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Aims: Root hairs are important for uptake, especially for nutrients with low mobility in soils with high sorption capacity. Mutants with defective root hairs are expected to have lower nutrient uptake, unless they compensate with more root growth. Since root hairs can also contribute to the plant's water uptake their importance could change over the course of a growing season. It was our objective to investigate the role of root hairs under field conditions. Methods: The root hair mutant rth3 of Zea mays and the corresponding wild-type were grown for two years under field conditions on sand and loam. Results: Shoot growth and P and K uptake of the plants were promoted by the presence of hairs at all growth stages. Differences between genotypes were greater on loam than on sand until tassel emergence, presumably as additional exploitation by hairs is more relevant in loam. Compensation for the absence of root hairs by increased root growth was not observed in absolute terms. The root to shoot ratio was higher for rth3 than for wild-type. Root traits showed high plasticity in response to texture, the most salient being a greater mean root diameter in sand, irrespective of genotype. The mechanism causing the increase in mean root diameter is still unknown. Root length density was higher in sand, which can be explained by a greater need for exploration than exploitation in this substrate. Conclusion: The role of hairs for nutrient uptake could be confirmed under field conditions. The large impact of texture on root growth and consequences for carbon balance require further investigations. [ABSTRACT FROM AUTHOR]

Soils with high stone content represent a challenge to root development, as each stone is an obstacle to root growth. A high stone content also affects soil properties such as temperature or water content, which in turn affects root growth. We investigated the effects of all soil properties combined on root development in the field using both experiments and modeling. Field experiments were carried out in rhizotron facilities during two consecutive growing seasons (wheat [Triticum aestivum L.] and maize [Zea mays L.]) in silty loam soils with high (>50%) and low (<4%) stone contents. We extended the CPlantBox root architecture model to explicitly consider the presence of stones and simulated root growth on the plot scale over the whole vegetation period. We found that a linear increase of stone content resulted in a linear decrease of rooting depth across all stone contents and developmental stages considered, whereas rooting depth was only sensitive to cracks below a certain crack density and at earlier growth stages. Moreover, the impact of precipitation‐influenced soil strength had a relatively stronger impact on simulated root arrival curves during the vegetation periods than soil temperature. Resulting differences between stony and non‐stony soil of otherwise the same crop and weather conditions show similar trends as the differences observed in the rhizotron facilities. The combined belowground effects resulted in differences in characteristic root system measures of up to 48%. In future work, comparison of absolute values will require including shoot effects—in particular, different carbon availabilities. Core Ideas: We present a dynamic root architecture model that considers macroscopic soil properties.Root elongation rate and preferred growth direction are influenced by stones.We simulate the effects of soil properties on root architecture development using field data.Only belowground effects are considered by the root architecture model.Similar trends in measured and simulated root growth are observed in two different soils. [ABSTRACT FROM AUTHOR]

Stomatal regulation and whole plant hydraulic signaling affect water fluxes and stress in plants. Land surface models and crop models use a coupled photosynthesis–stomatal conductance modeling approach. Those models estimate the effect of soil water stress on stomatal conductance directly from soil water content or soil hydraulic potential without explicit representation of hydraulic signals between the soil and stomata. In order to explicitly represent stomatal regulation by soil water status as a function of the hydraulic signal and its relation to the whole plant hydraulic conductance, we coupled the crop model LINTULCC2 and the root growth model SLIMROOT with Couvreur's root water uptake model (RWU) and the HILLFLOW soil water balance model. Since plant hydraulic conductance depends on the plant development, this model coupling represents a two-way coupling between growth and plant hydraulics. To evaluate the advantage of considering plant hydraulic conductance and hydraulic signaling, we compared the performance of this newly coupled model with another commonly used approach that relates root water uptake and plant stress directly to the root zone water hydraulic potential (HILLFLOW with Feddes' RWU model). Simulations were compared with gas flux measurements and crop growth data from a wheat crop grown under three water supply regimes (sheltered, rainfed, and irrigated) and two soil types (stony and silty) in western Germany in 2016. The two models showed a relatively similar performance in the simulation of dry matter, leaf area index (LAI), root growth, RWU, gross assimilation rate, and soil water content. The Feddes model predicts more stress and less growth in the silty soil than in the stony soil, which is opposite to the observed growth. The Couvreur model better represents the difference in growth between the two soils and the different treatments. The newly coupled model (HILLFLOW–Couvreur's RWU–SLIMROOT–LINTULCC2) was also able to simulate the dynamics and magnitude of whole plant hydraulic conductance over the growing season. This demonstrates the importance of two-way feedbacks between growth and root water uptake for predicting the crop response to different soil water conditions in different soils. Our results suggest that a better representation of the effects of soil characteristics on root growth is needed for reliable estimations of root hydraulic conductance and gas fluxes, particularly in heterogeneous fields. The newly coupled soil–plant model marks a promising approach but requires further testing for other scenarios regarding crops, soil, and climate. [ABSTRACT FROM AUTHOR]

