New Tech Predicts Local Corn Supply. -The Opportunities and Limits of Statistical Ag Data-

Transcription

1 New Tech Predicts Local Corn Supply -The Opportunities and Limits of Statistical Ag Data- Presented by: Steffen Mueller, PhD Principal Economist Biofuel and Bioenergy Research University of Illinois at Chicago Energy Resources Center

2 About Ourselves 15 year relationship Involved in development of Ag20/20 program Funded multiple projects involving biofuels and land use Price Yield Elasticity Research Risk Analysis for 4 Developed Bt Crop ethanol plants in Illinois Resistance monitoring and Iowa system 14 year relationship Image collection since 99 Multiple research projects ADM/John Deere/Monsanto Corn Stover Project Developed yield prediction system for ConAgra in early 2000s Support Contract for Start-up firm to determine accuracy of remote sensing for CCX no-till verification 2

3 Clutter of Agricultural Data: Risk to get Oversold All Data has Limits Understand the Limits Distributions Matter

4 What Constitutes Sound Ag Analysis? Must create daily products Focus imagery only on cropland not on the entire area. Work up in resolution, using field work first to high resolution satellite imagery to moderate resolution imagery Use extensive ground calibration and verification Combine satellite yield prediction with soil moisture, weather, growing degree days and precipitation to predict yield Use long term historical data to calibrate model Rigorous interaction with scientific community It does not make sense to use satellite data for soy bean yield predictions It does not make sense to use delayed vegetation products For field work it is valuable but not sufficient to rely on grower opinions need soil and plant scientists

5 What Constitutes Sound Ag Analysis? Good Statistical Modeling Quality Input Data Ground Calibration&Verification Expert Exchange

6 Stochastic Local Yield and Acreage Modeling High Resolution Vegetation and Weather Variables including Aflatoxin Index on uic.edu Ground Calibration & Verification Expert Phone Calls 5 Interactive Phone Calls Throughout the 2013 Season

7 Ground Calibration & Verification

8 Ground Calibration and Verification Collect several 1000 data points in multi-day trip across Midwest to classify crops Cooperate with Soil-Right Consulting to conduct ground analyses In business for 27 years, affiliated with highly reputable Brookside Laboratories of New Bremen, Ohio Currently servicing over 70,000 acres In depth soil analysis plus yield assessments

9 Ground Calibration & Verification Extensive Scouting

10 Ground Calibration & Verification May June July August What happened in 2012? Went into season with virtually perfect conditions. Rains in late May and early June added to crop conditions. Looking at record crop. Then the water shut off and heat entered in early July. As late as July 10, crop prospects looked good. Then the heat turned up. Within 2 weeks the corn crop was going backwards. Pollination of mid-date and later planted corn was hurt drastically. If the corn does not pollinate, it will not produce seed. Yield became a function of planting date and water holding capacity of the soil.

11 Quality Input Data

12 Quality Input Data LandViewer Uses Daily Original Data Sets Quality Controlled Weather Data Quality Controlled NDVI Satellite Data All posted on

13 Quality Input Data

14 Quality Input Data Vegetation Vigor Vegetative Vigor: The Normalized Difference Vegetation Index (NDVI) has been in use for many years to measure and monitor plant growth (vigor) and vegetation cover. This metric allows the user to benchmark the intensity/volume of vegetation on the fields at any point during the current growing season to the same time in earlier years. Chlorophyll absorbs blue and red light (not the green) The plant s structure reflects nearinfrared light strongly. 100% Typical Plant Spectral Signature 0% blue green red near-infrared

15 Quality Input Data Imagery Can Follow Crop Condition Throughout Season Late May Bare soilorganic matter and moisture Corn Field near Homer, IL Mid June Emergence- Stand count And vigor Corn 10' Corn 09' Corn 08' Early July- Tasseling and vigor (first yield predictions) Ability to separate out crops Late July Vigor and yield Mid September Senescence and yield Bare Soil Late August Early Senescence Yield Early August Vigor and yield Increasing Vegetation

