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Extending Hyperspectral Imaging for Plant Phenotyping to the UV-Range

Brugger, Anna ; Behmann, Jan ; Paulus, Stefan ; Luigs, Hans-Georg ; Kuska, Matheus Thomas ; Schramowski, Patrick ; Kersting, Kristian ; Steiner, Ulrike ; Mahlein, Anne-Katrin (2019)
Extending Hyperspectral Imaging for Plant Phenotyping to the UV-Range.
In: Remote Sensing, 11 (12)
doi: 10.3390/rs11121401
Artikel, Bibliographie

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Kurzbeschreibung (Abstract)

Previous plant phenotyping studies have focused on the visible (VIS, 400–700 nm), near-infrared (NIR, 700–1000 nm) and short-wave infrared (SWIR, 1000–2500 nm) range. The ultraviolet range (UV, 200–380 nm) has not yet been used in plant phenotyping even though a number of plant molecules like flavones and phenol feature absorption maxima in this range. In this study an imaging UV line scanner in the range of 250–430 nm is introduced to investigate crop plants for plant phenotyping. Observing plants in the UV-range can provide information about important changes of plant substances. To record reliable and reproducible time series results, measurement conditions were defined that exclude phototoxic effects of UV-illumination in the plant tissue. The measurement quality of the UV-camera has been assessed by comparing it to a non-imaging UV-spectrometer by measuring six different plant-based substances. Given the findings of these preliminary studies, an experiment has been defined and performed monitoring the stress response of barley leaves to salt stress. The aim was to visualize the effects of abiotic stress within the UV-range to provide new insights into the stress response of plants. Our study demonstrated the first use of a hyperspectral sensor in the UV-range for stress detection in plant phenotyping.

Typ des Eintrags: Artikel
Erschienen: 2019
Autor(en): Brugger, Anna ; Behmann, Jan ; Paulus, Stefan ; Luigs, Hans-Georg ; Kuska, Matheus Thomas ; Schramowski, Patrick ; Kersting, Kristian ; Steiner, Ulrike ; Mahlein, Anne-Katrin
Art des Eintrags: Bibliographie
Titel: Extending Hyperspectral Imaging for Plant Phenotyping to the UV-Range
Sprache: Englisch
Publikationsjahr: 2019
Ort: Basel
Verlag: MDPI
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Remote Sensing
Jahrgang/Volume einer Zeitschrift: 11
(Heft-)Nummer: 12
Kollation: 11 Seiten
DOI: 10.3390/rs11121401
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Kurzbeschreibung (Abstract):

Previous plant phenotyping studies have focused on the visible (VIS, 400–700 nm), near-infrared (NIR, 700–1000 nm) and short-wave infrared (SWIR, 1000–2500 nm) range. The ultraviolet range (UV, 200–380 nm) has not yet been used in plant phenotyping even though a number of plant molecules like flavones and phenol feature absorption maxima in this range. In this study an imaging UV line scanner in the range of 250–430 nm is introduced to investigate crop plants for plant phenotyping. Observing plants in the UV-range can provide information about important changes of plant substances. To record reliable and reproducible time series results, measurement conditions were defined that exclude phototoxic effects of UV-illumination in the plant tissue. The measurement quality of the UV-camera has been assessed by comparing it to a non-imaging UV-spectrometer by measuring six different plant-based substances. Given the findings of these preliminary studies, an experiment has been defined and performed monitoring the stress response of barley leaves to salt stress. The aim was to visualize the effects of abiotic stress within the UV-range to provide new insights into the stress response of plants. Our study demonstrated the first use of a hyperspectral sensor in the UV-range for stress detection in plant phenotyping.

Freie Schlagworte: plant substances, hyperspectral imaging, UV-range, abiotic stress
Zusätzliche Informationen:

This article belongs to the Special Issue Advanced Imaging for Plant Phenotyping

Sachgruppe der Dewey Dezimalklassifikatin (DDC): 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik
600 Technik, Medizin, angewandte Wissenschaften > 600 Technik
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Künstliche Intelligenz und Maschinelles Lernen
Zentrale Einrichtungen
Zentrale Einrichtungen > Centre for Cognitive Science (CCS)
Hinterlegungsdatum: 02 Mai 2024 13:07
Letzte Änderung: 02 Mai 2024 13:07
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