soil for 2007 and Clarion soil / anhydrous ammonia (170 lbs N/acre) injected (9 ) in late March / long-season corn hybrid planted on April 18 31

32 Estimated vs Measured Yields: 2007 Strip trials 32

33 Estimated vs Measured Yields: 2010 Strip trials 33

34 Outcomes: What did we gain from this exercise? Soil organic matter is critical Rooting depth : tiled vs non-tiled fields Conversion of ammonium to nitrate in the soil Need to improve representation of winter processes Fall applied anhydrous ammonia/manure Initialization of model in the spring Need to improve representation of the soybean N credit Impact of flooding on crop growth? 34

35 NYFVI and NRCS-CIG projects Strip Trial Collaborators New York Keith Severson, Cayuga County Kevin Ganoe, Central NY Chuck Bornt, Capital Region Sandy Menasha, Long Island Eric Young, Miner Institute Anita Deming, Michael Davis, and Eric Bever, Lake Champlain Region David Shearing, Nate Herendeen, Jason Post, and David DeGolyer, WNY CMA Iowa MGT Envirotec: Shannon Gomes, NE Iowa Frank Moore, NE Iowa Michael McNeil, NC Iowa Hal Tucker, W Iowa Iowa Soybean Association

36 Strip Trial Locations in NY and IA

37 Strip Trials Two N management practices: Conventional (C), (grower) N rate Adapt-N recommended N rate (A) (in-season) Four replications / spatially balanced design*. C1 A1 A2 C2 A3 C3 C4 A4 *van Es et al Spatially-Balanced Complete Block designs for field experiments. Geoderma 140:

38 Strip Trials NY : 30 strip trials / 18 with yield data Grain Silage Sweet corn IA : 25 strip trials / 19 with yield data All grain Corn Corn Soybean Corn NM Management Fall/Spring anhydrous ammonia Fall/Spring manure Spring fertilizer N

39 NY-Grain:Yields equal to/greater than Adapt-N yield goal * * *corn following soybean * * 39

40 NY-Grain: Measured yields less than Adapt-N yield goal 40

41 NY-Silage: All Trials 41

42 Iowa: Adapt-N Rec Higher than Grower N 42

43 Iowa: Adapt-N Rec Lower than Grower N Rec 43

44 Iowa: Soybean-Corn / No Manure Corn Corn / No Manure 3 Trials 191 bu/ac (Adapt-N) 187 lbs N/ac 176 bu/ac (Grower) 162 lbs N/ac 44

45 Iowa: Soybean-Corn / Manure Corn Corn / Manure 1 Trial 217 bu/ac (Adapt-N) 40 lbs N/ac 210 bu/ac (Grower) 0 lbs N/ac 45

46 LSNTs/PSNTs (12 ) : New York 46

47 LSNTs/PSNTs (12 ) : Iowa 47

48 Estimated N leaching losses: NY-Grain: All Trials 48

49 NY-Silage: All Trials 49

50 Preliminary Strip Trial Conclusions Adapt-N generally accurately estimated lower N needs, and in some cases higher N needs In some cases Adapt-N under-predicted N needs N savings were considerable on some fields Adapt-N will need some minor adjustments Post-application loss probabilities N immobilization and soybean credit Analyses of strip trial data Aerial photos showed treatment effects when present; LSNT and corn stalk nitrate tests provided mixed results. Importance of additional year of testing (2012)

51 Current: Adapt-N for Operational in Northeast and Iowa Winter 2011/12: - High resolution climate data East of 100th Meridian 2012 season: - Strip trials - Limited it extension to other Corn Belt States - Cover crops - Inhibitors - Improvements based on 2011 data - Daily summaries; text/ alerts 2013: - Estimation of N 2 O losses 51

52 Web Site: cornell edu or Google Adapt-N

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55 55 Using Adapt-N for Site-Specific Adaptive Management NRCS Soil survey Organic Carbon Content (%) estimated with VIS-NIR Spectroscopy (Veris Technologies)

56 N Sidedress Recommendation (kg/ha) wet spring Graham, C.J., H.M. van Es, J. Melkonian, and D.A. Laird Improved nitrogen and energy use efficiency using NIR estimated soil organic carbon and N simulation modeling. In: D.A. Clay and J. Shanahan. GIS Applications in Agriculture Nutrient 56 Management for Improved Energy Efficiency. pp , Taylor and Francis, LLC.

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