Polder, G. (Gerrit); van Marrewijk, B. M. (Bart); P.M. (Pieter) Blok; de Villiers, H.A.C. (Hendrik); van der Wolf, J.M. (Jan) et. al. (2020): Data underlying the publication: Potato Virus Y Detection in Seed Potatoes Using Deep Learning on Hyperspectral Images. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:b1f7853c-f52b-4f33-bb06-a6539c7a45a4

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Categories

• Artificial Intelligence and Image Processing
• Agriculture, Land and Farm Management

Keywords

Disease detection Erwinia hyperspectral imaging imaging spectroscopy potato plants Potato Y virus

Geolocation

view on openstreetmap

Time coverage

2017-06-27/2017-07-03

Licence

CC BY-SA 4.0

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by G. (Gerrit) Polder , B. M. (Bart) van Marrewijk , P.M. (Pieter) Blok , H.A.C. (Hendrik) de Villiers , J.M. (Jan) van der Wolf, J. (Jan) Kamp, T. (Toon) Tielen , G.A.L.M. (Gert-Jan) Swinkels, A. (Angelo) Mencarelli , K. (Kees) Boons, Y. (Youri) Schoutsen

Bacterial and virus diseases causes major damage in agriculture. Classifying those is an challenging but important task. This dataset contains +-274 000 spectral line images (512 pixels x 56 bands) of 6 different cultivars of healthy, bacterial (Erwinia) and virus (PVY) infected plants. The coordinates of each image is stored and can be compared with the stored position of individual plants labeled by crop experts.

History

• 2020-06-16 first online, published, posted

Publisher

4TU.Centre for Research Data

Format

media types: application/octet-stream, application/vnd.google-earth.kml+xml, application/x-7z-compressed, image/png, image/tiff, text/plain

References

• https://doi.org/10.3389/fpls.2019.00209

Funding

• Dutch Topsector Agri&Food. Op naar precisielandbouw 2.0, AF-14275

Organizations

Wageningen University and Research