{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T04:35:37Z","timestamp":1776400537101,"version":"3.51.2"},"reference-count":144,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2023,8,31]],"date-time":"2023-08-31T00:00:00Z","timestamp":1693440000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Project FoodLand","award":["H2020"],"award-info":[{"award-number":["H2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remote sensing technology is vital for precision agriculture, aiding in early issue detection, resource management, and environmentally friendly practices. Recent advances in remote sensing technology and data processing have propelled unmanned aerial vehicles (UAVs) into valuable tools for obtaining detailed data on plant diseases with high spatial, temporal, and spectral resolution. Given the growing body of scholarly research centered on UAV-based disease detection, a comprehensive review and analysis of current studies becomes imperative to provide a panoramic view of evolving methodologies in plant disease monitoring and to strategically evaluate the potential and limitations of such strategies. This study undertakes a systematic quantitative literature review to summarize existing literature and discern current research trends in UAV-based applications for plant disease detection and monitoring. Results reveal a global disparity in research on the topic, with Asian countries being the top contributing countries (43 out of 103 papers). World regions such as Oceania and Africa exhibit comparatively lesser representation. To date, research has largely focused on diseases affecting wheat, sugar beet, potato, maize, and grapevine. Multispectral, reg-green-blue, and hyperspectral sensors were most often used to detect and identify disease symptoms, with current trends pointing to approaches integrating multiple sensors and the use of machine learning and deep learning techniques. Future research should prioritize (i) development of cost-effective and user-friendly UAVs, (ii) integration with emerging agricultural technologies, (iii) improved data acquisition and processing efficiency (iv) diverse testing scenarios, and (v) ethical considerations through proper regulations.<\/jats:p>","DOI":"10.3390\/rs15174273","type":"journal-article","created":{"date-parts":[[2023,8,31]],"date-time":"2023-08-31T11:41:18Z","timestamp":1693482078000},"page":"4273","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":97,"title":["A Review on UAV-Based Applications for Plant Disease Detection and Monitoring"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9669-7807","authenticated-orcid":false,"given":"Louis","family":"Kouadio","sequence":"first","affiliation":[{"name":"Centre for Applied Climate Sciences, University of Southern Queensland, Toowoomba, QLD 4350, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9169-8824","authenticated-orcid":false,"given":"Moussa","family":"El Jarroudi","sequence":"additional","affiliation":[{"name":"Water, Environment and Development Unit, SPHERES Research Unit, Department of Environmental Sciences and Management, University of Li\u00e8ge, 6700 Arlon, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2436-0612","authenticated-orcid":false,"given":"Zineb","family":"Belabess","sequence":"additional","affiliation":[{"name":"Plant Protection Laboratory, Regional Center of Agricultural Research of Meknes, National Institute of Agricultural Research, Km 13, Route Haj Kaddour, BP 578, Meknes 50001, Morocco"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5986-8037","authenticated-orcid":false,"given":"Salah-Eddine","family":"Laasli","sequence":"additional","affiliation":[{"name":"Phytopathology Unit, Department of Plant Protection, Ecole Nationale d\u2019Agriculture de Meknes, Meknes 50001, Morocco"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2417-0365","authenticated-orcid":false,"given":"Md Zohurul Kadir","family":"Roni","sequence":"additional","affiliation":[{"name":"Horticultural Sciences Department, University of Florida, Gainesville, FL 32611-0690, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2148-6305","authenticated-orcid":false,"given":"Ibn Dahou Idrissi","family":"Amine","sequence":"additional","affiliation":[{"name":"Department of Agricultural Economics, Ecole Nationale d\u2019Agriculture de Meknes, BP S\/40, Meknes 50001, Morocco"}]},{"given":"Nourreddine","family":"Mokhtari","sequence":"additional","affiliation":[{"name":"Department of Agricultural Economics, Ecole Nationale d\u2019Agriculture de Meknes, BP S\/40, Meknes 50001, Morocco"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9679-8381","authenticated-orcid":false,"given":"Fouad","family":"Mokrini","sequence":"additional","affiliation":[{"name":"Nematology Laboratory, Biotechnology Unit, National Institute of Agricultural Research, CRRA-Rabat, Rabat 10101, Morocco"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2591-4509","authenticated-orcid":false,"given":"J\u00fcrgen","family":"Junk","sequence":"additional","affiliation":[{"name":"Environmental Research and Innovation, Luxembourg Institute of Science and Technology, 4422 Belvaux, Luxembourg"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1299-5733","authenticated-orcid":false,"given":"Rachid","family":"Lahlali","sequence":"additional","affiliation":[{"name":"Phytopathology Unit, Department of Plant Protection, Ecole Nationale d\u2019Agriculture de Meknes, Meknes 50001, Morocco"},{"name":"Plant Pathology Laboratory, AgroBiosciences, College of Sustainable Agriculture and Environmental Sciences, Mohammed VI Polytechnic University, Lot 660, Hay Moulay Rachid, Ben Guerir 43150, Morocco"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e2022239118","DOI":"10.1073\/pnas.2022239118","article-title":"The persistent threat of emerging plant disease pandemics to global food security","volume":"118","author":"Ristaino","year":"2021","journal-title":"Proc. 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