Abstract. The development of functional-structural plant models requires an increasing amount of computer modelling. All these models are developed by different teams in various contexts and with different goals. Efficient and flexible computational frameworks are required to augment the interaction between these models, their reusability, and the possibility to compare them on identical datasets. In this paper, we present an open-source platform, OpenAlea, that provides a user-friendly environment for modellers, and advanced deployment methods. OpenAlea allows researchers to build models using a visual programming interface and provides a set of tools and models dedicated to plant modelling. Models and algorithms are embedded in OpenAlea 'components' with well defined input and output interfaces that can be easily interconnected to form more complex models and define more macroscopic components. The system architecture is based on the use of a general purpose, high-level, object-oriented script language, Python, widely used in other scientific areas. We present a brief rationale that underlies the architectural design of this system and we illustrate the use of the platform to assemble several heterogeneous model components and to rapidly prototype a complex modelling scenario.

Light interception and radiation-use efficiency (RUE) are essential components of plant performance. Their genetic dissections require novel high-throughput phenotyping methods. We have developed a suite of methods to evaluate the spatial distribution of incident light, as experienced by hundreds of plants in a glasshouse, by simulating sunbeam trajectories through glasshouse structures every day of the year; the amount of light intercepted by maize (Zea mays) plants via a functional-structural model using three-dimensional (3D) reconstructions of each plant placed in a virtual scene reproducing the canopy in the glasshouse; and RUE, as the ratio of plant biomass to intercepted light. The spatial variation of direct and diffuse incident light in the glasshouse (up to 24%) was correctly predicted at the single-plant scale. Light interception largely varied between maize lines that differed in leaf angles (nearly stable between experiments) and area (highly variable between experiments). Estimated RUEs varied between maize lines, but were similar in two experiments with contrasting incident light. They closely correlated with measured gas exchanges. The methods proposed here identified reproducible traits that might be used in further field studies, thereby opening up the way for large-scale genetic analyses of the components of plant performance.

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Summary• The emergence of a regular phyllochron from the dynamic processes of leaf initiation, leaf elongation and whorl construction suggests causal relationships between leaf elongation and leaf emergence. This paper presents a hypothesis as to how the ontogeny of the growth zone of leaves is triggered by emergence events, and implements it in a dynamic model of leaf elongation.• Two different experiments, presenting two contrasted cases of relationships between leaf emergence and kinetics of leaf elongation, were analysed and interpreted with the model in terms of the functioning of the growth zone.• Analysis of elongation kinetics revealed that the hypothesis allows for several contrasted elongation patterns that were observed, and for a regular phyllochron emerging from the variable dynamic of elongation. The model was able to simulate these patterns, and helped to identify the mechanisms underlying the key points of the analysis.• The hypothesis is not demonstrated, but its coherence and robustness are established, which should inform a renewal of the modelling of leaf elongation in architectural models.