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 May 2025 | Viewed by 407

Special Issue Editors


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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
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

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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 (1 paper)

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Research

25 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 90
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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