Evidence map›Paper›PMID 40831728›Full record

ArticleFrontiers in plant science2025

Design and testing of a RealSense-based variable spraying control system for field kale.

Yahui Luo, Wen Li, Pin Jiang, Kaiwen Tang, Zhiluo Liang, Yixin Shi

Abstract read
In one paragraph

Article in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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

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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

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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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yahui LuoCollege of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha, China.
Wen LiCollege of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha, China.
Pin JiangCollege of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha, China.
Kaiwen TangCollege of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha, China.
Zhiluo LiangCollege of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha, China.
Yixin ShiCollege of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precision PWM variable spray technology and target detection, identification, and localization technology are key to solving the pesticide waste associated with traditional constant application methods and to improving pesticide utilization for achieving precise application. To address the problems of high pesticide dosage, low application efficiency, and poor kale pest and disease control in traditional upland gap sprayers, a variable spray control system was designed in the study. The system utilizes binocular vision sensors to detect kale targets in the field in real time and achieves accurate pesticide application through pulse-width modulation technology. An improved target detection model based on YOLOv8n is presented, with experimental results showing a detection accuracy of up to 88.7% for field-grown kale. The system was also tested for accuracy-responsive variable spraying in recognition detection tasks, with a 0.2% reduction in the central atomized deposition density coefficient of variation (CV) compared to constant spraying. A flow on/off test model was designed for the solenoid valve duty cycle, determining the correlation decision coefficient for spraying. The correlation coefficient of the flow model exceeded 0.9958 when the duty cycle was in the range of 20-90%, and the actual and theoretical flow rates at the spray terminals were strongly linearly correlated, with a maximum error of only 4.1%. The spraying effect of the system was evaluated through field tests. The results show that the theoretical spray volume of the variable spray control system aligns well with the actual spray volume. In field atomization deposition tests, compared with constant-rate spraying, the target center atomization density in variable spraying mode reached 34.42%. Although droplet deposition and coverage around the crop were slightly reduced, pest and disease control around kale remained effective. In addition, the variable-rate spraying control system further improved pesticide utilization, with a maximum pesticide savings of 26.58%. This study demonstrates the feasibility of binocular vision sensor-guided spraying operations in field environments and provides a reference for its application in field pest control.

Indexed as

atomization deposition densitybinocular vision sensorimproved YOLOv8n algorithmpulse width modulationvariable spraying

Identifiers

PMID40831728
PMCPMC12358357

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.