Evidence map›Paper›PMID 41459473›Full record

ReviewFrontiers in plant science2025

Unmanned aerial vehicle payload technology applications in agriculture and other low-altitude scenarios: a review.

Weixiang Yao, Changliang Liu, Yuzhou Liu, Qi Zheng, Junyong Wang, Huiduo Yu, Chunling Chen, Shuang Guo

Erratum issuedAbstract readReview
In one paragraph

Review in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Weixiang YaoCollege of Information and Electrical Engineering, Shenyang Agricultural University, National Digital Agriculture Regional Innovation Center (Northeast), Shenyang, China.
Changliang LiuCollege of Information and Electrical Engineering, Shenyang Agricultural University, National Digital Agriculture Regional Innovation Center (Northeast), Shenyang, China.
Yuzhou LiuCollege of Information and Electrical Engineering, Shenyang Agricultural University, National Digital Agriculture Regional Innovation Center (Northeast), Shenyang, China.
Qi ZhengCollege of Information and Electrical Engineering, Shenyang Agricultural University, National Digital Agriculture Regional Innovation Center (Northeast), Shenyang, China.
Junyong WangCollege of Information and Electrical Engineering, Shenyang Agricultural University, National Digital Agriculture Regional Innovation Center (Northeast), Shenyang, China.
Huiduo YuCollege of Information and Electrical Engineering, Shenyang Agricultural University, National Digital Agriculture Regional Innovation Center (Northeast), Shenyang, China.
Chunling ChenCollege of Information and Electrical Engineering, Shenyang Agricultural University, National Digital Agriculture Regional Innovation Center (Northeast), Shenyang, China.
Shuang GuoSchool of Intelligent Science and Information Engineering, Shenyang University, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unmanned Aerial Vehicle (UAV), as a new generation of intelligent equipment, has gradually become an essential tool across multiple industries due to its high maneuverability and strong task adaptability. UAV payload technology (UPT) serves as a key support for enhancing mission performance and expanding application scenarios. UPT is being rapidly integrated into agriculture and other key fields, emerging as a driving force for the low-altitude economy and intelligent operations. This study systematically analyzed and discussed the development status of UPT, its typical application scenarios, and the challenges faced. By conducting a comprehensive review of global research on UPT from 2012 to 2025, this review summarized research hotspots and revealed evolutionary trends. The findings demonstrated that UPT had made notable progress in typical application areas, including crop monitoring, precision agricultural operations, agricultural product harvesting and aerial transportation, power line inspection, emergency rescue, and logistics. However, UPT was still constrained by limited autonomous perception and path planning capabilities, insufficient universality of payload platforms, a lack of standardized device interfaces, as well as challenges related to endurance, communication, and operational stability under adverse weather conditions. Future research should focus on lightweight and multifunctional payload design, intelligent operation control, and modular and standardized integration, while building a "satellite-UAV-ground" collaborative perception and decision-making system. The outcomes of this study provide both theoretical reference and practical guidance for promoting UAV adoption in agriculture and other low-altitude application scenarios, thereby contributing to the sustainable development of smart agriculture and the low-altitude economy.

Indexed as

agricultureapplication scenarioslow-altitude economypayload technologyUAV

Identifiers

PMID41459473
PMCPMC12741142

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.