Sugar availability suppresses the auxin-induced strigolactone pathway to promote bud outgrowth.

Apical dominance occurs when the growing shoot tip inhibits the outgrowth of axillary buds. Apically-derived auxin in the nodal stem indirectly inhibits bud outgrowth via cytokinins and strigolactones. Recently, sugar deprivation was found to contribute to this phenomenon. Using rose and pea, we investigated whether sugar availability interacts with auxin in bud outgrowth control, and the role of cytokinins and strigolactones, in vitro and in planta. We show that sucrose antagonises auxin's effect on bud outgrowth, in a dose-dependent and coupled manner. Sucrose also suppresses strigolactone inhibition of outgrowth and the rms3 strigolactone-perception mutant is less affected by reducing sucrose supply. However, sucrose does not interfere with the regulation of cytokinin levels by auxin and stimulates outgrowth even with optimal cytokinin supply. These observations were assembled into a computational model in which sucrose represses bud response to strigolactones, largely independently of cytokinin levels. It quantitatively captures our observed dose-dependent sucrose-hormones effects on bud outgrowth and allows us to express outgrowth response to various combinations of auxin and sucrose levels as a simple quantitative law. This study places sugars in the bud outgrowth regulatory network and paves the way for a better understanding of branching plasticity in response to environmental and genotypic factors.

V-Mango: a functional-structural model of mango tree growth, development and fruit production.

BACKGROUND AND AIMS: Mango (Mangifera indica L.) is the fifth most widely produced fruit in the world. Its cultivation, mainly in tropical and sub-tropical regions, raises a number of issues such as the irregular fruit production across years, phenological asynchronisms that lead to long periods of pest and disease susceptibility, and the heterogeneity of fruit quality and maturity at harvest. To address these issues, we developed an integrative functional-structural plant model that synthesizes knowledge about the vegetative and reproductive development of the mango tree and opens up the possible simulation of cultivation practices. METHODS: We designed a model of architectural development in order to precisely characterize the intricate developmental processes of the mango tree. The appearance of botanical entities was decomposed into elementary stochastic events describing occurrence, intensity and timing of development. These events were determined by structural (position and fate of botanical entities) and temporal (appearance dates) factors. Daily growth and development of growth units and inflorescences were modelled using empirical distributions and thermal time. Fruit growth was determined using an ecophysiological model that simulated carbon- and water-related processes at the fruiting branch scale. KEY RESULTS: The model simulates the dynamics of the population of growth units, inflorescences and fruits at the tree scale during a growing cycle. Modelling the effects of structural and temporal factors makes it possible to simulate satisfactorily the complex interplays between vegetative and reproductive development. The model allowed the characterization of the susceptibility of mango tree to pests and the investigatation of the influence of tree architecture on fruit growth. CONCLUSIONS: This integrative functional-structural model simulates mango tree vegetative and reproductive development over successive growing cycles, allowing a precise characterization of tree phenology and fruit growth and production. The next step is to integrate the effects of cultivation practices, such as pruning, into the model.

A computational framework for 3D mechanical modeling of plant morphogenesis with cellular resolution.

The link between genetic regulation and the definition of form and size during morphogenesis remains largely an open question in both plant and animal biology. This is partially due to the complexity of the process, involving extensive molecular networks, multiple feedbacks between different scales of organization and physical forces operating at multiple levels. Here we present a conceptual and modeling framework aimed at generating an integrated understanding of morphogenesis in plants. This framework is based on the biophysical properties of plant cells, which are under high internal turgor pressure, and are prevented from bursting because of the presence of a rigid cell wall. To control cell growth, the underlying molecular networks must interfere locally with the elastic and/or plastic extensibility of this cell wall. We present a model in the form of a three dimensional (3D) virtual tissue, where growth depends on the local modulation of wall mechanical properties and turgor pressure. The model shows how forces generated by turgor-pressure can act both cell autonomously and non-cell autonomously to drive growth in different directions. We use simulations to explore lateral organ formation at the shoot apical meristem. Although different scenarios lead to similar shape changes, they are not equivalent and lead to different, testable predictions regarding the mechanical and geometrical properties of the growing lateral organs. Using flower development as an example, we further show how a limited number of gene activities can explain the complex shape changes that accompany organ outgrowth.

Quantitative assessment of automatic reconstructions of branching systems obtained from laser scanning.

BACKGROUND AND AIMS: Automatic acquisition of plant architecture is a major challenge for the construction of quantitative models of plant development. Recently, 3-D laser scanners have made it possible to acquire 3-D images representing a sampling of an object's surface. A number of specific methods have been proposed to reconstruct plausible branching structures from this new type of data, but critical questions remain regarding their suitability and accuracy before they can be fully exploited for use in biological applications. METHODS: In this paper, an evaluation framework to assess the accuracy of tree reconstructions is presented. The use of this framework is illustrated on a selection of laser scans of trees. Scanned data were manipulated by experienced researchers to produce reference tree reconstructions against which comparisons could be made. The evaluation framework is given two tree structures and compares both their elements and their topological organization. Similar elements are identified based on geometric criteria using an optimization algorithm. The organization of these elements is then compared and their similarity quantified. From these analyses, two indices of geometrical and structural similarities are defined, and the automatic reconstructions can thus be compared with the reference structures in order to assess their accuracy. KEY RESULTS: The evaluation framework that was developed was successful at capturing the variation in similarities between two structures as different levels of noise were introduced. The framework was used to compare three different reconstruction methods taken from the literature, and allowed sensitive parameters of each one to be determined. The framework was also generalized for the evaluation of root reconstruction from 2-D images and demonstrated its sensitivity to higher architectural complexity of structure which was not detected with a global evaluation criterion. CONCLUSIONS: The evaluation framework presented quantifies geometric and structural similarities between two structures. It can be applied to the characterization and comparison of automatic reconstructions of plant structures from laser scanner data and 2-D images. As such, it can be used as a reference test for comparing and assessing reconstruction procedures.

