Spectral ecophysiology: hyperspectral pressure-volume curves to estimate leaf turgor loss.

Autor: Castillo-Argaez R; Agronomy Department, University of Florida, Gainesville, FL, 32611, USA., Sapes G; Agronomy Department, University of Florida, Gainesville, FL, 32611, USA., Mallen N; Agronomy Department, University of Florida, Gainesville, FL, 32611, USA., Lippert A; Agronomy Department, University of Florida, Gainesville, FL, 32611, USA., John GP; Department of Biology, University of Florida, Gainesville, FL, 32611, USA., Zare A; Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, 32611, USA., Hammond WM; Agronomy Department, University of Florida, Gainesville, FL, 32611, USA.
Jazyk: angličtina
Zdroj: The New phytologist [New Phytol] 2024 May; Vol. 242 (3), pp. 935-946. Date of Electronic Publication: 2024 Mar 14.
DOI: 10.1111/nph.19669
Abstrakt: Turgor loss point (TLP) is an important proxy for plant drought tolerance, species habitat suitability, and drought-induced plant mortality risk. Thus, TLP serves as a critical tool for evaluating climate change impacts on plants, making it imperative to develop high-throughput and in situ methods to measure TLP. We developed hyperspectral pressure-volume curves (PV curves) to estimate TLP using leaf spectral reflectance. We used partial least square regression models to estimate water potential (Ψ) and relative water content (RWC) for two species, Frangula caroliniana and Magnolia grandiflora. RWC and Ψ's model for each species had R 2  ≥ 0.7 and %RMSE = 7-10. We constructed PV curves with model estimates and compared the accuracy of directly measured and spectra-predicted TLP. Our findings indicate that leaf spectral measurements are an alternative method for estimating TLP. F. caroliniana TLP's values were -1.62 ± 0.15 (means ± SD) and -1.62 ± 0.34 MPa for observed and reflectance predicted, respectively (P > 0.05), while M. grandiflora were -1.78 ± 0.34 and -1.66 ± 0.41 MPa (P > 0.05). The estimation of TLP through leaf reflectance-based PV curves opens a broad range of possibilities for future research aimed at understanding and monitoring plant water relations on a large scale with spectral ecophysiology.
(© 2024 The Authors. New Phytologist © 2024 New Phytologist Foundation.)
Databáze: MEDLINE
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