Loïc Pagès

Water uptake by plant roots: II - Modelling of water transfer in the soil root-system with explicit account of flow within the root system : Comparison with experiments

Soil water uptake by plant roots results from the complex interplay between plant and soil which modulates and determines transport processes at a range of spatial and temporal scales: at small scales, uptake rates are determined by local soil and root hydraulic properties but, at the plant scale, local processes interact within the root system and are integrated through the hydraulic architecture of the root system and plant transpiration. However, because of the inherent complexity of the root system (both structural and functional), plant roots are commonly account for with synthetic but over-simplifying descriptors, valid at a given spatial scale. In this article, we present a model describing both soil and plant processes involved in water uptake at the scale of the whole root system with explicit account of individual roots. This is achieved through the unifying concepts of root system architecture and hydraulic continuity between the soil and plant. The model is based on a combination of architectural, root system hydraulic and soil water transfer modelling. The model can reproduce qualitatively and quantitatively laboratory experimental data obtained from imaging of water uptake by light transmission (cf. Garrigues et al., Water uptake by plant roots: I-Formation and propagation of a water extraction front in mature root systems as evidenced by 2D light transmission imaging. Plant and soil (2006, this issue) or X-ray imaging for two soil types (a sand/clay mix and a sandy clay loam) and different narrow-leaf lupin root systems (taprooted and fibrous), using independently measured soil–plant parameters. Results of the experiments and modelling reported in this paper concur to show that a water extraction front formed on the root system. This uptake front’s spatial extension and propagation were closely related to the local dependence between root and soil hydraulic properties and root axial conductance. Hence, a sharp front formed in the sand/clay mix but was much more attenuated in the sandy loam. Comparison between taprooted and fibrous root systems grown in a sand/clay mix, show that the taprooted architecture induced a more spatially concentrated uptake zone (near the soil surface) with higher flux rates, but with xylem water potential at the base of the root system twice as low than in the fibrous architecture. Modelling provided evidence that hydraulic lift might have occurred when transpiration declined, particularly in soil prone to abrupt variations in soil water potential (sand/clay mix). Finally, such a model, explicitly coupling root system-soil water transfers, can be useful to study water uptake in relation with root architectural traits, distribution of root hydraulic conductance or influence of heterogeneous conditions (localised irrigation, root clumping).

A Novel Image-Analysis Toolbox Enabling Quantitative Analysis of Root System Architecture

We present in this paper a novel, semiautomated image-analysis software to streamline the quantitative analysis of root growth and architecture of complex root systems. The software combines a vectorial representation of root objects with a powerful tracing algorithm that accommodates a wide range of image sources and quality. The root system is treated as a collection of roots (possibly connected) that are individually represented as parsimonious sets of connected segments. Pixel coordinates and gray level are therefore turned into intuitive biological attributes such as segment diameter and orientation as well as distance to any other segment or topological position. As a consequence, user interaction and data analysis directly operate on biological entities (roots) and are not hampered by the spatially discrete, pixel-based nature of the original image. The software supports a sampling-based analysis of root system images, in which detailed information is collected on a limited number of roots selected by the user according to specific research requirements. The use of the software is illustrated with a time-lapse analysis of cluster root formation in lupin (Lupinus albus) and an architectural analysis of the maize (Zea mays) root system. The software, SmartRoot, is an operating system-independent freeware based on ImageJ and relies on cross-platform standards for communication with data-analysis software.

A simulation model of the three-dimensional architecture of the maize root system

In order to study the nutrient and water uptake of rootsin situ, we need a quantitative three-dimensional dynamic model of the root system architecture.The present model takes into account current observations on the morphogenesis of the maize root system. It describes the root system as a set of root axes, characterised by their orders and their inter-node of origin. The evolution of the simulated pattern is achieved by three processes, occuring at each time step: emission of new primary root axes from the shoot, growth and branching of existing root axes. The elongation of an axis depends on its order, inter-node and local growing conditions. Branches appear acropetally at a specified distance from the apex and from former branches, along ranks facing xylem poles, with a branching angle specific to their order and inter-node.From the three-dimensional branched patterns simulated by the model, various outputs, such as root profiles or cross-section maps can be computed, compared to observed data and used as inputs in uptake models. A number of examples of such possible outputs are presented.

