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| 001 | 845900 | ||
| 005 | 20210129233726.0 | ||
| 024 | 7 | _ | |a 10.1093/aob/mcx221 |2 doi |
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| 100 | 1 | _ | |a Schnepf, Andrea |0 P:(DE-Juel1)157922 |b 0 |e Corresponding author |u fzj |
| 245 | _ | _ | |a CRootBox: a structural–functional modelling framework for root systems |
| 260 | _ | _ | |a Oxford |c 2018 |b Oxford University Press |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 520 | _ | _ | |a Background and AimsRoot 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 architecture 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. The root architecture model CRootBox presented here is a flexible framework to model root architecture and its interactions with static and dynamic soil environments.MethodsCRootBox 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 a plain text file containing coordinates of root nodes. Furthermore, a database of published root architecture parameters was created. The capabilities of CRootBox for the unconfined growth of single root systems, as well as the different parameter sets, are highlighted in a freely available web application.Key resultsThe capabilities of CRootBox are demonstrated through five 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 code from the book Soil physics with Python to dynamically compute water flow in soil, root water uptake and water flow inside roots.ConclusionsCRootBox is a fast and flexible functional–structural root model that 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 roots on soil. In the future, this approach will be extended to the above-ground part of the plant. |
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| 773 | _ | _ | |a 10.1093/aob/mcx221 |g Vol. 121, no. 5, p. 1033 - 1053 |0 PERI:(DE-600)1461328-1 |n 5 |p 1033 - 1053 |t Annals of botany |v 121 |y 2018 |x 1095-8290 |
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