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Researcher
Jonathan Van Beek
- Disciplines:Geospatial information systems, Horticultural crop production, Remote sensing, Data visualisation and imaging, Photogrammetry and remote sensing, Image processing, Navigation and position fixing, Agricultural plant production not elsewhere classified
Affiliations
- Technology and Food Science (Research unit)
Responsible
From16 Sep 2019 → Today - Technology and Food Science (Research unit)
Responsible
From16 Sep 2019 → 23 Oct 2019
Projects
1 - 10 of 13
- Better quality of Flemish seed potatoes through new cultivation techniquesFrom1 Nov 2025 → TodayFunding: VLAIO - VIL - Agriculture Tracks
- Towards a cost-efficient and sustainable potato cultivation in 2023From1 Nov 2023 → Today
- Climate actions and smart water management with economic potential on farmFrom1 Jan 2023 → Today
- Futureproof DroneXperienceFrom1 Jan 2023 → 31 Dec 2023
- Enhancing soil health through values-based business modelsFrom1 Jan 2023 → Today
- Maximising the CO-benefits of agricultural Digitalisation through conducive digital ECoSystemsFrom1 Oct 2022 → Today
- Operational drone services for agri-foodFrom1 Jan 2022 → 31 Dec 2024
- Substantiated flax growing - Using precision agriculture in fiber flaxFrom1 Oct 2021 → 30 Sep 2025
- SpectroFood: Agrifood quality estimation using hyperspectral techniquesFrom1 Jan 2021 → 31 Dec 2023
- Towards climate-smart sustainable management of agricultural soilsFrom1 Feb 2020 → 31 Jan 2025
Publications
1 - 10 of 14
- Detecting Nematodes in Potato Plants An explainable machine learning approach for detection of potato cyst nematode infections using hyperspectral imaging(2025)Published in: Plant PhenomicsISSN: 2643-6515Issue: 4Volume: 7
- UAV Based Weed Pressure Detection Through Relative Labelling(2025)Published in: Remote Sensing 2020, Vol. 12, Page 1644ISSN: 2072-4292Issue: 20Volume: 17
- Geospatial Framework for Assessing the Suitability and Demand for Agricultural Digital Solutions in Europe: A Tool for Informed Decision-Making(2025)Published in: ISPRS International Journal of Geo-InformationIssue: 5Volume: 14
- Ultra-high-resolution UAV-imaging and supervised deep learning for accurate detection of Alternaria solani in potato fields(2024)Published in: Frontiers in Plant ScienceISSN: 1664-462XVolume: 15
- SpectroFood dataset: A comprehensive fruit and vegetable hyperspectral meta-dataset for dry matter estimation(2024)Published in: DATA IN BRIEFISSN: 2352-3409Volume: 52
- Analysis of hydraulic nozzles for pesticide applications on atomization and droplets distribution characteristics(2023)Published in: Chinese Journal of Pesticide ScienceISSN: 1008-7303
- Ultra-High-Resolution UAV-Based Detection of Alternaria solani Infections in Potato Fields(2022)Published in: Remote Sensing 2020, Vol. 12, Page 1644ISSN: 2072-4292Issue: 24Volume: 14
- Multispectral UAV-Based Monitoring of Leek Dry-Biomass and Nitrogen Uptake across Multiple Sites and Growing Seasons(2022)Published in: Remote Sensing 2020, Vol. 12, Page 1644ISSN: 2072-4292Issue: 24Volume: 14
- Application of Hyperspectral Imaging Systems and Artificial Intelligence for Quality Assessment of Fruit, Vegetables and Mushrooms: A Review(2022)Published in: Biosystems EngineeringISSN: 1537-5110Volume: 222Pages: 156-176
- Hyperspectrale sensoren en 5G maken hun intrede(2021)Published in: Proeftuinnieuws 14ISSN: 0777-9844Volume: 18Pages: 20-21
Linked dataset
1 - 9 of 9
- Hyperspectral Drone Imagery: Bare Soil Fields
- Ultra-high-resolution modified RGB UAV-imaging of Alternaria solani
- Ultra-high-resolution modified RGB UAV-imaging of Alternaria solani
- STEROPES_dataset-29
- SpectroFood dataset
- SpectroFood dataset Apple
- SpectroFood dataset Broccoli
- SpectroFood dataset Leek
- SpectroFood dataset Mushroom