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Abstract
Close-range hyperspectral imaging (HSI) of plants is now a potential tool for non-destructive extraction of plant functional traits. A major motivation is the plant phenotyping related applications where different plant genotypes are explored for different environmental conditions. HSI of Arabidopsis thaliana is of particular importance as it is a model organism in plant biology. In the present work, a portable HSI setup has been used for the monitoring of a set of 6 Arabidopsis thaliana plants. The plants were monitored under controlled watering conditions where 3 plants were watered as normal and the other 3 plants were given 50% of the normal volume of water. The images were pre-processed utilising the standard normal variate (SNV) and changes over time were evaluated using unsupervised clustering over the time series. The results showed an early detection of stress from day 4 onwards compared to the commonly used normalised difference vegetation index (NDVI), which provided detection from day 9.
Original language | English |
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Title of host publication | 2019 10th Workshop on Hyperspectral Imaging and Signal Processing |
Subtitle of host publication | Evolution in Remote Sensing |
Place of Publication | Piscataway |
Publisher | IEEE |
Number of pages | 5 |
ISBN (Print) | 9781728152943 |
DOIs | |
Publication status | Published - 5 Dec 2019 |
Event | 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) - Duration: 24 Sept 2019 → 26 Sept 2019 |
Conference
Conference | 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) |
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Period | 24/09/19 → 26/09/19 |
Keywords
- visible-near infrared
- automatic
- agriculture
- digital
- phenotyping
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- 1 Finished
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Modlife (H2020 MCSA ETN)
Nordon, A. (Principal Investigator)
European Commission - Horizon Europe + H2020
1/11/15 → 31/10/19
Project: Research