Crop type: Citrus

Location: South Africa

Driving Block Uniformity with Precision Drone Data

How Du Toit Agri is Using Tree-Level Insights to Standardize Orchard Performance

THE CHALLENGE

Achieving uniformity across orchard blocks is critical to maximizing yields, optimizing input usage, and simplifying farm operations. At Du Toit Agri, a leading fruit production business, ongoing variability in tree-row volume and performance was making it difficult to apply inputs efficiently and predict harvest outcomes.

Despite using satellite and aerial imagery from fixed-wing aircraft, the team struggled to gain consistent visibility—especially in a, where imaging quality was compromised.This limited their ability to detect underperforming zones and undermined efforts to execute a targeted, data-driven strategy.

SOLUTION

To overcome this challenge, Du Toit Agri partnered with Aerobotics to implement a more granular and reliable form of analysis.

Aerobotics deployed drone-based Tree Insights, capturing high-resolution imagery that accurately assessed each tree’s health, canopy size, and performance metrics—even under netting. Using these per-tree insights, the farm was able to create health and vigor maps at the block level.

These maps guided both variable rate applications and sampling strategies, ensuring that interventions were based on actual performance data rather than averages or assumptions.

THE IMPACT

This shift to drone-powered precision data led to significant improvements in orchard

management:

• Enabled targeted variable rate application: Inputs like fertilizer, nutrients, and irrigation

  could now be applied with precision, optimizing costs and maximizing tree response.

• Clear visibility of underperforming zones: Previously hidden stress areas were made

  visible, allowing for proactive treatment and follow-up monitoring.

  
  

• Set measurable goals for improvement: With accurate data in hand, Du Toit Agri set an

  ambitious target to bring 80% of blocks to within 10% uniformity over the next three seasons.

  
  

• Supported sustainable, data-driven practices: Precision targeting reduced over-

  application of inputs, aligning with both economic and environmental goals.

VISUAL PROOF

Comparative NDRE (Normalized Difference Red Edge) maps from January 2020 to January 2021 clearly show the impact of these changes: low-performing zones significantly reduced, and block-level uniformity markedly improved. The visual evidence not only validated the new approach but also provided a roadmap for continuous improvement.