Abstract
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, ΦF, 17% ∼ 31%), which confirms the contribution of physiological variation to SIF. We further evaluated whether ΦF indicated plant responses under high-temperature and high vapor pressure deficit (VPD) stresses. The plot-scale data showed that ΦF responded to the proxy for physiological stress (partial correlation coefficient, r p= 0.40, p< 0.001) while non-physiological signals of SIF did not respond (p> 0.1). The field-scale ΦF data showed water deficit stress from the comparison between irrigated and rainfed fields, and ΦF 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 ΦF 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 ΦF reflects crop physiological responses to environmental stresses with greater sensitivity to stress factors than SIF, and the stress quantification capability of ΦF is spatially scalable. Utilizing ΦF for physiological investigations will contribute to improve our understanding of vegetation responses to high-temperature and high-VPD stresses.
Highlights
Crop remote sensing needs to quantify environmental stress impacts on both canopy structure and plant physiology to fully understand environmental impacts on crop productivity and yield (Hatfield et al 2008, Guan et al 2017)
This study focused on the U.S Corn Belt where one-third of the global corn and soybean supply is produced, and we investigated non-physiological and physiological information contained in far-red Sun-induced chlorophyll fluorescence (SIF) (SIF indicates far-red SIF throughout the manuscript) responding to the major crop stress factors, high temperature and high vapor pressure deficit (VPD)
We found from the partial correlation results that the SIF-green chlorophyll vegetation index (GCVI) correlation was largely attributed to NIRvP, while the SIF-canopy temperature correlation was entirely attributed to ΦF, which showed even greater sensitivity to canopy temperature than SIF (figure 3(e))
Summary
Crop remote sensing needs to quantify environmental stress impacts on both canopy structure and plant physiology to fully understand environmental impacts on crop productivity and yield (Hatfield et al 2008, Guan et al 2017). Remote sensingbased monitoring has been effective in quantifying crop responses to various environmental stresses, it has been primarily focused on the structural variability of crops and insufficient in quantifying physiological stress impacts. SIF has shown its potential for quantifying plant physiological variability through higher accuracy and sensitivity in quantifying crop productivity or crop stress when compared to existing remote sensing approaches (Sun et al 2015, Song et al 2018, Li et al 2020a).
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