Havelock North played host to the delegates for the 2016 LandWISE
“Value of Smart Farming” Conference. Day one started with an Australian
perspective and Julie O’Halloran and Ian Layden from the Queensland Department
of Agriculture and Fisheries both spoke regarding challenges with precision ag
implementation in the Queensland context. Both are working on a precision ag
project with a small group of Queensland vegetable growers.
The key points in their project:
- Identify variability using EM surveys and Trimble GreenSeeker technology.
- Address variability using variable rate nutrients and water.
- Make sure that data is utilised and implemented into management decisions.
For more info on Trimble GreenSeeker and EM Soil Surveys
head to www.agritopics.co.nz
The story of Keith Jarret’s successful Koln Concert was the
analogy used by Ian make the point that although something doesn’t feel right,
e.g a new technology, embracing the change and stepping outside the comfort zone
can see great things can happen. Often, this is the case when new technology
doesn’t perfectly fit the system. Taking the risk and making it work can end in
a great result.
Dan Bloomer of LandWISE spoke about the website www.fertspread.nz, a fertiliser spread
analysis and calibration tool. Farmers, growers and contractors that spread
their own fert should head there to see some of the tips for accurately
calibrating their spreading equipment. The website provides access to some
extremely useful and practical resources.
Boosting the growth and development of cutting edge NZ
Agritech is the focus of Sprout (www.sproutagritech.com), an agritech incubator
that is supported by many big New Zealand agribusinesses. Stu Bradbury, also
from Agri Optics North, spoke about the role sprout is playing in developing
Kiwi startup agritech ventures.
Stu Bradbury introducing Sprout Agritech Accelerator |
Source: J Pishief, Landwise Presentation |
The key steps in utilising profit mapping:
- Capture georeferenced data at harvest.
- Identify the “Yield Gap”. i.e. the potential yield that each area or zone can reach.
- Link this data to the cost of production.
- Create a gross Margin for each zone in the paddock.
- Identify what is causing this loss.
Day two of the conference introduced delegates to the future
of smart farming. Big Data, Agricultural Cybernetics and machine learning was
some of the jargon used in the morning presentations. However… Big data does not equal information. This was the
guts the message from Tristian Perez, Professor of Robotics and Autonomous
Systems at Queensland University of Technology. Farmers now have access to more
data than ever but this does not necessarily equate to usable information. The
biggest issue facing farmers now is no longer the volume of data but the variety.
Data from multiple layers e.g. NDVI, EM and Yield are just some of the variety
that farmers are faced with.
Drones in action at the Centre for Land and Water |
The micro farm at the Centre for Land and Water (see http://www.claw.net.nz/ for more info) was
the setting for demos of drones spreading rice and aerial spraying as well as
an autonomous vehicle designed to drive itself around orchards. The level of
technology involved in automated ag vehicles is immense and the future of farm
machinery will see farmers needing knowledge of increasingly complex machinery
and technology.
Autonomous Orchard Robot |
By Nick Evans, PA Technician at Agri Optics. @AgriOpticsNick