Macadamias, Drones, and the Decisions That Follow
Why drone data in macadamia orchards is less about mapping, and more about improving management decisions.
I’ve recently contributed to an upcoming ProAgri article focused on drone use in macadamia orchards specifically.
This will be the first instalment in what I plan to become a wider series of drone-related articles with them. For context: ProAgri is one of South Africa’s well-known agricultural publications, with a strong readership among farmers locally and across Africa (46+ countries).
With this opening piece focused specifically on macadamias, I’m excited to contribute - it feels like the right place to start.
Macadamias are a strong fit for drone technology. Not because drones are trendy. Not because maps look impressive. And not because farmers need yet another layer of reporting for the sake of reporting. They’re a good fit because every tree matters.
A missing tree, weak tree, blocked irrigation line, drainage issue, pest hotspot, uneven canopy, or recurring stress pattern can carry a cost for several seasons.
With a long-term, high-value crop like macadamias, small differences in tree performance can become major differences in production, quality, sound kernel recovery, and margin.
This is where drones become quite useful…
They give growers and technical teams another way to observe the orchard. From the ground, we see individual trees and visible symptoms. From the air, we see patterns, variation, outliers, weak zones, canopy differences, and areas that need closer inspection.
But the drone is not the point, but the decisions that follow.
A colourful NDVI, NDRE, RGB, or thermal map may look useful, but the real question is always: what now?
Which block needs attention?
Which trees are outliers?
Which zone should be scouted first?
Where should leaf or soil samples be taken?
Which irrigation lines need checking?
Which areas should be compared against yield, cultivar, soil type, pest pressure, pruning history, or processor feedback?
That is where drone data starts to become practical.
The ProAgri article will touch on tree inventory, canopy variation, plant health monitoring, irrigation and water-stress insights, smart sampling, pest scouting, phenology, yield records, spray drones, variable-rate application, and the role of drone data in better orchard decision-making... and more.
The article also connects with some of the thinking behind my upcoming macadamia-focused drone data book.
The broader theme? Don’t start with the drone… Start with the problem. Something I touched on already in my chapter contribution in this book).
Drones don’t replace good farming practice.
They help show where expertise can be focused, leveraged, and utilised best.
The ProAgri article will be shared once it is published.
Thanks for reading,
Ken