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Background and Aims: Many studies exist in the literature dealing with mathematical representations of root systems, categorized, for example, as pure structure description, partial derivative equations or functional-structural plant models. However, in these studies, root architecture modelling has seldom been carried out at the organ level with the inclusion of environmental influences that can be integrated into a whole plant characterization., Methods: We have conducted a multidisciplinary study on root systems including field observations, architectural analysis, and formal and mathematical modelling. This integrative and coherent approach leads to a generic model (DigR) and its software simulator. Architecture analysis applied to root systems helps at root type classification and architectural unit design for each species. Roots belonging to a particular type share dynamic and morphological characteristics which consist of topological and geometric features. The DigR simulator is integrated into the Xplo environment, with a user interface to input parameter values and make output ready for dynamic 3-D visualization, statistical analysis and saving to standard formats. DigR is simulated in a quasi-parallel computing algorithm and may be used either as a standalone tool or integrated into other simulation platforms. The software is open-source and free to download at http://amapstudio.cirad.fr/soft/xplo/download., Key Results: DigR is based on three key points: (1) a root-system architectural analysis, (2) root type classification and modelling and (3) a restricted set of 23 root type parameters with flexible values indexed in terms of root position. Genericity and botanical accuracy of the model is demonstrated for growth, branching, mortality and reiteration processes, and for different root architectures. Plugin examples demonstrate the model's versatility at simulating plastic responses to environmental constraints. Outputs of the model include diverse root system structures such as tap-root, fasciculate, tuberous, nodulated and clustered root systems., Conclusions: DigR is based on plant architecture analysis which leads to specific root type classification and organization that are directly linked to field measurements. The open source simulator of the model has been included within a friendly user environment. DigR accuracy and versatility are demonstrated for growth simulations of complex root systems for both annual and perennial plants.

Three-dimensional (3D) reconstruction of plants is time-consuming and involves considerable levels of data acquisition. This is possibly one reason why the integration of genetic variability into 3D architectural models has so far been largely overlooked. In this study, an allometry-based approach was developed to account for architectural variability in 3D architectural models of oil palm (Elaeis guineensis Jacq.) as a case study. Allometric relationships were used to model architectural traits from individual leaflets to the entire crown while accounting for ontogenetic and morphogenetic gradients. Inter- and intra-progeny variabilities were evaluated for each trait and mixed-effect models were used to estimate the mean and variance parameters required for complete 3D virtual plants. Significant differences in leaf geometry (petiole length, density of leaflets, and rachis curvature) and leaflet morphology (gradients of leaflet length and width) were detected between and within progenies and were modelled in order to generate populations of plants that were consistent with the observed populations. The application of mixed-effect models on allometric relationships highlighted an interesting trade-off between model accuracy and ease of defining parameters for the 3D reconstruction of plants while at the same time integrating their observed variability. Future research will be dedicated to sensitivity analyses coupling the structural model presented here with a radiative balance model in order to identify the key architectural traits involved in light interception efficiency., (© The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)