16 Quality Input Data Steps to Production of Change in Vegetation Vigor Maps 1.) Remove all land cover other than crop 2.) Obtain average of historical vegetation values 3.) Subtract this average from the current vegetation vigor map 4.) Break this map into zones: Greater than 2 standard deviations below the mean: Label severe decline 1 to 2 standard deviations below the average: label moderate decline Mean to 1 standard deviation below: Label minor decline Mean to 1 standard deviation above: Label minor improvement 1 to 2 standard deviations above: Label moderate improvement Greater than 2 standard deviations above: Label severe decline Mapping Starts May 1, 2013

17 Quality Input Data Typical NASA Satellite Value Adder 1) Download 8-day NASA product 2) Convert to vegetation index 3) Present to user LandViewer Procedures (all automated) 1) Daily download of near real-time NASA satellite images for U.S. MOD09A1-250 meter reflectance product MOD35-1km cloud mask MOD11A2-1km ground temperature (day time and night time) This is over 45 gigabytes of data a day and 2 hours of processing time 2) Use MOD35 cloud removal mask to eliminate cloud cover from reflectance image 3) Combine multiple images to cover entire United States 4) Convert reflectance to vegetation index 5) Combine with previous days imagery for timeliest data product 5) Remove non-crop or non-corn areas as appropriate 6) Create change maps by comparing new imagery to historical image dataset

18 Quality Input Data

19 Quality Input Data

20 Quality Input Data

21 Quality Input Data

22 Quality Input Data

23 Quality Input Data

24 Quality Input Data

25 Quality Input Data

26 Quality Input Data

27 Quality Input Data Growing Degree Days & Night Time Temps Growing Degree Days (GDD) measure of accumulated heat throughout the growing season key metrics influencing yield Map created starting May 1 Night time minimum temperature for the critical mid-july through mid-august period compared to last 5 years. Studies have shown that relatively high night time temperatures (greater 66 F) after pollination can reduced yield by between 5-13 percent. Map created starting July 1

28 Quality Input Data Aflatoxin Meta Analysis of Publications (Iowa State University, USDA ARS, University of Reading) Temperatures above 86 degree plus relatively dry conditions during silking and grain fill helps fungus invade High night time temperatures plus rain at blacklayer stage/physical maturity ie at ~2700 GDD Soil temperatures below 65 deg F little/no risk of aflatoxins Map created starting July 1

29 Stochastic County-by-County Yield and Acreage Modeling

30 Stochastic County-by-County Yield & Acreage Modeling Acres in 1800 counties and 18 corn states with highest influence on corn yield 30

31 Stochastic County-by-County Yield & Acreage Modeling Based on research and comparison to historical yield trends the following parameters The potential impact to yield from the following parameters are weighted: Precipitation Soil Moisture Growing Degree Days Vegetation Vigor Night time temperature minimum Day time temperature maximum

32 Stochastic County-by-County Yield & Acreage Modeling

33 Stochastic County-by-County Yield & Acreage Modeling 2011 & 2012 Model Backcasting

34 Expert Exchange

35 Expert Exchange 5 Conference Calls Throughout Season Interactive Exchange among participants Scouting updates throughout the Midwest Summary of Growing Conditions Local Yield and Acreage Prediction Updates

36 Next Slides 2012 Yield Animation Based on Satellite NDVI Data

37

38

39

40

41

42

43

44

45 2013 Service Access to Website Starting April 15, 2013 Access to National and Regional Weather and Vegetation Data Access to county-by-county yield statistics 5 conference calls throughout season Crop and Soil Scouting Updates from Soil-Right Consulting Weather, Yield and Acreage Updates Exchange with Traders, Growers, Grain Buyers

46 2013 Season Existing Client List Ethanol Plant Operators (for third season) Airborne Fertilizer Applicator (for second season) Traders Grain Elevator Operators

47 Contact Steffen Mueller: Ken Copenhaver: