Understanding How Precision Ag Works Regardless of Your Farm Size

Transcription

1 Understanding How Precision Ag Works Regardless of Your Farm Size John Fulton 2017 FarmSmart Agriculture Conference, University of Guelph, Ontario

2 Air Conditioning in the Cab Smart phones / ipads / Tablets Guidance technology Yield monitors

3 Planter Displays By-Row Seed Monitoring Will improve planting quality 3

4 Section / Row Control for Planters Corn - SAVINGS: 4.3% - YIELD: 17% less - HARVET LOSS: >6 times higher Automatic Section Control Technology for Row Crop Planters (Auburn Extension Publication)

5 Average Overlap Reduction PA Technology Percent Savings GPS-based Guidance 10% Variable-Rate Application 7% Automatic Section Control (ASC) 5% TOTAL AVERAGE 22% NOTE: Data based upon Auburn studies. Values could be higher or lower depending upon many production factors.

6 Variable-rate Seeding in Corn Average 5% yield gain Fields may exist where VR Seeding does not work so maintain fixed rate. 10% to 15% gain in some fields using VR

7 Field-by-field basis Prescriptive Agriculture Food, Agricultural and Biological Engineering

8 Today s Technology Food, Agricultural and Biological Engineering

9 By-row Prescription (Rx) Hybrid Population Starter & pop-up fertilizer Downforce Row-cleaner Rx Management

10 Planter Technology Precision Planting Food, Agricultural and Biological Engineering

11 Multi-Hybrid Planting Technology Data People - Evaluation Food, Agricultural and Biological Engineering

12 Agriculture Connectivity Image courtesy of New Holland

13 Digital Agriculture Enterprise Agriculture Big Data in Agriculture Prescriptive Agriculture Precision Agriculture Information adapted from an Iowa AgState / Hale Group report.

14 Prescriptive Agriculture data driven recommendations and information; fastest growing area. Food, Agricultural and Biological Engineering

15 Data Exchange for Growers Producer Recommendations Preseason Fertility Management Prescription P and K application (Precision Crop Services) Tillage Management Prescription tillage maps (AGCO; CNH) Multi-Hybrids Prescription seeding of multi-hybrids (Beck s; Pioneer) SCN Management Prescription application/use of nematicides (FMC) In-Season Fertility Management Prescription N application (DuPont Pioneer; Climate Corp) Irrigation Management Prescription Irrigation (AgSmart) Disease Management Prescription fungicide application (BASF)

16 Why collect data? Collecting and archiving data enables its use on-farm and participation in data services (Prescriptive Agriculture).

17 Precision / Digital Ag Evolution - Electronic drives for metering inputs (planter drives, PWM nozzles, etc.) - Automating machinery - M2M, M2I - Prescriptive agriculture (data driven) - Online viewing dashboards (operational centers) - Integration of agronomic, machine and imagery data - Sustainability and Environmental Stewardship

18 Types of Data 1) Agronomic yield, as-applied, as-planted, etc. 2) Machine engine parameters, tractor status variables, implement mode & functions 3) Production - Information within home office, weather, notes, etc. 4) Remote Sensed Imagery satellite, aerial, drones 5) Public Data SSURGO, imagery, DEMs, etc. 6) Business Field-by-Field Database

19 Agronomic Data: As- Planted Data Verification of seed placement In-Cab Display Feedback Producer Value 1) Identify and correct equipment issues immediately.; 2) Execute prescriptions; 3) Identify soil characteristics (e.g. clods, trafficked areas); 4) Verification of seed placement

20 As-Planted Data: Row-Unit Ride Quality Map In-Cab Display Feedback Producer Value 1) Identify and correct equipment issues immediately.; 2) Execute prescriptions; 3) Identify soil characteristics (e.g. clods, trafficked areas)

21 Tractor tire paths visible after field cultivator Hidden variables impacting crop development and yield COMPACTION (soil health component) Question: How do we identify and quantify?

22 As-Planted Data Downforce Map Producer Value 1) Identify and correct equipment issues immediately.; 2) Execute prescriptions; 3) Identify soil characteristics (e.g. clods, trafficked areas)

23 Agronomic Data Yield Maps Producer Value Requires cleaning before creating Rx s. 4 to 8 years of good yield data for prescriptive services. Quality data leads to accurate analyses and information. Historical data provides value to RX creation.

24 General Use of Yield Maps for Nutrient Prescriptions Published Research - Good for identifying management zones by production levels (placement). - Good for using within P and K management (removal map for helping establish rate) - Cautiously use yield maps to drive variable-rate N.

25 Machine Data CAN messages, Health, etc. Effective tool to evaluate operating costs and capacity --- FUEL USAGE, UPTIME vs. DOWNTIME, ENGINE LOAD.

26 Telematics (Farmobile) Harvest Operation Paths Producer Value: 1) Identify potential zones of soil compaction / structure issues; 2) Data for future analyses.

27 Frequency Frequency Food, Agricultural and Biological Engineering Fuel Use Summary based on CANbus data Fuel Use Rate Distributions Field 1C Planting Field 4A NH 3 Application Fuel Use Rate (L/h) Fuel Use Rate (L/h) Source: Shearer and Klopfenstein; Ohio State University

28 NDVI Image Early July Corn Identifying Man- / Machine-made Vs. Natural variability

29 Identifying Man- / Machine-made Vs. Natural variability Food, Agricultural and Biological Engineering

30 Individual data streams are valuable but the merging these data streams provides powerful insights.

31 Agronomic Data Yield Maps, As-applied Food, Agricultural and Biological Engineering

32 Bridging Agronomic and Machine Data Moisture Content (%) Ground Speed (mph) Fuel Usage (gallons per acre) Mean % Engine Load Mean Field Capacity (ac/hr) Hybrid A Hybrid B

33 Best Practices to Managing Farm Data 1) What are you key data layers? 2) Maintain Copies & Backups of Display Data 3) Data storage (on and off-farm) 4) Organization of stored data 5) Who do I plan to share data with?

34 You can't manage what you don't measure! (W. Edwards Deming) & You can t utilize what you don t collect.

35 Planter University Beck s Hybrid s, London, OH (right beside Farm Science Review) Tuesday, February 28 th (8 AM to 4:30 PM)

36 Digital Agriculture Providing solutions to meet world demand John Fulton Ohio State Precision Ag Program Facebook: Ohio State Precision Ag