9. Kalbar Carrots – Data Mining
Yield
Thousands of individual, geo-referenced data points
Multiple spatial layers
96%
EM Soil Survey 89%
NDVIYIELD
NDVI (Greenseeker)
10. How much of the field is
underperforming? By how much?
Is there value in increasing yield
in poorer performing areas?
Economic analyses of variability
vs management intervention
Farming values
Yield
category
Area % area
0-40 t/ha 2.8 31
40-60 t/ha 5.6 62
60-100 t/ha 0.6 6
high $/ha
low $/ha
Kalbar Carrots - Decision making Profit-Loss Map
15. Atherton Potatoes – Treat Variability
EM mapping and & moisture probes (telemetry)
Low water holding capacity soils in the East
VRT irrigation, automatically manual
16. 30% higher yielding
variety
Atherton Potatoes – Data Mining
Zone Average (t/ha) % Area
1 79.30 4.98%
2 51.30 15.99%
3 38.44 50.04%
4 25.58 27.09%
5 14.58 1.89%
Average/total 38.59 100%
18. Bowen Capsicums - Identify Variability
53% with ESP >6%
As high as 20% at 0.5m
Yield consequences? Data doesn’t exist
Up to 60% based on calculations derived
from Ayars & Westcott, 1994
Not seen here = good water/nutrition
management
Soil tests & local erosion show
considerable soil-structural effects
ESP %
21. Keep an eye on water levels
Leach in dry years only
Gypsum application 0-5 t/ha banded
(traditional 1t/ha over 32 ha)
VRT increases GM by $9/ha OR 0.002%
of the GM
Bowen Capsicums - Treat Variability
YES!
0 t/ha
1.75 t/ha
3.25 t/ha
5 t/ha
22. So why is PA in veg important?
While not always straightforward, PA does help identify, quantify & treat variability
Crop uniformity is critical – contract & mechanical harvesting, hand harvesting (reducing
multiple harvests)
Current agronomy is very good – has been revised due to missing some important within block
factors affecting profitability (pests, irrigation, soil)
More efficient & strategic utilisation of resources (inputs, labour) & land (environmental
advantages)
Government investment has an important role in kick-starting/navigating adoption of new
technologies, particularly where market failure exists
Future
Improved grower/agronomist readiness for emerging data challenges (storage, analysis, privacy,
mobile applications, robotics, automation)
Traceability – becoming more important in the fresh sector (agronomic/chemical data on
demand, exact locations/harvest days, pack out, safety, quality ………)
23. Challenges
Yield monitors are critical to adoption & understanding the cost
of variability – require significant optimisation & calibration to
determine “marketable” yield
Data management, capacity building in utilising software,
‘cloud’ & mobile mapping applications e.g. Google Earth,
Dropbox
Technology optimisation – not just plug & play technologies,
compatibilities
Capacity building for ground truthing activities e.g.
strategic/zonal sampling
Multiple layers & data mining to get the most out of the
investment
24. This work was supported by the Queensland Department of
Agriculture and Fisheries (DAF), Department of Environment and
Heritage Protection and the Australian Government’s National
Landcare Programme.
This work was made possible by the co-operation of producers and
commercial service providers.
Acknowledgements
Kengoon Farming ● Windhum Farms ● NorthQual ● Veejays ● Rieck Farming ● DJM Farming ●
Ben Poggioli ● AustChilli ● Kalfresh ● Windolf Farms ● Rugby Farms ● Phantom Farms
Precision Agriculture ● Precision Ag Solutions ● Vanderfields ● BGA Agri Services ● GT Ag Services ● SST
Software ● Bowen Crop Monitoring ● Tableland Fert ● Airborn Insight ●
BMS Laser Sat