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Data underlying the publication: Potato Virus Y Detection in Seed Potatoes Using Deep Learning on Hyperspectral Images

dataset

posted on 16.06.2020, 00:00 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.

Funding

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

History

References

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

Contributors

Wageningen University and Research

Publisher

4TU.Centre for Research Data

Time coverage

2017-06-27/2017-07-03

Geolocation

Location of Potato Virus Y Detection in Seed Potatoes Using Deep Learning on Hyperspectral Images

Geolocation Longitude

5.7132

Geolocation Latitude

52.6732

Format

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

Usage metrics

Keywords

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

Licence

CC BY-SA 4.0