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Introducing the new CPlantBox

Computational model may help unravel the complex processes of drought tolerance.

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In recent years, drought has caused significant reductions in crop yield, and projections indicate that drought will become more frequent and severe in many regions in the future.

A study by Liming Xiong and colleagues emphasized that the progress in enhancing the drought tolerance of crop plants through both traditional breeding methods and modern genetic approaches has been hindered by the sluggish pace in uncovering the complex processes underlying drought tolerance. This is because drought tolerance is a very complex trait and plants have many ways to respond to drought.

Furthermore, the impact of drought on plants is influenced by various factors, including its intensity, frequency, duration, and timing. For instance, drought can cause the greatest harm when it occurs during critical stages of crop development, such as after planting or during flowering.

By employing computational modeling, scientists can disentangle the interactions between these processes and gain insights into the causes of reduced yield. This valuable information can then be utilized to mitigate the detrimental effects of drought by guiding management practices or facilitating the development of drought-tolerant plants.

Mona Giraud, PhD student at Forschungszentrum Jülich, and colleagues present the latest implementation of CPlantBox, a user-friendly model that can simulate the effects of drought on plants in in silico Plants. CPlantBox, is a three-dimensional functional structural plant model (3D FSPM) first presented in 2020 by Xiao-Ran Zhou and colleagues. It is capable of simulating plant growth and development and the dynamic movement of water and carbon between the soil, a growing plant, and the atmosphere.

The new version of CPlantBox expands these capabilities. The incorporation of additional modules allows it to better represent physiological and physical processes. For example,

  • an expansion of the analytical water flow module from the whole plant rather than just the root;
  • inclusion of soil water flow rather than disregarding this variable; and
  • inclusion of coupled photosynthesis-transpiration-stomatal regulation modules rather than disregarding the influence of their dynamic values on carbon and water flux.
On the left is a diagram of the modules of the former version of CPlantBox showing a soft coupling between PiafMunch and CPlantBox. On the right is a diagram of the modules of the updated CPlantBox showing a tight coupling between PiafMunch and CPlantBox.
Representation of (A) the former and
(B) current version of CPlantBox.

By changing the interdependencies between the modules, it has higher computing speed and better captures the dynamic processes of a growing plant. Previously, there was a soft coupling between the mechanistic model of water and carbon flow and the model that simulates growth and development of a plant. This means that the output of the model of water and carbon flow was used as an input to the growth and development model at the end of its simulation. The update features a tight coupling mechanism that allows the model of water and carbon flow to supply output data as an input to the growth and development model for each timestep.

3D representation of the virtual plants exposed to a baseline scenario, early dry spell or late dry spell at the end of simulation. Each segment is colored according to its sucrose concentration.

To test the model, the authors simulated the growth of plants experiencing drought conditions at various stages of development. The model successfully calculated the responses of variables like xylem water potential, phloem sucrose concentration, and carbon partitioning at small time intervals for a plant with complex architecture. However, the level of agreement between the simulated results and existing literature varied.

Nonetheless, the authors remain determined – they believe that that any discrepancies between their model and other observed or simulated outcomes are valuable because they provide valuable insights into the fundamental processes involved in how plants respond to drought.

In future work, the authors would like to integrate additional calibration and parameter data into the model to improve CPlantBox’s predictions.


Mona Giraud and others, CPlantBox: a fully coupled modeling platform for the water and carbon fluxes in the Soil-Plant-Atmosphere-Continuum, in silico Plants, 2023;, diad009, https://doi.org/10.1093/insilicoplants/diad009

This article is part of the Functional Structural Plant Model special issue.

The CPlantBox code used to run the simulations is available at https://github.com/Plant-Root-Soil-Interactions-CPlantBox/releases/tag/v2.0. All the files used to run the simulations and plot the results are also available on Zenodo.

Rachel Shekar

Rachel (she/her) is a Founding and Managing Editor of in silico Plants. She has a Master’s Degree in Plant Biology from the University of Illinois. She has over 15 years of academic journal editorial experience, including the founding of GCB Bioenergy and the management of Global Change Biology. Rachel has overseen the social media development that has been a major part of promotion of both journals.

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