Modelling root–soil interactions using three–dimensional models of root growth, architecture and function

BackgroundThree–dimensional root architectural models emerged in the late 1980s, providing an opportunity to conceptualise and investigate that all important part of plants that is typically hidden and difficult to measure and study. These models have progressed from representing pre–defined root architectural arrangements, to simulating root growth in response to heterogeneous soil environments. This was done through incorporating soil properties and more complete descriptions of plant function, moving into the realm of functional-structural plant modelling. Modelling studies are often designed to investigate the relationship between root architectural traits and root distribution in soil, and the spatio–temporal variability of resource supply. Modelling root systems presents an opportunity to investigate functional tradeoffs between foraging strategies (i.e. shallow vs deep rooting) for contrasting resources (immobile versus mobile resources), and their dependence on soil type, rainfall and other environmental conditions. The complexity of the interactions between root traits and environment emphasises the need for models in which traits and environmental conditions can be independently manipulated, unlike in the real world.ScopeWe provide an overview of the development of three–dimensional root architectural models from their origins, to their place today in the world of functional–structural plant modelling. The uses and capability of root architectural models to represent virtual plants and soil environment are addressed. We compare features of six current models, RootTyp, SimRoot, ROOTMAP, SPACSYS, R-SWMS, and RootBox, and discuss the future development of functional-structural root architectural modelling.ConclusionFunctional-structural root architectural models are being used to investigate numerous root–soil interactions, over a range of spatial scales. They are not only providing insights into the relationships between architecture, morphology and functional efficiency, but are also developing into tools that aid in the design of agricultural management schemes and in the selection of root traits for improving plant performance in specific environments.

Modelling the influence of assimilate availability on root growth and architecture

A model has been designed to simulate rubber seedling root development as related to assimilate availability. Each root of the system is defined both as an element of a network of axes, characterized by its order, position and connections and as an individual sink competing for assimilates. At each time step, the growth of each root is calculated as a function of its own growth potential and of assimilate availability calculated within the whole plant. The potential elongation rate of a root is estimated by its apical diameter, which reflects the size of the meristem. When a root is initiated, the apical diameter depends on root type, but it varies thereafter according to assimilate availability. Thus, the latter controls both current and potential elongation. The model was able to simulate periodicity in root development as related to shoot growth and to reproduce differences in sensitivity to assimilate availability related to root type. It thereby validated the hypothesis that root growth but also root system architecture depend on assimilate allocation and that apical diameter is a good indicator of root growth potential. Provided that specific calibration is done, this model may be used for other species.

GRAAL: a model of GRowth, Architecture and carbon ALlocation during the vegetative phase of the whole maize plant: Model description and parameterisation

Abstract A model has been developed to understand the interactions between morphogenetic and carbohydrate partitioning processes during the vegetative development of individual maize plants. It merges models of plant morphogenesis and models simulating the growth of plant compartments as related to assimilate availability. Using object-oriented methods, knowledge is formalised at the object level (local rules of organ development), which has its own properties, and the behaviour of the system arises from interactions between the objects and the integration of the processes into the whole system. Shoot and root organs are initiated as a function of temperature. Their potential growth in size (length, width, diameter) and dry mass depends on temperature and carbon availability. Using the source–sink concept, effective organ growth at each time step (1 day) is calculated from potential organ growth rate and plant carbon availability. Early simulation results indicate that the model makes it possible to reproduce the main features of plant functioning (e.g. kinetics of root:shoot ratio, changes in priority between organs, periods of plant sensitivity and plasticity to carbon availability) and to analyse the sensitivity to the model parameters. The model is shown to be a useful tool for testing functioning hypotheses and for hierarchizing ecophysiological processes involved in stand development.

