Hyperspectral and Thermal Sensing of Stomatal Conductance, Transpiration, and Photosynthesis for Soybean and Maize under Drought

Abstract

During water stress, crops undertake adjustments in functional, structural, and biochemical traits. Hyperspectral data and machine learning techniques (PLS-R) can be used to assess water stress responses in plant physiology. In this study, we investigated the potential of hyperspectral optical (VNIR) measurements supplemented with thermal remote sensing and canopy height (hc) to detect changes in leaf physiology of soybean (C3) and maize (C4) plants under three levels of soil moisture in controlled environmental conditions. We measured canopy evapotranspiration (ET), leaf transpiration (Tr), leaf stomatal conductance (gs), leaf photosynthesis (A), leaf chlorophyll content and morphological properties (hc and LAI), as well as vegetation cover reflectance and radiometric temperature (TL,Rad). Our results showed that water stress caused significant ET decreases in both crops. This reduction was linked to tighter stomatal control for soybean plants, whereas LAI changes were the primary control on maize ET. Spectral vegetation indices (VIs) and TL,Rad were able to track these different responses to drought, but only after controlling for confounding changes in phenology. PLS-R modeling of gs, Tr, and A using hyperspectral data was more accurate when pooling data from both crops together rather than individually. Nonetheless, separated PLS-R crop models are useful to identify the most relevant variables in each crop such as TL,Rad for soybean and hc for maize under our experimental conditions. Interestingly, the most important spectral bands sensitive to drought, derived from PLS-R analysis, were not exactly centered at the same wavelengths of the studied VIs sensitive to drought, highlighting the benefit of having contiguous narrow spectral bands to predict leaf physiology and suggesting different wavelength combinations based on crop type. Our results are only a first but a promising step towards larger scale remote sensing applications (e.g., airborne and satellite). PLS-R estimates of leaf physiology could help to parameterize canopy level GPP or ET models and to identify different photosynthetic paths or the degree of stomatal closure in response to drought.

Drone-Based Hyperspectral and Thermal Imagery for Quantifying Upland Rice Growth and Water Use Efficiency After Biochar Application

“…Correspondingly, the rice canopy surface temperature, an indicator for instantaneous plant water stress [56], was slightly higher in BC2 than the other two groups (Table S1). Moreover, the leaf water content, an indicator for sustained water stress [10], was the lowest in BC2 among the three groups. Although these differences between the biochar groups and the control were generally small in magnitude during the campaign days, if the mild plant stress had been accumulated over time, it could lead to significantly inferior rice growth, explaining the lower LAI and canopy cover in BC2 compared with the control.…”

“…(10) uses the surface temperature as a proxy of aerodynamic temperature, even though is introduce to account for this, underestimates on may result in an overestimation of the sensible heat flux for bare soil area from an overestimated aerodynamic temperature, and subsequently results in negative evapotranspiration in Eq. (10). When this happened, we assigned a zero value for evapotranspiration (reasonable for dry bare soil) and recalculated sensible heat flux H using Eq.…”

LED and HPS Supplementary Light Differentially Affect Gas Exchange in Tomato Leaves

“…Stomatal conductance is a measure of the degree of stomatal opening and density and is a physiological variable related to the regulation of water and carbon assimilation. Moreover, g s can be used as an indicator of plant water status [ 34 ]. Transpiration rate ( E) is closely related to water movement through a plant and its transpiration from leaves, stems, and flowers.…”

Hyperspectral sensing of photosynthesis, stomatal conductance, and transpiration for citrus tree under drought condition

“…Although using remote sensing to assess responses to drought is a very active topic of research, most studies to date have focused on estimating biochemical and structural parameters related to water stress (Sobejano-Paz et al 2020). In this study, physiological and spectral responses to soil drought were assessed.…”

“…Physiological, morphological and biochemical change were observable early at the drought onset (fast changes) or after some time (slow changes) when green plant was encountered soil drought (Acevedo et al 1971, Zaher-Ara et al 2016, Sobejano-Paz et al 2020. Measuring photosynthesis data is a challenge impacted by heterogenetic environmental parameters such as soil moisture content (Zhang et al 2020).…”