AgDNA maximising field level profitability using IoT and data automation, presented by Paul Turner, AgDNA, SPAA Symposium Toowoomba, Sep 2016.

1. © AgDNA 2016
Maximising field level
profitability using
IoT and data
automation

2. ◦ Access to quality
data
◦ Data processing
complexity
◦ Actionable insights
◦ Demonstrable ROI
Precision Ag
Challenges
gclark@agdna.com @MyAgDNA

3. ◦ IoT (Internet-of-Things)
◦ API’s (Application
Programming Interface)
◦ Cloud computing
◦ Wireless
connectivity
Emerging
Technologies
gclark@agdna.com @MyAgDNA

4. Lux Research – AgDNA Top 10 most innovative companies for 2015
AgDNA
• Agronomic
• Topography
• Inventory
• Climate
• Financial
IoT Data Automation - How it works
gclark@agdna.com @MyAgDNA

5. Financial Data Automation
◦ As applied seed, chemical, fertiliser, fuel rate
(spatial)
◦ Inventory input costs per unit, fixed and
variable costs, labour rate, equipment costs
◦ Yield results, contract price
(spatial)
gclark@agdna.com @MyAgDNA

6. Net Profit $$$
Seeding
Application
Yield
Fuel
every pass
Speed
every pass
Elevation
Fuel + Input $$$
cumulative
Crop Income $$$
Spatially Accurate Results
gclark@agdna.com @MyAgDNA

7. Poor – Average – Excellent – zones by net profit
Output - Pixel Profit™
gclark@agdna.com @MyAgDNA

8. Identify yield limitations and provide recommendation with $ROI.
Actionable Insights – point & click
gclark@agdna.com @MyAgDNA

9. ◦ Use IoT to automate data capture
◦ Spatially analyse data in the cloud
◦ Apply all costs and income spatially
◦ Determine net profit by hectare
◦ Correlate yield limiting factors
◦ Provide insights with probability %
Technology can automate the path from data to decision to dollars
Summary
gclark@agdna.com @MyAgDNA

10. Know more | Grow more
agdna.com
For more information contact:
Glenn Clark
gclark@agdna.com © 2016 AgDNA