Drones in Pest Management and Plant Disease Detecting: State of the Art, Achievements and Perspectives
A special issue of Drones (ISSN 2504-446X). This special issue belongs to the section "Drones in Agriculture and Forestry".
Deadline for manuscript submissions: 12 February 2026 | Viewed by 39
Special Issue Editors
Interests: precision agriculture; UAV applications in crop protection; remote sensing; plant disease detection; autonomous spraying systems
Interests: biocontrol; drones; beneficial organisms; precision agriculture; IPM
Interests: precision agriculture; agricultural mechanization; biomass production and procurement chains; environmenatal sciences
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The integration of unmanned aerial vehicles (UAVs) into modern agriculture has opened new frontiers in pest management and plant disease detection. Recent advances in sensor technology, artificial intelligence, and autonomous flight systems have made it possible to identify early symptoms of crop stress, detect disease outbreaks, and perform site-specific interventions with unprecedented precision and efficiency.
This Special Issue, titled "Drones in Pest Management and Plant Disease Detecting: State of the Art, Achievements and Perspectives", aims to gather cutting-edge research and review articles that explore the development, deployment, and assessment of UAV-based technologies in plant protection. Contributions may address both fundamental and applied aspects, from sensor fusion and image analysis to real-time monitoring systems and precision spraying platforms.
We are particularly interested in studies that demonstrate how drones are transforming traditional pest and disease management practices by enabling faster diagnostics, reducing agrochemical use, and improving crop resilience. Papers that combine UAV data with machine learning models, remote sensing, or decision support systems are also welcome.
This Special Issue welcomes submissions on (but not limited to) the following topics:
- UAV-based detection of plant diseases and pests;
- Precision spraying and site-specific crop protection;
- Multispectral, hyperspectral, and thermal imaging in agriculture;
- AI and machine learning for image-based diagnosis;
- Real-time field monitoring and autonomous intervention;
- Integration of UAV data into farm management systems;
- Challenges in regulatory, environmental, and economic aspects.
We look forward to receiving your original research articles and reviews that contribute to the advancement of drone-enabled solutions for sustainable plant health management.
Dr. Zoran Stamenković
Dr. Aleksandar Ivezić
Dr. Antonio Scarfone
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. Drones 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 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
- unmanned aerial vehicle
- pest management
- plant disease detection
- precision agriculture
- remote sensing
- multispectral imaging
- hyperspectral data
- machine learning
- crop monitoring
- smart spraying
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