Artificial Intelligence and Unmanned Aerial Vehicle (UAV) Applications in Horticultural Crop Production
A special issue of Horticulturae (ISSN 2311-7524). This special issue belongs to the section "Protected Culture".
Deadline for manuscript submissions: 20 April 2026 | Viewed by 96
Special Issue Editors
Interests: intelligent robotics system; remote sensing; smart agriculture; intelligent decision-making system
Interests: UAVs-drones; artificial intelligence; machine vision; precision agriculture
Interests: smart agriculture applications; embedded systems developing; FPGA intelligent acceleration system; information and communications technology (ICT); hyperspectral analysis
Special Issue Information
Dear Colleagues,
In recent years, the integration of artificial intelligence (AI) and unmanned aerial vehicle (UAV) technologies has brought unprecedented transformations to horticultural crop production, including fruit trees and vegetables. With the advancement of high-resolution remote sensing, multispectral and hyperspectral imaging, thermal infrared imaging, and 3D reconstruction, UAV drones can now rapidly and accurately acquire spatiotemporal information across large-scale horticultural fields. Combined with deep learning, computer vision, and intelligent decision-making algorithms such as large language models (LLMs) and reinforcement learning, these systems enable precise disease and pest detection and tracking, growth monitoring, yield estimation, and targeted spraying, while also playing a vital role in irrigation management, nutrient health diagnosis, and smart farming practices. Such innovations significantly enhance production efficiency and quality, reduce resource consumption, and promote the development of sustainable and eco-friendly agriculture.
This Special Issue will provide a scholarly exchange platform focusing on the innovative applications of AI and UAV technologies in horticultural crop production. We welcome contributions presenting cutting-edge research findings, advanced methodologies, application cases, and experimental validations, particularly emphasizing their role in improving crop yield and quality, optimizing agricultural resource allocation, and fostering sustainable horticultural development.
Dr. Yongming Chen
Dr. Ping Lin
Dr. Zhiyong Zou
Guest Editors
Manuscript Submission Information
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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. Horticulturae is an international peer-reviewed open access monthly 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 2200 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
- artificial intelligence (AI)
- unmanned aerial vehicles (UAVs)
- deep learning
- computer vision
- decision-making
- horticultural crops production
- smart farming
- pest and disease detection
- yield estimation
- smart irrigation
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