Makin and Usin Management Zones A Case Study

Transcription

1 Makin and Usin Management Zones A Case Study Dan Breckon : Woodrill Farms, Precison Ag Specialist Doug Aspinall: Woodrill Farms, Precision Soil Scientist

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3 Management Zones Zones are a function of soils, landscape (topography) and productivity (yield) areas of homogeneous yield limiting factors Physical Limitations Truncated soil profiles Low AWHC Stones Thin/thick plow layer Shallow soils (bedrock) Poor soil structure Poor drainage (no tile) Soil texture variation Soil Compaction Fertility Limitations Low ph/high ph Low CEC Low % OM Low nutrients

4 Making Zones - Geospatial Data Sets: Elevation Data - Lidar, RTK GPS, SGM Yield multiple years of yield monitor data Imagery ortho, satellite, (google earth), drone, NDVI Soil Sensing Veris EC, Dual EM, Soil Optix Soils Data soil type and soil property maps Your knowledge of the field

5 Elevation Data Sources Off farm Lidar (laser) SGM, semi global matching (photogrammetric stereo pairs) IFIS (radar), GeoSAR On Farm RTK GPS, planter, sprayer, fertilizer, greenseeker, combine Waas Total Station ($$$) Laser imagery ($$$$$)

6 LiDAR Raw LiDAR Bare Ground

7 Lidar and RTK GPS elevation data LiDAR points/ha Greenstar RTK Winter wheat 34 swath 53 acre field 500 points/ha

8 Digital Elevation Model (DEM) Relative Accuracy how well the DEM represents the surface morphology of the field

9 DEM Terrain Analysis: Curvature Concave Convex

10 %slope TPI RHSP Elevation Contours demsoiloptix Value High : Low : Convex Concave CI LS factor VD RSP

11 Geospatial Data Sets: Yield Mapping Absolute Yield (bu/ac, T/ac, T/ha) and Normalized Yield Maps (above and below average) Multiple Year Yield Mapping - SMS software, normalize with field average Yield Probability Mapping - GFO/Niagara College Data Portal, normalize with field average Yield Index Mapping Aspinall/OMAFRA, normalize with load average

12 Corn Yield Index 3D Below average Above Average 7 years of grain corn yield monitor data

13 The Relationship of Yield and Topography Curvature and Yield Index 6 CONVEX Yield Index 0 0 Curvature CONCAVE Distance (m) Yield Index Curvature

14 Geospatial Data Sets: Electrical Conductivity Veris EC Parent Materials Red = sandy, blue = clayey

15 Electromagnetic DualEM

16 Geospatial Data Sets: Imagery Bare Ground Segmentation, May 2010

17 In-Crop Segmentation October, 2003, Soybeans

18 NDVI Zones

19 Predictive Digital Soil Mapping (PDSM) Soil type maps (Guelph loam, London loam, Parkhill loam) Soil property maps (%OM, CEC, ph, %clay, P, K) Significantly higher spatial accuracy Show the actual distribution of the soil types Increase the speed and accuracy of soil mapping If the relationship is known between a soil and its environment then the occurrence of that soil can be predicted in other areas having the same environment.

20 Management Zone Soil Type

21 Guelph Loam, London Loam, Parkhill loam,caledon fsl, Granby sl, Farmington loam Wellington County Soil Survey, 1964, 1:63,360 Soil Type Guelph Loam

22 Soil Type = Soil Series + Surface Texture Solum Soil series parent material, drainage class, kinds and arrangements of soil horizons (texture, colour, thickness, structure, reaction) + Plow layer soil texture (loam, sandy loam, silt loam etc.) Guelph loam, Guelph sandy loam

23 Profile Changes due to Soil and Tillage Erosion Intact Truncated Depositional

24 PDSM Mapping: how does it work? Classification of environmental layers into classes Target most representative cells for each class Determine soil type at each inspection point Develop rule sets to map soil types Rule base example: Donnybrook gsl degraded Description: Apk, Ck profile found on relatively dry, stony, gravelly sands on knolls located at upper and midslope landscape positions Upper and mid slope (terrain classification index, valley depth, midslope, normalized height) Dry (topographic wetness index, RHSP) Knoll (strongly convex- terrain surface convexity, profile and plan curvature) Parent Material, stony, gravelly sand (EM very low reading) 2013 September 4 Imagery, yellow and brown colours

