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Agriculture
Special Issues
Smart Spraying Technology in Orchards: Innovation and Application
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Smart Spraying Technology in Orchards: Innovation and Application

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Agricultural Technology".

Deadline for manuscript submissions: 10 November 2025 | Viewed by 1841

Special Issue Editors

Dr. Pengchao Chen

E-Mail Website
Guest Editor
1. College of Electronic Engineering and Artificial Intelligence, South China Agricultural University, Wushan Road, Guangzhou 510642, China
2. National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangzhou 510642, China
Interests: unmanned aerial spraying system (UASS); pesticide application technology; remote sensing; prescription map; spray drift
Special Issues, Collections and Topics in MDPI journals
Dr. Juan Wang

E-Mail Website
Guest Editor
Mechanical and Electrical Engineering College, Hainan University, Haikou 570228, China
Interests: UASS; aerial application; spray deposition; spray drift; environmental risks; LAI; airflow field; deep learning; tropical crops

Special Issue Information

Dear Colleagues,

The adoption of smart spraying technology in orchards is vital for enhancing management practices, boosting production efficiency, and promoting the sustainable development of agriculture. Traditional spraying methods often suffer from uneven application, significant pesticide waste, and low efficiency. In response, this Special Issue explores how smart spraying technology, driven by sensor and image recognition systems, can revolutionize orchard management by optimizing pesticide use, minimizing environmental impact, and ensuring the quality and safety of agricultural products.

By enabling real-time monitoring of orchard environments, pest infestations, and disease outbreaks, smart spraying technology allows for precise, targeted applications that reduce pesticide residues and waste, ensuring effective deposition on fruit tree targets. This Issue will focus on the latest innovations and evaluations of smart spraying systems, with a particular emphasis on improving the efficiency of pest and disease monitoring, reducing application volumes, and enhancing precision.

We welcome interdisciplinary research spanning agriculture, agricultural machinery, artificial intelligence, and botany. Contributions may address the development and application of smart spraying technologies, the assessment of environmental impacts, and the effectiveness of these technologies across various fruit tree species. Topics may also include IoT- and big data-based spraying management. Submissions can take the form of original research, opinion pieces, or reviews.

Dr. Pengchao Chen
Dr. Juan Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • smart spraying technology
  • orchards
  • precise application
  • spray deposition
  • real-time monitoring
  • artificial intelligence
  • pesticide usage
  • IoT-based management

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Published Papers (3 papers)

