Do specific root zones shape plant net N uptake? Modeling insights from Root-CyNAPS

Tristan Gérault; Christophe Pradal; Romain Barillot; Céline Richard-Molard; Marion Gauthier; Alexandra Jullien; Frédéric Rees

doi:10.1093/insilicoplants/diag008/8661921

January 1, 2026Open Access

Do specific root zones shape plant net N uptake? Modeling insights from Root-CyNAPS

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Key Points

This research aims to understand the impact of specific root zones on plant nitrogen uptake through a modeling approach.
Implemented Root-CyNAPS model in Python
Utilized the Multiscale Tree Graph (MTG) framework
Data made publicly available under CeCILL-C license
No specific findings are presented in the abstract.

Implication

Modeling evaluates how specific root zones affect nitrogen uptake, indicating significant implications for plant growth.

Abstract

MODEL IMPLEMENTATION AND DATA AVAILABILITY STATEMENT: Root-CyNAPS was implemented in Python, leveraging the Multiscale Tree Graph (MTG, Pradal and Godin (2020)) from the OpenAlea platform (Pradal et al., 2008, 2015). Root-CyNAPS is publicly available under a CeCILL-C license at https://github.com/openalea/Root-CyNAPS.

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Cite This Study

Gérault et al. (2026) studied this question.

synapsesocial.com/papers/69f6e5ac8071d4f1bdfc64d2 https://doi.org/10.1093/insilicoplants/diag008/8661921

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Do specific root zones shape plant net N uptake? Modeling insights from Root-CyNAPS

Key Points

Implication

Abstract

Discussion

Cite This Study

Do specific root zones shape plant net N uptake? Modeling insights from Root-CyNAPS

Key Points

Implication

Abstract

Discussion

Cite This Study

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