Abstract
Abstract Functional–structural plant models (FSPMs) are powerful tools to explore the complex interplays between plant growth, underlying physiological processes and the environment. Various modelling platforms dedicated to FSPMs have been developed with limited support for collaborative and distributed model design, reproducibility and dissemination. With the objective to alleviate these problems, we used the Jupyter project, an open-source computational notebook ecosystem, to create virtual modelling environments for plant models. These environments combined Python scientific modules, L-systems formalism, multidimensional arrays and 3D plant architecture visualization in Jupyter notebooks. As a case study, we present an application of such an environment by reimplementing V-Mango, a model of mango tree development and fruit production built on interrelated processes of architectural development and fruit growth that are affected by temporal, structural and environmental factors. This new implementation increased model modularity, with modules representing single processes and the workflows between them. The model modularity allowed us to run simulations for a subset of processes only, on simulated or empirical architectures. The exploration of carbohydrate source–sink relationships on a measured mango branch architecture illustrates this possibility. We also proposed solutions for visualization, distant distributed computation and parallel simulations of several independent mango trees during a growing season. The development of models on locations far from computational resources makes collaborative and distributed model design and implementation possible, and demonstrates the usefulness and efficiency of a customizable virtual modelling environment.
Highlights
Functional–structural plant models (FSPMs) provide new opportunities to understand the complex interplays between plant growth, their underlying physiological functioning and the environment (Godin and Sinoquet 2005; Louarn and Song 2020)
Since the state and the number of units change over time, simulating plant growth corresponds to a class of problems formalized as dynamic systems with dynamic structures (DS)2 (Giavitto and Michel 2001), which leads to the definition of dedicated formalisms (Godin et al 2005) such as L-systems (Prusinkiewicz and Lindenmayer 1990)
While models built with agnostic modelling languages such as Python or Java could be integrated within Jupyter notebooks, dedicated formalisms such as L-systems have been widely adopted by the modelling community to create FSPMs and require specific integration
Summary
Functional–structural plant models (FSPMs) provide new opportunities to understand the complex interplays between plant growth, their underlying physiological functioning and the environment (Godin and Sinoquet 2005; Louarn and Song 2020). The key points of this environment are: (i) the seamless integration into Jupyter that allows the easy collaboration, dissemination, visualization and introspection of the generated data and model processes; and (ii) a full compatibility with the Python scientific stack and, direct access to the vast numpy and SciPy ecosystem since the data are almost entirely modelled as multidimensional arrays To illustrate this approach, we developed a new implementation of V-Mango (Boudon et al 2020), a model of mango tree development and fruit production that is composed of complex architectural and fruit growth processes sensitive to environmental (temperature, light, etc.), temporal and structural factors. We addressed the shortcomings of current approaches related to dissemination, reproducibility, complex model handling and interoperability, and greater genericity (Louarn and Song 2020)
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