25 Soil Type Map Inputs Soybean September 2013 Relative Hydrological Slope Position High, dry Terrain Classification Index Up high Down low Low, wet Terrain Surface Convexity Convex Yield Index Above average Soil Type Inspection Points Concave Below average

26 N Woodrill Linders Farm Detailed Soil Map ~1:800

27 Guelph Loam, modal, intact Guelph Loam, truncated

28 Donnybrook gsl, intact Donnybrook gsl, truncated

29 Linders loam, modal

30 Management Zone- Soil Property Management Zone = f (Yield Index, CEC and ph) Yield Index = spatial and temporal yield patterns from multiple crop years CEC = f (% Organic matter and % clay) CEC= ((0.5*%clay)+(%OM*2)) (Soil Fertility Handbook, Pub pg. 35) %clay and %OM f Convexity (SAGA) Topographic wetness index (TWI) SAGA Percent min to max (Pmin2max) LandMapR Elevation Slope Height (SAGA) Peak_elev (LandMapR) Z2pit (LandMapR) + measured values of %clay and %OM

31 Yield Index, CEC, ph Input Maps Yield Index CEC ph Above average/ Below Average High/Low High/Low

32 Zone Map and Zone Stats Zone YI CEC ph Filtered

33 CYI YP (bu/ac) ph %OM Convexity TWI CEC

34 Yield Potential/Yield Goal Map - 6 years of cleaned absolute yield measurements in bu/ac - 116,000 points - Vesper software block kriging, 5x5 m resolution - Yield ranges from 38 to 187 bu/ac - Used for estimating crop removal of nutrients

35 Zone Polygon Mean Soil Properties Zone 1 Zone 8 Property Value YI 4.1 YP CEC 17 OM 3.4 CLAY 21.3 ph 7.4 Twi 9 Cvx 0.1 Property Value YI YP CEC 11 OM 4.2 CLAY 5.5 ph 5.1 Twi 6 Cvx 0.91

36 Woodrill We have lots of tools to adapt different management practices in mgmt. zones High resolution soil type maps are an objective tool to manage and measure our crops and soils Straightforward way to implement precision management practices on the farm

37 Why Soil Type? All soil types take into account: The depth of the soil profile and the horizons that are present What the soil is made of (parent material) Soil texture of each horizon Drainage Capability (Well or Poorly Drained) Landscape Position Soil Type Descriptions are found in the Ontario Soil Survey and Soil Reports

38 Measure with a Soil Type Map 2013 Soybean Yield Dougs Soil Map Current Ontario Soil Map

39 Corn Population Donnybrook Guelph Loam Consistently low yielding Water availability is a yield limiting factor in average years Lowering corn seed population may increase plant available water and Consistently high yielding Deep soil profile with lots of water holding capacity Increasing corn seed population may maximize yield increase yield

40 VR Corn Population Target Population sds/ac sds/ac sds/ac

41 Nitrogen in Corn Donnybrook Guelph Loam N mineralization is minimal during the growing year Mineralizes N from organic matter consistently throughout the growing season N is highly susceptible to leaching from the root zone Will hold applied N for a longer period of time before leaching out of the root zone Would there be a response to more that 2 split applications?

42 Nitrogen in Corn Target Nitrogen Rate 90 lbsn/ac 75 lbsn/ac 60 lbsn/ac 30 lbsn/ac Assuming ideal weather Application at V10-V12 75 lbsn/ac applied Preemerge

43 Compost/Manure Donnybrook Guelph Loam Spread more Compost and Manure to increase OM and water holding capacity Build structure and minimize erosion Spread less as OM and water holding capability are excellent Still going to spread some to increase OM

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45 Tillage Donnybrook Guelph Loam Shallow Ap Deep Ap Highly Erodible Lower risk of erosion No-till to maintain and lower risk of Full Tillage every few years unlikely to erosion degrade this soil type

46 Tillage Prescription No Tillage Tillage

47 N Detailed Soil Map ~1:800