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    Estimating how the "hidden half" of plants, that is the roots, take up water or the influences of root system architecture or root physiological properties (such as root hydraulic conductance) on efficiency of water uptake is of prime importance for improving crops against water deficits. To unravel soil-root interactions for water, we describe a system that enables a dynamic imaging of the soil water content and of the root system, from the single root to the whole root system scales.This system uses plants grown in rhizotrons filled with sandy soil and is based on the variable attenuation of the intensity of light transmitted through the rhizotron with soil water content (the rhizotron is nearly translucent when saturated and becomes darker as soil water content decreases). Images of the transmitted light during plant water uptake (or exudation) phases are recorded with a camera, showing a qualitative pattern of water content variations. The gray levels of the image pixels are then quantitatively related to water content with a calibration.This system is affordable and can be easily implemented without specific equipment. It is scalable and quick to allow the phenotyping of a range of plant genotypes relative to their water uptake pattern. This pattern can be then related with root system properties (soil colonization, root architecture ) at different plant stages. In combination with modeling , imaging results help in obtaining physiological parameters such as root hydraulic conductivity, distributed root water uptake rates or root xylem water potential. Combination of modeling and experiment further helps in testing biological and physiological assumptions and in predicting the uptake behavior of plants in the field. © 2022. Springer Science+Business Media, LLC, part of Springer Nature.

    Citation

    Claude Doussan. Putting Plant Roots at Light: Temporal Imaging of Plant Roots and Soil Water with a Light Transmission Technique for Linking Water and Root Observations to Soil-Plant Models. Methods in molecular biology (Clifton, N.J.). 2022;2395:227-246

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    PMID: 34822156

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