Early detection of drought stress in Arabidopsis thaliana utilsing a portable hyperspectral imaging setup

Puneet Mishra, Torsten Feller, Martin Schmuck, Andreas Nicol, Alison Nordon

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

18 Citations (Scopus)
31 Downloads (Pure)

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 languageEnglish
Title of host publication2019 10th Workshop on Hyperspectral Imaging and Signal Processing
Subtitle of host publicationEvolution in Remote Sensing
Place of PublicationPiscataway
PublisherIEEE
Number of pages5
ISBN (Print)9781728152943
DOIs
Publication statusPublished - 5 Dec 2019
Event2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) -
Duration: 24 Sept 201926 Sept 2019

Conference

Conference2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)
Period24/09/1926/09/19

Keywords

  • visible-near infrared
  • automatic
  • agriculture
  • digital
  • phenotyping

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