Detection of the metabolic response to drought stress using hyperspectral reflectance

Published by Oxford University Press on behalf of the Society for Experimental Biology 2021.

Bibliographische Detailangaben
Veröffentlicht in:Journal of experimental botany. - 1985. - 72(2021), 18 vom: 30. Sept., Seite 6474-6489
1. Verfasser: Burnett, Angela C (VerfasserIn)
Weitere Verfasser: Serbin, Shawn P, Davidson, Kenneth J, Ely, Kim S, Rogers, Alistair
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2021
Zugriff auf das übergeordnete Werk:Journal of experimental botany
Schlagworte:Journal Article Research Support, U.S. Gov't, Non-P.H.S. Abscisic acid (ABA) climate change crop breeding and management drought stress leaf reflectance metabolites remote sensing stress responses mehr... water deficit water stress Abscisic Acid 72S9A8J5GW
Beschreibung
Zusammenfassung:Published by Oxford University Press on behalf of the Society for Experimental Biology 2021.
Drought is the most important limitation on crop yield. Understanding and detecting drought stress in crops is vital for improving water use efficiency through effective breeding and management. Leaf reflectance spectroscopy offers a rapid, non-destructive alternative to traditional techniques for measuring plant traits involved in a drought response. We measured drought stress in six glasshouse-grown agronomic species using physiological, biochemical, and spectral data. In contrast to physiological traits, leaf metabolite concentrations revealed drought stress before it was visible to the naked eye. We used full-spectrum leaf reflectance data to predict metabolite concentrations using partial least-squares regression, with validation R2 values of 0.49-0.87. We show for the first time that spectroscopy may be used for the quantitative estimation of proline and abscisic acid, demonstrating the first use of hyperspectral data to detect a phytohormone. We used linear discriminant analysis and partial least squares discriminant analysis to differentiate between watered plants and those subjected to drought based on measured traits (accuracy: 71%) and raw spectral data (66%). Finally, we validated our glasshouse-developed models in an independent field trial. We demonstrate that spectroscopy can detect drought stress via underlying biochemical changes, before visual differences occur, representing a powerful advance for measuring limitations on yield
Beschreibung:Date Completed 20.10.2021
Date Revised 20.10.2021
published: Print
Citation Status MEDLINE
ISSN:1460-2431
DOI:10.1093/jxb/erab255