Introduction - Functional-Structural Plant Models give new opportunities to understand plant growth and interaction with their environment. In the last decade, dedicated modelling platforms allowed the creation of a multitude of models, built upon series of dedicated tools for the representation, acquisition, analysis and simulation of plant growth and functioning. Such integrative platforms usually relied on software modules built using multiple computer languages or formalisms. While some efforts have been made for the distribution of these tools over multiple operating systems, the resulting models were usually poorly documented and organized. Models were either created as scripts or scientific workflows. The visual representation of workflows gives an overview of the modelled processes. However, their reuse by non-experts was usually limited to the modification of parameters. Reproducibility was also limited due to deployment and installation complexity on new computers with different configurations. Until recently, no cross-platform packaging suite was robust enough to manage modules built with multiple languages. In a new initiative to alleviate these problems, we explored, in the context of the OpenAlea platform (Pradal et al., 2008), the use of the Jupyter framework (Kluyver et al., 2016) to create virtual research environments for plant modelling. Material and Methods – Our approach is based on Jupyter Notebooks, an increasingly popular web-based interactive computational application. Notebooks allow to formalize modelling scenarios as “computational narrative” (Perkel, 2018) by combining code with clear documentation based on the markdown language that includes illustration and mathematical formula rendering capability. Users can customize the narratives by editing cells of code and execute these cells in any order to refine operations. Notebooks can combine different modelling languages such as Python, R or Julia. Jupyter, combined with web deployment ser