Dataset Information

Dynamic leaf energy balance: deriving stomatal conductance from thermal imaging in a dynamic environment.

ABSTRACT: In spite of the significant progress made in recent years, the use of thermography to derive biologically relevant traits remains a challenge under fluctuating conditions. The aim of this study was to rethink the current method to process thermograms and derive temporal responses of stomatal conductance (gsw) using dynamic energy balance equations. Time-series thermograms provided the basis for a spatial and temporal characterization of gsw responses in wheat (Triticum aestivum). A leaf replica with a known conductance was used to validate the approach and to test the ability of our model to be used with any material and under any environmental conditions. The results highlighted the importance of the co-ordinated stomatal responses that run parallel to the leaf blade despite their patchy distribution. The diversity and asymmetry of the temporal response of gsw observed after a step increase and step decrease in light intensity can be interpreted as a strategy to maximize photosynthesis per unit of water loss and avoid heat stress in response to light flecks in a natural environment. This study removes a major bottleneck for plant phenotyping platforms and will pave the way to further developments in our understanding of stomatal behaviour.

SUBMITTER: Vialet-Chabrand S

PROVIDER: S-EPMC6506762 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Dynamic leaf energy balance: deriving stomatal conductance from thermal imaging in a dynamic environment.

Vialet-Chabrand Silvere S Lawson Tracy T

Journal of experimental botany 20190501 10

In spite of the significant progress made in recent years, the use of thermography to derive biologically relevant traits remains a challenge under fluctuating conditions. The aim of this study was to rethink the current method to process thermograms and derive temporal responses of stomatal conductance (gsw) using dynamic energy balance equations. Time-series thermograms provided the basis for a spatial and temporal characterization of gsw responses in wheat (Triticum aestivum). A leaf replica ...[more]

PMID: 30793211

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Project description:The dual-source Shuttleworth-Wallace model has been widely used to estimate and partition crop evapotranspiration (?ET). Canopy stomatal conductance (Gsc), an essential parameter of the model, is often calculated by scaling up leaf stomatal conductance, considering the canopy as one single leaf in a so-called "big-leaf" model. However, Gsc can be overestimated or underestimated depending on leaf area index level in the big-leaf model, due to a non-linear stomatal response to light. A dual-leaf model, scaling up Gsc from leaf to canopy, was developed in this study. The non-linear stomata-light relationship was incorporated by dividing the canopy into sunlit and shaded fractions and calculating each fraction separately according to absorbed irradiances. The model includes: (1) the absorbed irradiance, determined by separately integrating the sunlit and shaded leaves with consideration of both beam and diffuse radiation; (2) leaf area for the sunlit and shaded fractions; and (3) a leaf conductance model that accounts for the response of stomata to PAR, vapor pressure deficit and available soil water. In contrast to the significant errors of Gsc in the big-leaf model, the predicted Gsc using the dual-leaf model had a high degree of data-model agreement; the slope of the linear regression between daytime predictions and measurements was 1.01 (R2?=?0.98), with RMSE of 0.6120 mm s-1 for four clear-sky days in different growth stages. The estimates of half-hourly ?ET using the dual-source dual-leaf model (DSDL) agreed well with measurements and the error was within 5% during two growing seasons of maize with differing hydrometeorological and management strategies. Moreover, the estimates of soil evaporation using the DSDL model closely matched actual measurements. Our results indicate that the DSDL model can produce more accurate estimation of Gsc and ?ET, compared to the big-leaf model, and thus is an effective alternative approach for estimating and partitioning ?ET.

Dataset Information

Dynamic leaf energy balance: deriving stomatal conductance from thermal imaging in a dynamic environment.

Publications

Dynamic leaf energy balance: deriving stomatal conductance from thermal imaging in a dynamic environment.

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