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Plant Science Today (PST)

Review Articles

Vol. 13 No. sp5 (2026): Recent Advances in Agriculture

Drone-based herbicide application in rice: Current status, field performance and future prospects

DOI
https://doi.org/10.14719/pst.15559
Submitted
14 May 2026
Published
21-09-2026

Abstract

Rice productivity is strongly affected by weed competition, especially in direct-seeded and aerobic systems where rice and weeds emerge almost simultaneously. Herbicides remain important for rice weed management, but conventional knapsack and boom spraying are limited by labour scarcity, poor trafficability in flooded fields, uneven coverage, high carrier-water requirement and operator exposure. This critical narrative review synthesises the literature published between 2010 and 2026 on unmanned aerial vehicle (UAV)-based rice herbicide delivery, covering weed ecology, spray deposition, drift, crop safety, field efficacy, economics, environmental risk and adoption constraints. Rice-field evidence shows that UAV herbicide application can achieve weed-control efficiency of about 81.8–95.6 % under optimised early-season conditions. In direct-seeded rice, UAV application of pretilachlor followed by bispyribac-sodium at 30–40 L ha-1 produced 89.2–91.9 % weed-control efficiency at 30 days after sowing, comparable with knapsack spraying at 500 L ha-1. Favourable operating ranges reported in rice include spray volumes of 30–45 L ha-1, droplet sizes of about 150–250 µm, flight heights of 1.5–2.5 m and flight speeds of 2–5 m s-1, but these values depend on herbicide type, weed stage, canopy structure and weather. Unmanned aerial vehicle adoption is most justified in flooded, fragmented and labour-constrained rice fields where timely herbicide application is difficult. Nevertheless, low-volume spraying can increase sensitivity to wind, evaporation, canopy interception, drift and calibration errors. Drone-based herbicide delivery should therefore be viewed as a calibrated precision tool within integrated weed management, not as a stand-alone replacement for conventional weed-control systems. Future progress will depend on integrating UAV spraying with weed mapping, artificial intelligence (AI)-based detection, site-specific spraying and variable-rate herbicide application.

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