Field-Validated Drone-Based Precision Control of the Invasive Apple Snail (Pomacea canaliculata) in Rice Paddy Fields: Chemical Reduction and Yield Preservation

Apple snail infestation poses a persistent threat to rice production in open-field environments, where long-term coexistence with this species is unavoidable. This study presents a drone-based precision control approach that integrates high-resolution micro-topographic mapping with site-specific pesticide application. A lightweight mapping unmanned aerial vehicle was deployed to produce centimeter-level microtopographic data across paddy fields, facilitating the identification of deep-water areas preferred by apple snails. From these elevation-derived water risk patterns, prescription maps were generated to guide downstream management decisions, and agricultural drones equipped for granular application subsequently performed targeted pesticide delivery only in these high-risk areas. Over 2 years of field experiments, the proposed method achieved rice yields comparable to those under conventional management while reducing pesticide use by 44.1–63.0%, with lower estimated crop damage in regions with high apple snail occurrence. Designed with robustness and scalability in mind, the system demonstrated considerable potential for practical implementation in general farming households and broader applications in precision pest management.

Authors

Institutions

Publication Details

Journal
Drones
Published
2026-03-05
DOI
https://doi.org/10.3390/drones10030176
Primary Topic
Mollusks and Parasites Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Field-Validated Drone-Based Precision Control of the Invasive Apple Snail (Pomacea canaliculata) in Rice Paddy Fields: Chemical Reduction and Yield Preservation

Shuichi Watanabe, Kimiyasu Takahashi, Koichiro Fukami, SenLin Guan et al.
Drones
Mollusks and Parasites Studies
article

Field-Validated Drone-Based Precision Control of the Invasive Apple Snail (Pomacea canaliculata) in Rice Paddy Fields: Chemical Reduction and Yield Preservation

Shuichi Watanabe, Kimiyasu Takahashi, Koichiro Fukami, SenLin Guan, Hiroyuki Obanawa, Keita Ono
article en

Abstract

Apple snail infestation poses a persistent threat to rice production in open-field environments, where long-term coexistence with this species is unavoidable. This study presents a drone-based precision control approach that integrates high-resolution micro-topographic mapping with site-specific pesticide application. A lightweight mapping unmanned aerial vehicle was deployed to produce centimeter-level microtopographic data across paddy fields, facilitating the identification of deep-water areas preferred by apple snails. From these elevation-derived water risk patterns, prescription maps were generated to guide downstream management decisions, and agricultural drones equipped for granular application subsequently performed targeted pesticide delivery only in these high-risk areas. Over 2 years of field experiments, the proposed method achieved rice yields comparable to those under conventional management while reducing pesticide use by 44.1–63.0%, with lower estimated crop damage in regions with high apple snail occurrence. Designed with robustness and scalability in mind, the system demonstrated considerable potential for practical implementation in general farming households and broader applications in precision pest management.

DronesVol. 10(3)
National Agriculture and Food Research Organization (JP), Kyushu Okinawa Agricultural Research Center (JP)
Zero hunger
Openalex Percentile: Top 40%
Mollusks and Parasites Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.