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A physiological signal derived from sun-induced chlorophyll fluorescence quantifies crop physiological response to environmental stresses in the U.S. Corn Belt

Bibliographic Data

ID15548554
AuthorsHyungsuk Kimm (0000-0001-8189-0874, University of Illinois Urbana-Champaign), Kaiyu Guan (0000-0002-3499-6382, University of Illinois Urbana-Champaign, corresponding author), Chongya Jiang (0000-0002-1660-7320, University of Illinois Urbana-Champaign), Guofang Miao (0000-0001-5532-932X, University of Illinois Urbana-Champaign), Genghong Wu (0000-0002-6227-6390, University of Illinois Urbana-Champaign), Andrew E Suyker (0000-0002-4394-1607, University of Nebraska–Lincoln), Elizabeth A Ainsworth (0000-0002-3199-8999, University of Illinois Urbana-Champaign), Carl J Bernacchi (0000-0002-2397-425X, University of Illinois Urbana-Champaign), Christopher M Montes (0000-0002-7295-3092, Urbana University), Joseph A Berry (0000-0002-5849-6438, Carnegie Institution for Science), Xi Yang (0000-0002-5095-6735, University of Virginia), Christian Frankenberg (0000-0002-0546-5857, California Institute of Technology), Min Chen (0000-0001-8922-8789, University of Wisconsin–Madison), Philipp Köhler (0000-0003-0427-8934, California Institute of Technology)
Year2021
Volume16
Issue12
Pages124051-124051
Publication date2021-11-19
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEnvironmental Research Letters (JOURNAL)
Journal identifiersISSN: 1748-9326 • E-ISSN: 1748-9326
PublisherIOP Publishing (PUBLISHER • GB)
DOI10.1088/1748-9326/ac3b16
OpenAlexW3214749184
LanguageEN
References cited52

Sun-induced chlorophyll fluorescence (SIF) measurements have shown unique potential for quantifying plant physiological stress. However, recent investigations found canopy structure and radiation largely control SIF, and physiological relevance of SIF remains yet to be fully understood. This study aims to evaluate whether the SIF-derived physiological signal improves quantification of crop responses to environmental stresses, by analyzing data at three different spatial scales within the U.S. Corn Belt, i.e. experiment plot, field, and regional scales, where ground-based portable, stationary and space-borne hyperspectral sensing systems are used, respectively. We found that, when controlling for variations in incoming radiation and canopy structure, crop SIF signals can be decomposed into non-physiological (i.e. canopy structure and radiation, 60% ∼ 82%) and physiological information (i.e. physiological SIF yield, Φ F , 17% ∼ 31%), which confirms the contribution of physiological variation to SIF. We further evaluated whether Φ F indicated plant responses under high-temperature and high vapor pressure deficit (VPD) stresses. The plot-scale data showed that Φ F responded to the proxy for physiological stress (partial correlation coefficient, r p = 0.40, p 0.1). The field-scale Φ F data showed water deficit stress from the comparison between irrigated and rainfed fields, and Φ F was positively correlated with canopy-scale stomatal conductance, a reliable indicator of plant physiological condition (correlation coefficient r = 0.60 and 0.56 for an irrigated and rainfed sites, respectively). The regional-scale data showed Φ F was more strongly correlated spatially with air temperature and VPD ( r = 0.23 and 0.39) than SIF ( r = 0.11 and 0.34) for the U.S. Corn Belt. The lines of evidence suggested that Φ F reflects crop physiological responses to environmental stresses with greater sensitivity to stress factors than SIF, and the stress quantification capability of Φ F is spatially scalable. Utilizing Φ F for physiological investigations will contribute to improve our understanding of vegetation responses to high-temperature and high-VPD stresses

Agronomy · Atmospheric sciences · Biology · Botany · Canopy · Chlorophyll · Chlorophyll fluorescence · Photosynthesis · Physics · Stomatal Conductance · Transpiration · Vapour Pressure Deficit · Environmental Science · Plant responses to elevated CO2 · Plant Water Relations and Carbon Dynamics · Remote Sensing in Agriculture · Soil Science

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