Three-dimensional models of root growth, architecture and function are becoming important tools that aid the design of agricultural management schemes and the selection of beneficial root traits. However, while benchmarking is common in many disciplines that use numerical models, such as natural and engineering sciences, functional-structural root architecture models have never been systematically compared. The following reasons might induce disagreement between the simulation results of different models: different representation of root growth, sink term of root water and solute uptake and representation of the rhizosphere. Presently, the extent of discrepancies is unknown, and a framework for quantitatively comparing functional-structural root architecture models is required. We propose, in a first step, to define benchmarking scenarios that test individual components of complex models: root architecture, water flow in soil and water flow in roots. While the latter two will focus mainly on comparing numerical aspects, the root architectural models have to be compared at a conceptual level as they generally differ in process representation. Therefore, defining common inputs that allow recreating reference root systems in all models will be a key challenge. In a second step, benchmarking scenarios for the coupled problems are defined. We expect that the results of step 1 will enable us to better interpret differences found in step 2. This benchmarking will result in a better understanding of the different models and contribute toward improving them. Improved models will allow us to simulate various scenarios with greater confidence and avoid bugs, numerical errors or conceptual misunderstandings. This work will set a standard for future model development. [ABSTRACT FROM AUTHOR]

Background and Aims Root architecture development determines the sites in soil where roots provide input of carbon and take up water and solutes. However, root architecture is difficult to determine experimentally when grown in opaque soil. Thus, root architecture models have been widely used and been further developed into functional--structural models that simulate the fate of water and solutes in the soil--root system. The root architecture model CRootBox presented here is a flexible framework to model root architecture and its interactions with static and dynamic soil environments. Methods CRootBox is a C++-based root architecture model with Python binding, so that CRootBox can be included via a shared library into any Python code. Output formats include VTP, DGF, RSML and a plain text file containing coordinates of root nodes. Furthermore, a database of published root architecture parameters was created. The capabilities of CRootBox for the unconfined growth of single root systems, as well as the different parameter sets, are highlighted in a freely available web application. Key results The capabilities of CRootBox are demonstrated through five different cases: (1) free growth of individual root systems; (2) growth of root systems in containers as a way to mimic experimental setups; (3) fieldscale simulation; (4) root growth as affected by heterogeneous, static soil conditions; and (5) coupling CRootBox with code from the book Soil physics with Python to dynamically compute water flow in soil, root water uptake and water flow inside roots. Conclusions 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. [ABSTRACT FROM AUTHOR]

