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Soil hydraulic conductivity ( k soil ) drops significantly in dry soils, resulting in steep soil water potential gradients ( ψ s ) near plant roots during water uptake. Coarse soil grid resolutions in root system scale (RSS) models of root water uptake (RWU) generally do not spatially resolve this gradient in drying soils which can lead to a large overestimation of RWU. To quantify this, we consider a benchmark scenario of RWU from drying soil for which a numerical reference solution is available. We analyze this problem using a finite volume scheme and investigate the impact of grid size on the RSS model results. At dry conditions, the cumulative RWU was overestimated by up to 300% for the coarsest soil grid of 4.0 cm and by 30% for the finest soil grid of 0.2 cm, while the computational demand increased from 19 s to 21 h. As an accurate and computationally efficient alternative to the RSS model, we implemented a continuum multi-scale model where we keep a coarse grid resolution for the bulk soil, but in addition, we solve a 1-dimensional radially symmetric soil model at rhizosphere scale around individual root segments. The models at the two scales are coupled in a mass-conservative way. The multi-scale model compares best to the reference solution (−20%) at much lower computational costs of 4 min. Our results demonstrate the need to shift to improved RWU models when simulating dry soil conditions and highlight that results for dry conditions obtained with RSS models of RWU should be interpreted with caution.

• Understanding P uptake in soil–plant systems requires suitable P tracers. The stable oxygen isotope ratio in phosphate (expressed as δ18OP) is an alternative to radioactive labelling, but the degree to which plants preserve the δ18OP value of the P source is unclear. We hypothesised that the source signal will be preserved in roots rather than shoots. • In soil and hydroponic experiments with spring wheat (Triticum aestivum), we replaced irrigation water by 18O-labelled water for up to 10 d. We extracted plant inorganic phosphates with trichloroacetic acid (TCA), assessed temporal dynamics of δ18OTCA-P values after changing to 18O-labelled water and combined the results with a mathematical model. • Within 1 wk, full equilibration of δ18OTCA-P values with the isotope value of the water in the growth medium occurred in shoots but not in roots. Model results further indicated that root δ18OTCA-P values were affected by back transport of phosphate from shoots to roots, with a greater contribution of source P at higher temperatures when back transport was reduced. • Root δ18OTCA-P partially preserved the source signal, providing an indicator of P uptake sources. This now needs to be tested extensively for different species, soil and climate conditions to enable application in future ecosystem studies.

Functional-structural root architecture models have evolved as tools for the design of improved agricultural management practices and for the selection of optimal root traits. In order to test their accuracy and reliability, we present the first benchmarking of root water uptake from soil using five well-established functional-structural root architecture models: DuMux, CPlantBox, R-SWMS, OpenSimRoot and SRI. The benchmark scenarios include basic tests for water flow in soil and roots as well as advanced tests for the coupled soil-root system. The reference solutions and the solutions of the different simulators are available through Jupyter Notebooks on a GitHub repository. All of the simulators were able to pass the basic tests and continued to perform well in the benchmarks for the coupled soil-plant system. For the advanced tests, we created an overview of the different ways of coupling the soil and the root domains as well as the different methods used to account for rhizosphere resistance to water flow. Although the methods used for coupling and modelling rhizosphere resistance were quite different, all simulators were in reasonably good agreement with the reference solution. During this benchmarking effort, individual simulators were able to learn about their strengths and challenges, while some were even able to improve their code. Some now include the benchmarks as standard tests within their codes. Additional model results may be added to the GitHub repository at any point in the future and will be automatically included in the comparison.

This article describes an immersive extended reality reconstruction tool for root system architectures from 3D volumetric scans of soil columns. We have conducted a laboratory user study to assess the performance of new users with our software in comparison to classical and established desktop software. We utilize a functional-structural plant model to derive a synthetic root architecture that serves as objective quantification for the root system architecture reconstruction. Additionally, we have collected quantitative feedback on our software in the form of standardized questionnaires. This work provides an overview of the extended reality software and the advantage of using immersive techniques for 3D data extraction in plant science. Through our formal study, we further provide a quantification of manual root system reconstruction accuracy. We observe an increase in root system architecture reconstruction accuracy (F1) compared to state-of-the-art desktop software and a more robust extraction quality.