Potato Late Blight Detection at the Leaf and Canopy Level Using Hyperspectral Data
Author:
Affiliation:
1. Faculty of Forestry and Environmental Management, University of New Brunswick, Fredericton E5B 5A3, Canada
2. A&L Canada Laboratories, London N5V 3P5, Canada
3. Department of Geography, University of Western Ontario, London N5V 3P5, Canada
Funder
Natural Sciences and Engineering Research Council of Canada
New Brunswick Innovation Foundation
Publisher
Informa UK Limited
Subject
General Earth and Planetary Sciences
Link
https://www.tandfonline.com/doi/pdf/10.1080/07038992.2020.1769471
Reference62 articles.
1. Soybean Disease Monitoring with Leaf Reflectance
2. Detection and differentiation between potato (Solanum tuberosum) diseases using calibration models trained with non-imaging spectrometry data
3. New estimates of leaf angle distribution from terrestrial LiDAR: Comparison with measured and modelled estimates from nine broadleaf tree species
4. Non-destructive estimation of potato leaf chlorophyll and protein contents from hyperspectral measurements using the PROSPECT radiative transfer model
5. In vivo spectroscopy and internal optics of leaves as basis for remote sensing of vegetation
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