CRootBox is a fast and flexible functional-structural root model that is based on state-of-the-art computational science methods. Its aim is to facilitate modelling of root responses to environmental conditions as well as the impact of roots on soil. In the future, this approach will be extended to the above-ground part of the plant.

Background and aims The main difficulty in the use of 3D root architecture models is correct parameterization. We evaluated distributions of the root traits inter-branch distance, branching angle and axial root trajectories from contrasting experimental systems to improve model parameterization. Methods We analyzed 2D root images of different wheat varieties (Triticum Aestivum) from three different sources using automatic root tracking. Model input parameters and common parameter patterns were identified from extracted root system coordinates. Simulation studies were used to (1) link observed axial root trajectories with model input parameters (2) evaluate errors due to the 2D (versus 3D) nature of image sources and (3) investigate the effect of model parameter distributions on root foraging performance. Results Distributions of inter-branch distances were approximated with lognormal functions. Branching angles showed mean values <90°. Gravitropism and tortuosity parameters were quantified in relation to downwards reorientation and segment angles of root axes. Root system projection in 2D increased the variance of branching angles. Root foraging performance was very sensitive to parameter distribution and variance. Conclusions 2D image analysis can systematically and efficiently analyze root system architectures and parameterize 3D root architecture models. Effects of root system projection (2D from 3D) and deflection (at rhizotron face) on size and distribution of particular parameters are potentially significant. Abbreviations β, root segment angle to the horizontal ∆β, reorientation angle of an individual root segment D e , diffusion coefficient of a solute in soil ibd, inter-branch distance IRC, inter-root competition μ, mean value σ, standard deviation of the random deflection angle (tortuosity) sg, sensitivity to gravitropism std, standard deviation θ, branching angle in the vertical plane

Background and Aims The use of standard dynamic root architecture models to simulate root growth in soil containing macropores failed to reproduce experimentally observed root growth patterns. We thus developed a new, more mechanistic model approach for the simulation of root growth in structured soil. Methods In our alternative modelling approach, we distinguish between, firstly, the driving force for root growth, which is determined by the orientation of the previous root segment and the influence of gravitropism and, secondly, soil mechanical resistance to root growth. The latter is expressed by its inverse, soil mechanical conductance, and treated similarly to hydraulic conductivity in Darcy's law. At the presence of macropores, soil mechanical conductance is anisotropic, which leads to a difference between the direction of the driving force and the direction of the root tip movement. Results The model was tested using data from the literature, at pot scale, at macropore scale, and in a series of simulations where sensitivity to gravity and macropore orientation was evaluated. Conclusions Qualitative and quantitative comparisons between simulated and experimentally observed root systems showed good agreement, suggesting that the drawn analogy between soil water flow and root growth is a useful one.

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In models of water flow in soil and roots, differences in the soil hydraulic properties of the rhizosphere and the bulk soil are usually neglected. There is, however, strong experimental evidence that rhizosphere and bulk soil hydraulic properties differ significantly from each other due to various root-soil interaction processes. Two such processes, which can also influence each other, are rhizosphere loosening or compaction and mucilage deposition. In this work, we identified realistic gradients in rhizosphere bulk density and mucilage concentration using X-ray CT imaging, respectively, model simulation for two different soil types and soil bulk densities and related them to soil hydraulic parameters. Using a 1D-single-root model, we then evaluated both the individual and combined effects of these gradients on soil water dynamics using scenario simulations. We showed that during soil drying, a lower rhizosphere bulk density leads to an earlier onset of water stress and to a reduced root water uptake that is sustained longer. The presence of mucilage led to a faster reduction of root water uptake. This is due to the stronger effect of mucilage viscosity on hydraulic conductivity compared to the mucilage- induced increase in water retention. Root water uptake was rapidly reduced when both mucilage and rhizosphere bulk density gradients were considered. The intensity of the effect of gradients in rhizosphere bulk density and mucilage concentration depended strongly on the interplay between initial soil hydraulic conditions, soil type and soil bulk densities. Both gradients in rhizosphere bulk density and mucilage concentration appear as a measure to sustain transpiration at a lower level and to avoid fast dehydration.