OpenSimRoot is an open-source, functional–structural plant model and mathematical description of root growth and function


Models provide a framework for data and concepts, to advance understanding of research systems that are complex, such as the case for plant roots and the processes controlling efficient use of soil resources. The Root Dynamics Group is aiming to fully integrate modelling within the loop of defining experimental question, supporting experimental design, interpretation of data, and use of that data for simulation of further experimentation.

OpenSimRoot website

1. OpenSimRoot

Simulated root system of bean (left) and maize (right) as rendered with PARAVIEW. Root systems are made up of different root classes, each with their own root diameter, branching rules, growth direction and growth rates. Root cross-sections are not simulated, but illustrate root segment traits that are represented in OPENSIMROOT.

A central root model in use is OpenSimRoot, previously known as SimRoot which was originally a functional structural model to study root phenotypes for nutrient acquisition. In 2016, IBG-2 open sourced an expended version as OpenSimRoot. The model underwent many improvements before open sourcing including coupling to tomographic phenotypic information and to soil water models, and these are reported in full with the model in Postma et al. 2017. IBG-2 hosts and provides international support for the model through a web interface.

Prof. Malcolm Bennett, University of Nottingham, UK

2. What models best describe root water uptake experimental data?

Soil pedon with the hydraulic head indicated in pseudo-color (left) and three barley root systems (right) taking up water from that column. At the dry top, water uptake is negative, meaning that some hydraulic lift occurs in this scenario

A major challenge for modeling and research is to understand limitation to available soil water. Working with the ET Group and Magnetic Resonance Imaging (MRI), data of water uptake per root length is being obtained, and tested with different existing and new models. Accurate representation of root water uptake experimental data in models is a critical step towards identifying new root-based solutions to greater water use efficiency.

Root Dynamics Group: Dr. Johannes Postma, Christian Kuppe
, mit Enabling Technologies Grou

3. Translating lab to field: Applying modelling to understanding root architecture in field environments

Influence of plant density on root architecture
Managing seed planting density is an important and flexible agronomic tool for farmers. Various crop models “guess” on the influence of planting density on root architecture, because direct data were missing and current crop models do not handle root architecture parameters. Barley root architecture and the allocation among root and shoot were strongly influenced by plant density. Detailed phenotyping showed that at higher density plants had fewer tillers, fewer nodal roots and greater finer seminal root system. Results imply that lab-grown plants should be sown at higher density to reflect many cropping systems (Hecht et al., 2016).

Plant sowing density influences root architecture, a birds eye view of the field experiment

Root Dynamics Group PI: Dr. Johannes Postma mit JPPC Group PI: Dr. Kerstin Nagel und Shoot Dynamics Group PI: Prof. Uwe Rascher

Prof. Jens Leon, University of Bonn, Germany

4. Root plasticity studies

Root plasticity is defined as increasing lateral branching density with increasing nutrient availability. Phosphorus (P) availability is high in the top soil, causing branching density to be high in the top as well. At the same time, the reduced branching density deeper down, as a result of plasticity, allows the plant to grow the individual laterals longer. Pseudo-colors show the local P availability.

Understanding root growth in the field, requires understanding of the plasticity responses to vertical gradients in soil parameters. We aim to describe the plasticity responses with the root architectural model OpenSimRoot, in order to estimate possible benefits and tradeoffs with respect to nutrient and water uptake.


  • Institute of Bio- and Geosciences (IBG)
  • Plant Sciences (IBG-2)
Building 06.1 /
Room 211
+49 2461/61-85013

Dr. Johannes Auke Postma

Co-Leader Root Group

  • Institute of Bio- and Geosciences (IBG)
  • Plant Sciences (IBG-2)
Building 06.1 /
Room 015
+49 2461/61-4333

Dr. Frank Hochholdinger, University of Bonn, Germany
Dr. Richard Whalley, Rothamsted Research Centre, UK

5. Development of rhizosphere models

Rhizosphere biology and chemisty is manipulated by the plant and has large impact on nutrient uptake and root architecture. We develop models to understand this interactive effect

Root Dynamics Group PIs: Christian Kuppe, Dr. Josefine Nestler and Dr. Johannes Postma

6. References

Postma, J.A.,  Kuppe, C., Owen, M.R., Mellor, N., Watt, M., et al. (2017) OpenSimRoot: widening the scope and application of root architectural modelsont. New Phytologist, 215(3), 1274-1286.

Hecht, V.L., Temperton, V.M., Nagel, K.A., Rascher, U. and Postma, J. (2016) Sowing Density: A Neglected Factor Fundamentally Affecting Root Distribution and Biomass Allocation of Field Grown Spring Barley (Hordeum Vulgare L.). Front. Plant Sci.

Last Modified: 20.10.2022