How much water can be taken up by roots and how this depends on the root and water distributions in the root zone are important questions that need to be answered to describe water fluxes in the soil-plant-atmosphere system. Physically based root water uptake (RWU) models that relate RWU to transpiration, root density, and water potential distributions have been developed but used or tested far less. This study aims at evaluating the simulated RWU of winter wheat using the empirical Feddes-Jarvis (FJ) model and the physically based Couvreur (C) model for different soil water conditions and soil textures compared to sap flow measurements. Soil water content (SWC), water potential, and root development were monitored noninvasively at six soil depths in two rhizotron facilities that were constructed in two soil textures: stony vs. silty, with each of three water treatments: sheltered, rainfed, and irrigated. Soil and root parameters of the two models were derived from inverse modeling and simulated RWU was compared with sap flow measurements for validation. The different soil types and water treatments resulted in different crop biomass, root densities, and root distributions with depth. The two models simulated the lowest RWU in the sheltered plot of the stony soil where RWU was also lower than the potential RWU. In the silty soil, simulated RWU was equal to the potential uptake for all treatments. The variation of simulated RWU among the different plots agreed well with measured sap flow but the C model predicted the ratios of the transpiration fluxes in the two soil types slightly better than the FJ model. The root hydraulic parameters of the C model could be constrained by the field data but not the water stress parameters of the FJ model. This was attributed to differences in root densities between the different soils and treatments which are accounted for by the C model, whereas the FJ model only considers normalized root densities. The impact of differences in root density on RWUcould be accounted for directly by the physically based RWUmodel but not by empirical models that use normalized root density functions. [ABSTRACT FROM AUTHOR]

In 1978, Landsberg and Fowkes presented a solution of the water flow equation inside a root with uniform hydraulic properties. These properties are root radial conductivity and axial conductance, which control, respectively, the radial water flow between the root surface and xylem and the axial flow within the xylem. From the solution for the xylem water potential, functions that describe the radial and axial flow along the root axis were derived. These solutions can also be used to derive root macroscopic parameters that are potential input parameters of hydrological and crop models. In this paper, novel analytical solutions of the water flow equation are developed for roots whose hydraulic properties vary along their axis, which is the case for most plants. We derived solutions for single roots with linear or exponential variations of hydraulic properties with distance to root tip. These solutions were subsequently combined to construct single roots with complex hydraulic property profiles. The analytical solutions allow one to verify numerical solutions and to get a generalization of the hydric behaviour with the main influencing parameters of the solutions. The resulting flow distributions in heterogeneous roots differed from those in uniform roots and simulations led to more regular, less abrupt variations of xylem suction or radial flux along root axes. The model could successfully be applied to maize effective root conductance measurements to derive radial and axial hydraulic properties. We also show that very contrasted root water uptake patterns arise when using either uniform or heterogeneous root hydraulic properties in a soil-root model. The optimal root radius that maximizes water uptake under a carbon cost constraint was also studied. The optimal radius was shown to be highly dependent on the root hydraulic properties and close to observed properties in maize roots. We finally used the obtained functions for evaluating the impact of root maturation versus root growth on water uptake. Very diverse uptake strategies arise from the analysis. These solutions open new avenues to investigate for optimal genotype-environment-management interactions by optimization, for example, of plant-scale macroscopic hydraulic parameters used in ecohydrogolocial models. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Split root experiments have the potential to disentangle water transport in roots and soil, enabling the investigation of the water uptake pattern of a root system. Interpretation of the experimental data assumes that water flow between the split soil compartments does not occur. Another approach to investigate root water uptake is by numerical simulations combining soil and root water flow depending on the parameterization and description of the root system. Our aim is to demonstrate the synergisms that emerge from combining split root experiments with simulations. We show how growing root architectures derived from temporally repeated X-ray CT scanning can be implemented in numerical soil-plant models. Faba beans were grown with and without split layers and exposed to a single drought period during which plant and soil water status were measured. Root architectures were reconstructed from CT scans and used in the model R-SWMS (root-soil water movement and solute transport) to simulate water potentials in soil and roots in 3D as well as water uptake by growing roots in different depths. CT scans revealed that root development was considerably lower with split layers compared to without. This coincided with a reduction of transpiration, stomatal conductance and shoot growth. Simulated predawn water potentials were lower in the presence of split layers. Simulations showed that this was related to an increased resistance to vertical water flow in the soil by the split layers. Comparison between measured and simulated soil water potentials proved that the split layers were not perfectly isolating and that redistribution of water from the lower, wetter compartments to the drier upper compartments took place, thus water losses were not equal to the root water uptake from those compartments. Still, the layers increased the resistance to vertical flow which resulted in lower simulated collar water potentials that led to reduced stomatal conductance and growth. [ABSTRACT FROM AUTHOR]

