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 architectural 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.
Generates a realistic solid model of root geometry. SimRoot can modify the functional form of the growth model of a simulated root system or simply the parameters of that model in order to change drastically the geometric aspects of this root system. It is able to calculate nutrient and water uptake as the roots grow. The tool can be used in studies that focus on the effect of specific root traits on resource acquisition.
Simulates solute transport and water flow in and between the soil and the plant systems. R-SWMS is based on the water potential gradient between soil and root nodes. It assumes that soil water is preferably taken up at spatial locations where the energy to bring water to the root collar is minimized. The tool can be used to improve the understanding of water variability and solute transport at the plant scale.
Allows to model 3D architectural plant model. OpenSimRoot is based on interaction of minimodels, which encapsulate the simulation of a single state variable. It can represent the stele diameter, thickness of the cortex, the degree of cortical senescence, the degree of root cortical aerenchyma formation, and the length, diameter and density of root hairs. The tool can be exploited as an extension to physical phenotyping platforms for data interpretation, and trait-function exploration.
Provides a root system architecture characterization software. ARIA is based on a mathematically rigorous approach of converting root images into graphs. It automates phenotyping with the potential of adding additional features. This tool completes large phenotyping experiments required for many quantitative genetic studies. It is able to analyze 2D flat plane images and 3D images of roots.
Models root architecture and its interactions with static and dynamic soil environments. CRootBox provides generic interfaces to interact with external models that simulate the soil environment or root internal states. It offers control of the segment length and hence spatial discretization of the root architecture as numerical grid. The tool is able to simulate explicitly many root architectures on the field scale.
Allows users to analyze root images using machine learning techniques. PRIMAL trains the Random Forest (RF) model and analyzes data. The software can be used to extract descriptors from large libraries of root images. It was used to predict architectural traits based on automatically-extracted image descriptors and trained on a subset of the whole dataset that had been previously analyzed using a semi-automated tool.