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Research

18 pages, 13123 KiB  
Article
Field Study of UAV Variable-Rate Spraying Method for Orchards Based on Canopy Volume
by Pengchao Chen, Haoran Ma, Zongyin Cui, Zhihong Li, Jiapei Wu, Jianhong Liao, Hanbing Liu, Ying Wang and Yubin Lan
Agriculture 2025, 15(13), 1374; https://doi.org/10.3390/agriculture15131374 - 27 Jun 2025
Viewed by 318
Abstract
The use of unmanned aerial vehicle (UAV) pesticide spraying technology in precision agriculture is becoming increasingly important. However, traditional spraying methods struggle to address the precision application need caused by the canopy differences of fruit trees in orchards. This study proposes a UAV [...] Read more.
The use of unmanned aerial vehicle (UAV) pesticide spraying technology in precision agriculture is becoming increasingly important. However, traditional spraying methods struggle to address the precision application need caused by the canopy differences of fruit trees in orchards. This study proposes a UAV orchard variable-rate spraying method based on canopy volume. A DJI M300 drone equipped with LiDAR was used to capture high-precision 3D point cloud data of tree canopies. An improved progressive TIN densification (IPTD) filtering algorithm and a region-growing algorithm were applied to segment the point cloud of fruit trees, construct a canopy volume-based classification model, and generate a differentiated prescription map for spraying. A distributed multi-point spraying strategy was employed to optimize droplet deposition performance. Field experiments were conducted in a citrus (Citrus reticulata Blanco) orchard (73 trees) and a litchi (Litchi chinensis Sonn.) orchard (82 trees). Data analysis showed that variable-rate treatment in the litchi area achieved a maximum canopy coverage of 14.47% for large canopies, reducing ground deposition by 90.4% compared to the continuous spraying treatment; variable-rate treatment in the citrus area reached a maximum coverage of 9.68%, with ground deposition reduced by approximately 64.1% compared to the continuous spraying treatment. By matching spray volume to canopy demand, variable-rate spraying significantly improved droplet deposition targeting, validating the feasibility of the proposed method in reducing pesticide waste and environmental pollution and providing a scalable technical path for precision plant protection in orchards. Full article
(This article belongs to the Special Issue Smart Spraying Technology in Orchards: Innovation and Application)
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25 pages, 4740 KiB  
Article
Field Evaluation of Different Unmanned Aerial Spraying Systems Applied to Control Panonychus citri in Mountainous Citrus Orchards
by Zongyin Cui, Li Cui, Xiaojing Yan, Yifang Han, Weiguang Yang, Yilong Zhan, Jiapei Wu, Yingdong Qin, Pengchao Chen and Yubin Lan
Agriculture 2025, 15(12), 1283; https://doi.org/10.3390/agriculture15121283 - 13 Jun 2025
Viewed by 371
Abstract
In mountainous citrus orchards, the application of conventional ground sprayers for the control of citrus red mite (Panonychus citri) is often constrained by complex terrain and low operational efficiency. The Unmanned Aerial Spraying System (UASS), due to its low-altitude, low-volume, and [...] Read more.
In mountainous citrus orchards, the application of conventional ground sprayers for the control of citrus red mite (Panonychus citri) is often constrained by complex terrain and low operational efficiency. The Unmanned Aerial Spraying System (UASS), due to its low-altitude, low-volume, and high-maneuverability characteristics, has emerged as a promising alternative for pest management in such challenging environments. To evaluate the spray performance and field efficacy of different UASS types in controlling P. citri, five representative UASS models (JX25, DP, T1000, E-A2021, and T20), four mainstream pesticide formulations, and four novel tank-mix adjuvants were systematically assessed in a field experiment conducted in a typical hilly citrus orchard. The results showed that T20 delivered the best overall spray deposition, with upper canopy coverage reaching 10.63%, a deposition of 3.01 μg/cm2, and the highest pesticide utilization (43.2%). E-A2021, equipped with a centrifugal nozzle, produced the finest droplets and highest droplet density (120.3–151.4 deposits/cm2), but its deposition and coverage were lowest due to drift. Nonetheless, it exhibited superior penetration (dIPR 72.3%, dDPR 73.5%), facilitating internal canopy coverage. T1000, operating at higher flight parameters, had the weakest deposition. Formulation type had a limited impact, with microemulsions (MEs) outperforming emulsifiable concentrates (ECs) and suspension concentrates (SCs). All adjuvants improved spray metrics, especially Yimanchu and Silwet, which enhanced pesticide utilization to 46.8% and 46.4% for E-A2021 and DP, respectively. Adjuvant use increased utilization by 4.6–11.9%, but also raised ground losses by 1.5–4.2%, except for Yimanchu, which reduced ground loss by 2.3%. In terms of control effect, the rapid efficacy (1–7 days after application, DAA) of UASS spraying was slightly lower than that of ground sprayers—electric spray gun (ESG), while its residual efficacy (14–25 DAA) was slightly higher. The addition of adjuvants improved both rapid and residual efficacy, making it comparable to or even better than ESG. E-A2021 with 5% abamectin·etoxazole ME (5A·E) and Yimanchu achieved 97.4% efficacy at 25 DAA. Among UASSs, T20 showed the rapid control, while E-A2021 outperformed JX25 and T1000 due to finer droplets effectively targeting P. citri. In residual control (14–25 DAA), JX25 with 45% bifenazate·etoxazole SC (45B·E) was most effective, followed by T20. 5A·E and 45B·E showed better residual efficacy than abamectin-based formulations, which declined more rapidly. Adjuvants significantly extended control duration, with Yimanchu performing best. This study demonstrates that with optimized spraying parameters, nozzle types, and adjuvants, UASSs can match or surpass ground spraying in P. citri control in hilly citrus orchards, providing valuable guidance for precision pesticide application in complex terrain. Full article
(This article belongs to the Special Issue Smart Spraying Technology in Orchards: Innovation and Application)
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23 pages, 12752 KiB  
Article
Aerial Spray Droplet Deposition Determination Based on Fluorescence Correction: Exploring the Combination of a Chemical Colorant and Water-Sensitive Paper
by Ziqi Yu, Mingyang Li, Boli Xing, Yu Chang, Hao Yan, Hongyang Zhou, Kun Li, Weixiang Yao and Chunling Chen
Agriculture 2025, 15(9), 931; https://doi.org/10.3390/agriculture15090931 - 24 Apr 2025
Viewed by 464
Abstract
With the rapid development of precision agriculture spraying technology, the evaluation and detection of deposition effects have gradually become research hotspots. Rhodamine-B is often used for the quantitative elution detection of droplet deposition due to its fluorescent properties. In contrast, the method of [...] Read more.
With the rapid development of precision agriculture spraying technology, the evaluation and detection of deposition effects have gradually become research hotspots. Rhodamine-B is often used for the quantitative elution detection of droplet deposition due to its fluorescent properties. In contrast, the method of detecting droplet deposition using water-sensitive paper (WSP) is simple to operate. However, it often faces issues with measurement accuracy due to factors such as irregular droplet diffusion and the excessive hydrophilicity of the sampler material. Based on this, the study proposes a method for correcting WSP deposition assays by using the quantitative elution of chemical colorants as a baseline reference. Experiments were conducted using a DJI T30 unmanned aerial spraying system (UASS) as the spray carrier, with four types of samplers—Ginkgo biloba leaves (GBL), Malus spectabilis leaves (MS), polyvinyl chloride (PVC) cards, and WSP—fixed at nine different angles. The deposition amounts of five concentrations of Rhodamine-B stain sprayed on the samplers were then compared. The results indicate that the correction factor can be influenced by various factors, including the environment, the type of sampler, the concentration of the sprayed colorant, and the angle of the sampler. Deposition correction coefficients for WSP with different samplers were determined to be in the ranges of 1.507 to 1.547 (WSP–GBL), 1.471 to 1.478 (WSP–MS), and 1.312 to 1.391 (WSP–PVC), respectively. The study confirmed the feasibility of the proposed fluorescence-corrected aerial spray droplet deposition method, which retains the advantages of two existing typical deposition determination methods. Additionally, pre-tests should be tailored to experimental conditions, and the choice of colorant concentration should be carefully considered. Full article
(This article belongs to the Special Issue Smart Spraying Technology in Orchards: Innovation and Application)
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