The rhizosphere refers to the soil area that is directly and actively influenced by root exudation and secretions. In terms of its spatio-temporal pattern, the rhizosphere is a not a fixed-size region, but consists of gradients in biological, chemical and physical properties that vary radially, longitudinally and temporally along the root. A better understanding of the rhizosphere in terms of root exudation and secretions dynamics and associated biogeochemical processes is critical for maintaining the health of plant growth and the composition of the organisms within the rhizosphere. Various types of organic substances are released by roots. Their crucial impact on rhizosphere properties and related functional processes depends on their spatio-temporal concentration distribution around roots. Further more, different plant species/genotypes have varying root architectures, and individual rhizodeposits have their own diffusion coefficients and decomposition rates. Their re- lease patterns, root growth dynamics and solute transport are jointly responsible for the distribution of the rhizodeposit in the soil. Here, we derive a mathematical model that simulates the spatio-temporal distribution of rhizodeposits. The model is based on convolutions of the analytical solution of the 3D convection diffusion equation coupled to a root growth model. In terms of the rhizodeposit distribution, we define the mathematical formulas to describe the rhizosphere and hotspot for each single root of the root system. The model simulations did involve two plant species differing in root architecture (Vicia faba and Zea mays) and two kinds of rhizodeposits (citrate and mucilage) were examined. The impact of the transport parameters (diffusion and sorption coefficients) and the root architecture on the spatio-temporal evolution of the rhizodeposit distribution was also evaluated. The spatio-temporal distribution of the rhizodeposits can be characterized by discriptors, such as the width of the rhizodeposit zone, reactor ratio. The following information about the rhizosphere was highlighted by the model simulation: (a) the dynamics of the root architecture development strongly affects the rhizodeposit distribution in the root zone; (b) each growing root develops a dynamic rhizosphere (i.e. the width of the rhizosphere is varying for a given position behind the root tip-it is increasing over a certain time interval and then decreasing). Its width depends on the value of the diffusion coefficient of the compound in soil. The overlap of individual rhizospheres is more likely to occur for citrate than for mucilage rhizodeposits. Our results improve our understanding of the impact of the spatial and temporal heterogeneity of rhizodeposits input on rhizosphere development for different root system types and substances and gain insight into the computation and interpretation of the development of the rhizosphere mathematically. [ABSTRACT FROM AUTHOR]

Abstract: In arable farming systems, the term ‘subsoil’ refers to the soil beneath the tilled or formerly tilled soil horizon whereas the latter one is denoted as ‘topsoil’. To date, most agronomic and plant nutrition studies have widely neglected subsoil processes involved in nutrient acquisition by crop roots. Based on our current knowledge it can be assumed that subsoil properties such as comparatively high bulk density, low air permeability, and poverty of organic matter, nutrients and microbial biomass are obviously adverse for nutrient acquisition, and sometimes subsoils provide as little as less than 10% of annual nutrient uptake in fertilised arable fields. Nevertheless, there is also strong evidence indicating that subsoil can contribute to more than two-thirds of the plant nutrition of N, P and K, especially when the topsoil is dry or nutrient-depleted. Based on the existing literature, nutrient acquisition from arable subsoils may be conceptualised into three major process components: (I) mobilisation from the subsoil, (II) translocation to the shoot and long-term accumulation in the Ap horizon and (III) re-allocation to the subsoil. The quantitative estimation of nutrient acquisition from the subsoil requires the linking of field experiments with mathematical modelling approaches on different spatial scales including Process Based Models for the field scale and Functional–Structural Plant Models for the plant scale. Possibilities to modify subsoil properties by means of agronomic management are limited, but ‘subsoiling’ – i.e. deep mechanical loosening – as well as the promotion of biopore formation are two potential strategies for increasing access to subsoil resources for crop roots in arable soils. The quantitative role of biopores in the nutrient acquisition from the subsoil is still unclear, and more research is needed to determine the bioaccessibility of nutrients in subsoil horizons. [Copyright &y& Elsevier]