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Title
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Detection of plant responses to drought using close-range hyperspectral imaging in a high-throughput phenotyping platform
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Author
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Abstract
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| The detection and characterization of physiological processes in crop plants under water-limited conditions is essential for the selection of drought-tolerant genotypes and the functional analysis of related genes. Close-range hyperspectral imaging (HSI) is a promising, non-invasive technique for sensing of plant traits, and has the potential to detect plant responses to water deficit stress at an early stage. The present study describes a data analysis method to realize this potential. Reflectance spectra of plants in close-range imaging are highly influenced by illumination effects. Standard normal variate (SNV) was applied to reduce linear illumination effects, while non-linear effects were filtered by discarding the affected pixels through a clustering procedure. Once the illumination effects were eliminated, the remaining differences in plant spectra were assumed to be related to changes in plant traits. To quantify stress-related spectral dynamics, a spectral analysis procedure was developed based on a supervised band selection and a direct calculation of a spectral similarity measure against a reference. The proposed method was tested on HSI data of maize plants acquired in a high-throughput plant phenotyping platform for assessment of drought stress responses and recovery after re-watering events. Results show that the spectral analysis method successfully detected the drought stress responses at an early stage and consistently revealed the recovery effects shortly after the re-watering period. |
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Language
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English
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Source (journal)
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Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing : [proceedings]. - Piscataway, NJ
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EVOLUTION IN REMOTE SENSING (WHISPERS)
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Source (book)
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9th Workshop on Hyperspectral Image and Signal Processing - Evolution in, Remote Sensing (WHISPERS), SEP 23-26, 2018, Amsterdam, NETHERLANDS
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Publication
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New york
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Ieee
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2018
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ISBN
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978-1-72811-581-8
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978-1-72811-581-8
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Volume/pages
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(2018)
, 5 p.
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ISI
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000482659100077
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Full text (open access)
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