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© AgDNA 2016
Maximising field level profitability using IoT and data automation
◦ Access to quality data
◦ Data processing complexity
◦ Actionable insights
◦ Demonstrable ROI
Precision Ag Challenges
[email protected] @MyAgDNA
◦ IoT (Internet-of-Things)
◦ API’s (Application Programming Interface)
◦ Cloud computing
◦ Wireless connectivity
Emerging Technologies
[email protected] @MyAgDNA
Lux Research – AgDNA Top 10 most innovative companies for 2015
AgDNA
• Agronomic• Topography• Inventory• Climate• Financial
IoT Data Automation - How it [email protected] @MyAgDNA
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)
[email protected] @MyAgDNA
Net Profit $$$
Seeding
Application
Yield
Fuelevery pass
Speedevery pass
Elevation
Fuel + Input $$$cumulative
Crop Income $$$
Spatially Accurate [email protected] @MyAgDNA
Poor – Average – Excellent – zones by net profit
Output - Pixel Profit™[email protected] @MyAgDNA
Identify yield limitations and provide recommendation with $ROI.
Actionable Insights – point & [email protected] @MyAgDNA
◦ 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
[email protected] @MyAgDNA
Know more | Grow more
agdna.comFor more information contact:Glenn [email protected] © 2016 AgDNA