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Hyperspectral imagery of Pinus strobiformis infected with fungal pathogen

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https://ir.library.oregonstate.edu/concern/datasets/pn89df234

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Abstract
  • Hyperspectral images were taken from March till October, 2018, of southwestern white pine (Pinus strobiformis), SWWP, seedlings of ten different seed-source families. Half of the seedlings were inoculated with white pine blister rust (Cronartium ribicola). Visual assessments of vigor coincided with hyperspectral data acquisition. The aim of the experiment was to use hyperspectral data to automaticaly and objectively identify infection and degree of infection in SWWP seedlings. Moreover, we developed and evaluated a feature importance algorithm to identify the most usefull hyperspectral features for classification tasks.
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Citation
  • Haagsma, M.; Page, G.F.M., Johnson, J.S.(2020) Hyperspectral imagery of Pinus strobiformis infected with fungal pathogen (Version 1) [Dataset]. Oregon State University. https://doi.org/10.7267/pn89df234
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Funding Statement (additional comments about funding)
  • National Science Foundation under grant nr. NSF-CCF 1521687
  • National Science Foundation under grant nr. NSF-EAR 1440506
  • National Science Foundation under grant nr. NSF-DEB 1442456-1442597
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Additional Information
  • Related publication: Marja Haagsma, Gerald F. M. Page, Jeremy S. Johnson, Christopher Still, Kristen M. Waring, Richard A. Sniezko, John S. Selker. Using hyperspectral imagery to detect an invasive fungal pathogen and symptom severity in Pinus strobiformis seedlings of different genotypes. [in progress]

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Artikel

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file details instructions_to_download_dataset.txt 2020-10-28 Öffentlich Herunterladen
file details README.txt 2020-11-09 Öffentlich Herunterladen
file details Dataset_Haagsma_pn89df234.torrent 2020-11-09 Öffentlich Herunterladen