DART: a software to analyse root system architecture and development from captured images

Image analysis is used in numerous studies of root system architecture (RSA). To date, fully automatic procedures have not been good enough to completely replace alternative manual methods. DART (Data Analysis of Root Tracings) is freeware based on human vision to identify roots, particularly across time-series. Each root is described by a series of ordered links encapsulating specific information and is connected to other roots. The population of links constitutes the RSA. DART creates a comprehensive dataset ready for individual or global analyses and this can display root growth sequences along time. We exemplify here individual tomato root growth response to shortfall in solar radiation and we analyse the global distribution of the inter-root branching distances. DART helps in studying RSA and in producing structured and flexible datasets of individual root growth parameters. It is written in JAVA and relies on manual procedures to minimize the risks of errors and biases in datasets.

Towards developmental modelling of tree root systems

Abstract Knowledge of belowground structures and processes is essential for understanding and predicting ecosystem functioning, and consequently in the development of adaptive strategies to safeguard production from trees and woody plants into the future. In the past, research has mainly been concentrated on growth models for the prediction of agronomic or forest production. Newly emerging scientific challenges, e.g. climate change and sustainable development, call for new integrated predictive methods where root systems development will become a key element for understanding global biological systems. The types of input data available from the various branches of woody root research, including biomass allocation, architecture, biomechanics, water and nutrient supply, are discussed with a view to the possibility of incorporating them into a more generic developmental model. We discuss here the main focus of root system modelling to date, including a description of simple allometric biomass models, and biomechanical stress models, and then build in complexity through static growth models towards architecture models. The next progressive and logical step in developing an inclusive developmental model that integrates these modelling approaches is discussed.

Evaluation of parameters describing the root system architecture of field grown maize plants (Zea mays L.)

The objective of this work was to study elongation curves of maize axile roots throughout their elongation period under field conditions. Relationships between their elongation rate and the extension rate of their branched region were also studied. Maize, early-maturing cultivar Dea, was grown on a deep, barrier-free clay loam (depth 1.80m). Trenches were dug during four periods until after silking and axile roots were excavated. Parameters measured were total length and the lengths of basal and apical unbranched zones. The rank of the bearing phytomer and general data about the carrying plant were also recorded.Results showed that axile roots from lower phytomers had similar elongation rates irrespective of the rank of the carrying phytomer. This elongation rate declined with root age. A monomolecular elongation model was fitted to the experimental data. Elongation was much slower in roots from upper phytomers. A rough linear relationship was found between the elongation rate of axile roots and the length of the apical unbranched zone. This result suggests that laterals appeared on a root segment a constant time after it was formed.Possible mechanisms with may account for the declining elongation rate with root age (increasing distance from aerial parts or adverse environmental conditions in deep soil layers) and variability between individual roots are also discussed.

Geometrical properties of simulated maize root systems: consequences for length density and intersection density

The spatial distribution of root length density (RLD) is important because it affects water and nutrient uptake. It is difficult to obtain reliable estimates of RLD because root systems are very variable and heterogeneous. We identified systematic trends, clustering, and anisotropy as geometrical properties of root systems, and studied their consequences for the sampling and observation of roots. We determined the degree of clustering by comparing the coefficient of variation of a simulated root system with that of a Boolean model. We also present an alternative theoretical derivation of the relation between RLD and root intersection density (RID) based on the theory of random processes of fibres. We show how systematic trends, clustering and anisotropy affect the theoretical relation between RLD and RID, and the consequences this has for measurement of RID in the field. We simulated the root systems of one hundred maize crops grown for a thermal time of 600 K d, and analysed the distribution of RLD and root intersection density RID on regular grids of locations throughout the simulated root systems. Systematic trends were most important in the surface layers, decreasing with depth. Clustering and anisotropy both increased with depth. Roots at depth had a bimodal distribution of root orientation, causing changes in the ratio of RLD/RID. The close proximity of the emerging lateral roots and the parent axis caused clustering which increased the coefficient of variation.