Author
Listed:
- Andrey Ronzhin
(St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), 199178 St. Petersburg, Russia)
- Artem Ryabinov
(St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), 199178 St. Petersburg, Russia)
- Elena Shkodina
(St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), 199178 St. Petersburg, Russia)
- Anton Saveliev
(St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), 199178 St. Petersburg, Russia)
- Ekaterina Cherskikh
(St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), 199178 St. Petersburg, Russia)
- Aleksandra Figurek
(School of Business, GNOSIS Mediterranean Institute for Management Science, University of Nicosia, 1700 Nicosia, Cyprus)
Abstract
The operational limitations of ground-based machinery in waterlogged soils of northern regions often lead to missed agronomic treatments, resulting in substantial yield losses. This problem is important in potato production, where a delay in disease protection can quickly lead to loss of leaf mass and reduced yield. This article evaluates an integrated UAV-based approach for crop production in potato cultivation, encompassing aerial soil analysis, weed segmentation, targeted spraying, and yield prediction. A field experiment was designed using a developed GD-4 drone on a 300 m × 6 m test plot. Aerial photography was used to generate an orthophotomap for monitoring and planning pesticide applications. The UAV, operating at a 2-m altitude, achieved a 3-m spray swath, enabling complete plot coverage. Visual assessment confirmed superior plant health in the test plot compared to the control. Quantitative analysis revealed a yield of 39.06 t/ha in the test plot, a 15.2% increase over the control plot (33.91 t/ha), with a comparable percentage of marketable tubers (94.5% vs. 93.3%). The study concludes that UAV technology is a reliable means of remote sensing and offers an alternative for ensuring timely agricultural operations and enhancing yield in inaccessible terrains.
Suggested Citation
Andrey Ronzhin & Artem Ryabinov & Elena Shkodina & Anton Saveliev & Ekaterina Cherskikh & Aleksandra Figurek, 2026.
"UAV-Assisted Pesticide Application in Potato Cultivation Under Waterlogged Soil Conditions: Orthophotomap-Based Monitoring and Field Assessment,"
Sustainability, MDPI, vol. 18(9), pages 1-20, May.
Handle:
RePEc:gam:jsusta:v:18:y:2026:i:9:p:4567-:d:1936015
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