Measuring root system traits of wheat in 2D images to parameterize 3D root architecture models

Background and aimsThe 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.MethodsWe 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.ResultsDistributions 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.Conclusions2D 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

Mechanistic framework to link root growth models with weather and soil physical properties, including example applications to soybean growth in Brazil

Background and aimsRoot elongation is generally limited by a combination of mechanical impedance and water stress in most arable soils. However, dynamic changes of soil penetration resistance with soil water content are rarely included in models for predicting root growth. Better modelling frameworks are needed to understand root growth interactions between plant genotype, soil management, and climate. Aim of paper is to describe a new model of root elongation in relation to soil physical characteristics like penetration resistance, matric potential, and hypoxia.MethodsA new diagrammatic framework is proposed to illustrate the interaction between root elongation, soil management, and climatic conditions. The new model was written in Matlab®, using the root architecture model RootBox and a model that solves the 1D Richards equations for water flux in soil. Inputs: root architectural parameters for Soybean; soil hydraulic properties; root water uptake function in relation to matric flux potential; root elongation rate as a function of soil physical characteristics. Simulation scenarios: (a) compact soil layer at 16 to 20 cm; (b) test against a field experiment in Brazil during contrasting drought and normal rainfall seasons.Results(a) Soil compaction substantially slowed root growth into and below the compact layer. (b) Simulated root length density was very similar to field measurements, which was influenced greatly by drought. The main factor slowing root elongation in the simulations was evaluated using a stress reduction function.ConclusionThe proposed framework offers a way to explore the interaction between soil physical properties, weather and root growth. It may be applied to most root elongation models, and offers the potential to evaluate likely factors limiting root growth in different soils and tillage regimes

Simulating the role of rooting traits in crop-weed competition

Tailoring root systems to particular cropping systems is of interest in Australia's challenging cropping soils. The capacity to better match root systems to the environment in which they grow offers the potential to improve crop productivity. In this study, the ROOTMAP model of crop root growth was used to screen combinations of rooting traits and cropping environments, to identify rooting characteristics important for crop productivity. This study focussed on grain crops growing as perfect weed-free monocultures or in competition with weeds. A sensitivity analysis approach was used to investigate 30 parameters that describe root architecture, the cropping environment and agronomic management. Parameters were ranked in order of importance for water, nitrogen and phosphorus uptake. Parameters controlling the efficient distribution of roots through soil (geotropism index, deflection index, branch angle), and physiological parameters determining the rate of phosphate influx into roots (P uptake kinetics), ranked highest for weed-free crops. In contrast, the most important parameters for plants in competition with weeds were those controlling the intensity of soil foraging (plant density and branch spacing) and rate of root system establishment (relative root growth rate), highlighting the importance of quickly and effectively occupying the soil volume during establishment if a crop is to out-compete weeds. This separation of characteristics into those of greatest benefit to weed-free crops or in crop-weed competition, suggests that there is the potential for tailoring root characteristics to specific conditions

Improving Nitrogen and Phosphorus Management in South-East Australian Cropping Systems

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Using the ROOTMAP model of crop root growth to investigate root-soil interactions

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Delivering a World-class Root Model to Australian Grains Researchers

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Rhizosphere Models

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4R Approach to Nutrient Best Managemetn Practice

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