Section: Overall Objectives

Highlights of the Year

• Move of the team to a new campus to join other Inria teams. Until this year, the team was located at the Cirad Lavalette campus in Montpellier. In May 2012, it moved to the Maison de la Modélisation pour le vivant et l'environnement in Montpellier close to the campus of Computer Science research (LIRMM). This move is intended to strengthen the presence of Inria in Montpellier by gathering several Inria teams at the same place, fostering interactions between them and consequently augment the visibility of Inria in the region. It is also meant to support the creation of the Computational Biology Institute of Montpellier, IBC, that succeeded to the national call on investissements d'avenir of ANR, and in which both Zenith and Virtual Plants Inria teams are strongly involved.

• Acceptation of the Inria Large Scale Initiative Morphogenetics. The Inria action d'envergure Morphognetics was evaluated by Inria and accepted. The project gathers 3 Inria teams (Imagine, Morpheme and Virtual Plants) from 2 Inria centers (Rhône-Alpes and Sophia-Antipolis-Méditerranée) and 2 Inra teams (RDP and RFD) from Lyon an Grenoble respectively to address the problem of flower development at early stages. The kick-off meeting of the project was held in November in Montpellier. The project will last 4 years and will focus in particular on the modelling of meristem mechanics during the early phases of organogenesis and how it is related to genes.

• First paper on L-Py published. The first paper describing our simulation system language L-Py has been published in Frontiers in Plant Science. The maturity and the diffusion of this software module increases and is now the basis of the work of several groups worldwide. Several training sessions have been organized by the team in the last two years and will be at the core of the future training program proposed by the Virtual Plants team on plant modeling.

• Completion of a series of papers on tree development analysis using various types of stochastic processes. Understanding tree development over several years has been the object of active research since about 10 years. This has generated the development of integrative models for analyzing tree growth components (ontogeny, climate and local environment influence) and patterns, in particular models combining latent state variables, tree response variables and environmental explanatory variables but also individual and population parameters [39] [2] . This approach has been applied to forest and fruit trees, to tropical and temperate species growing in various conditions (orchard, managed forest stand and unmanaged forest understory) [7] [49] , [16] .