Precision pesticide detection and control system for fruit orchards using UAV spectral imaging
A precision agriculture system combining UAV-based spectral imaging, fluorescent paint tracers, and UV spectrophotometry to detect, predict, and optimize pesticide application in fruit orchards. The approach reduces pesticide volume, frequency of applications, and pest/disease damage across olive, apple, grape, and avocado crops.
Overview
This solution offers a precision agriculture system designed to detect and control pesticide applications in fruit orchards. It combines fluorescent paint tracers, UV spectrophotometry, and spectral image segmentation algorithms obtained through UAV flights to determine the optimal volume of pesticide mixture to apply per area. The system has been validated on five fruit crops including olive trees, apple trees, grapes, and avocado trees, demonstrating significant reductions in pesticide volume, application frequency, and pest and disease damage. By integrating smart machinery with advanced imaging and chemical detection, the technology enables targeted, data-driven crop protection that increases application efficiency while reducing environmental and economic costs.
Technical specifications
Core methodology:
- Spectral image segmentation algorithms analyze UAV-captured imagery to determine tree crown volume and canopy structure
- Fluorescent paint is mixed with pesticide formulations to enable visual tracking of droplet distribution on leaves and soil
- UV spectrophotometry using nanodrop equipment measures absorbance spectra of specific pesticides at defined wavelengths
- WAATIC hardware integration links UAV image acquisition with field application data
Validated pesticide detection wavelengths:
- Bentazone at 335nm
- Pendimethalin at 238nm
- Cyprodinil at 270nm
- Fludioxonil at 271nm
- Fluopyram at 270nm
- Tebuconazole at 290nm
- Profenofos (wavelength to be determined)
Target pests and diseases evaluated:
- Pests: A. spiraecola, P. kellianus, C. orchidii
- Diseases: P. viticola, B. cinerea, A. vitis
Demonstrated results:
- Botrytis cinerea applications reduced from 14 to 9 per season
- Pesticide volume reduced from 1000 to 700 liters per hectare
Technology readiness level
The system has been validated through field experiments conducted across two locations on five fruit tree species. Results demonstrate measurable decreases in pest and disease incidence alongside reduced application frequency and chemical volume. Future validation efforts will extend the spectral segmentation algorithm to apple and sweet cherry orchards, quantify pesticide volumes through laboratory UV spectrophotometry using both nanodrop and conventional equipment, and establish calibration curves for precise quantification. The technology is at an advanced field-validation stage, ready for pilot-scale deployment and collaborative refinement with industry partners.
About Instituto de Investigaciones Agropecuarias
INIA is Chile’s national agricultural research and innovation institute, a private non‑profit corporation linked to the Ministry of Agriculture, with roughly 1,000 staff and a network of 11 regional research centers across the country. Co‑located experimental farms and specialized laboratory services enable field‑to‑lab collaboration for partners. A national germplasm bank network and an International Depository Authority microbial collection support characterization, secure deposits, and downstream commercialization. Core funding comes via a performance agreement with the Undersecretariat of Agriculture, complemented by competitive national R&D and innovation programs and revenue from services, seeds, and varieties. Dedicated extension and technology transfer programs accelerate adoption through demonstrations, training, and variety release to producers and agri‑food firms.
delivered to your inbox.