Date post: | 11-Jan-2017 |
Category: |
Food |
Upload: | amanda-woods |
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Fishing for new solutions to old problems
Turning sensor data into decisions in the paddock
Ash Wallace Eileen Perry, James Nuttall, Jason Brand & Glenn Fitzgerald
What problems are we targeting?
Frost
• Estimated damage up to $100M p.a.
• Potential increased risk in the future.
Pulse diseases
• Estimated damage up to $74M p.a.
What technology are we using?
Fluorometer • Measures a range of indices related
to photosynthesis and plant stress.
• Active, proximal sensor.
Hyperspectral sensor • Measures reflected sunlight ranging from UV, to
visible and beyond.
• Passive sensor, very sensitive to sky conditions. • Provides a very wide range of indices e.g. NDVI.
So what?
Research questions: • How early can we detect damage? • What ‘level’ of damage can we detect? • Do these indices ‘hold up’ across time and space?
Practical questions: • What decisions can we make with this information? • Couldn’t you make a decision based on ‘eye’? • Would the ability to map damage help?
Measuring pulse diseases in the field
• Monitoring disease progression in Faba Beans and Chickpeas.
• Targeting multiple varieties and fungicide strategies.
• Multiple sensors, proximity to the crop and time of monitoring.
Moving from canopy to leaf level measurements
• Using a hyperspectral sensor to test a broad range of indices.
• Hopefully an indicator of indices that might be of use at the canopy level.
• Challenges where the upper canopy is relatively ‘clean’.
• Haven’t yet found any ‘best bets’ for diagnosis.
Turning sensor data into a decision
What is the problem?
What can we measure?
Can we do anything about it?
• Practicalities of the equipment:
• How can it be deployed?
• Active vs. passive sensors.
• What resolution of data and decision is required?
• Translating that decision into an action.