PT - JOURNAL ARTICLE AU - Andrea Schnepf AU - Daniel Leitner AU - Magdalena Landl AU - Guillaume Lobet AU - Trung Hieu Mai AU - Shehan Morandage AU - Cheng Sheng AU - Mirjam Zörner AU - Jan Vanderborght AU - Harry Vereecken TI - CRootBox: A structural-functional modelling framework for root systems AID - 10.1101/139980 DP - 2017 Jan 01 TA - bioRxiv PG - 139980 4099 - http://biorxiv.org/content/early/2017/05/19/139980.short 4100 - http://biorxiv.org/content/early/2017/05/19/139980.full AB - 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 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. We present a root architectural model, CRootBox, as a flexible framework to model 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 CSV. We further created a database of published root architectural parameters. The capabilities of CRootBox for the unconfined growth of single root systems, as well as the different parameter sets, are highlighted into a freely available web application.Key results We demonstrate the use of CRootBox for 5 different cases (1) free growth of individual root systems (2) growth of root systems in containers as a way to mimic experimental setups, (3), field scale simulation, (4) root growth as affected by heterogeneous, static soil conditions, and (5) coupling CRootBox with Soil Physics with Python code to dynamically compute water flow in soil, root water uptake, and water flow inside roots.Conclusions In conclusion, we present a fast and flexible functional-structural root model which 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 root on soil. In the future, we plan to extend this approach to the aboveground part of the plant.