Light Regulation of Axillary Bud Outgrowth Along Plant Axes: An Overview of the Roles of Sugars and Hormones.

Apical dominance, the process by which the growing apical zone of the shoot inhibits bud outgrowth, involves an intricate network of several signals in the shoot. Auxin originating from plant apical region inhibits bud outgrowth indirectly. This inhibition is in particular mediated by cytokinins and strigolactones, which move from the stem to the bud and that respectively stimulate and repress bud outgrowth. The action of this hormonal network is itself modulated by sugar levels as competition for sugars, caused by the growing apical sugar sink, may deprive buds from sugars and prevents bud outgrowth partly by their signaling role. In this review, we analyze recent findings on the interaction between light, in terms of quantity and quality, and apical dominance regulation. Depending on growth conditions, light may trigger different pathways of the apical dominance regulatory network. Studies pinpoint to the key role of shoot-located cytokinin synthesis for light intensity and abscisic acid synthesis in the bud for R:FR in the regulation of bud outgrowth by light. Our analysis provides three major research lines to get a more comprehensive understanding of light effects on bud outgrowth. This would undoubtedly benefit from the use of computer modeling associated with experimental observations to deal with a regulatory system that involves several interacting signals, feedbacks, and quantitative effects.

Multi-scale high-throughput phenotyping of apple architectural and functional traits in orchard reveals genotypic variability under contrasted watering regimes.

Despite previous reports on the genotypic variation of architectural and functional traits in fruit trees, phenotyping large populations in the field remains challenging. In this study, we used high-throughput phenotyping methods on an apple tree core-collection (1000 individuals) grown under contrasted watering regimes. First, architectural phenotyping was achieved using T-LiDAR scans for estimating convex and alpha hull volumes and the silhouette to total leaf area ratio (STAR). Second, a semi-empirical index (I PL) was computed from chlorophyll fluorescence measurements, as a proxy for leaf photosynthesis. Last, thermal infrared and multispectral airborne imaging was used for computing canopy temperature variations, water deficit, and vegetation indices. All traits estimated by these methods were compared to low-throughput in planta measurements. Vegetation indices and alpha hull volumes were significantly correlated with tree leaf area and trunk cross sectional area, while I PL values showed strong correlations with photosynthesis measurements collected on an independent leaf dataset. By contrast, correlations between stomatal conductance and canopy temperature estimated from airborne images were lower, emphasizing discrepancies across measurement scales. High heritability values were obtained for almost all the traits except leaf photosynthesis, likely due to large intra-tree variation. Genotypic means were used in a clustering procedure that defined six classes of architectural and functional combinations. Differences between groups showed several combinations between architectural and functional traits, suggesting independent genetic controls. This study demonstrates the feasibility and relevance of combining multi-scale high-throughput methods and paves the way to explore the genetic bases of architectural and functional variations in woody crops in field conditions.

Integrating Physiology and Architecture in Models of Fruit Expansion.

Architectural properties of a fruit, such as its shape, vascular patterns, and skin morphology, play a significant role in determining the distributions of water, carbohydrates, and nutrients inside the fruit. Understanding the impact of these properties on fruit quality is difficult because they develop over time and are highly dependent on both genetic and environmental controls. We present a 3D functional-structural fruit model that can be used to investigate effects of the principle architectural properties on fruit quality. We use a three step modeling pipeline in the OpenAlea platform: (1) creating a 3D volumetric mesh representation of the internal and external fruit structure, (2) generating a complex network of vasculature that is embedded within this mesh, and (3) integrating aspects of the fruit's function, such as water and dry matter transport, with the fruit's structure. We restrict our approach to the phase where fruit growth is mostly due to cell expansion and the fruit has already differentiated into different tissue types. We show how fruit shape affects vascular patterns and, as a consequence, the distribution of sugar/water in tomato fruit. Furthermore, we show that strong interaction between tomato fruit shape and vessel density induces, independently of size, an important and contrasted gradient of water supply from the pedicel to the blossom end of the fruit. We also demonstrate how skin morphology related to microcracking distribution affects the distribution of water and sugars inside nectarine fruit. Our results show that such a generic model permits detailed studies of various, unexplored architectural features affecting fruit quality development.

An auxin-mediated shift toward growth isotropy promotes organ formation at the shoot meristem in Arabidopsis.

To control morphogenesis, molecular regulatory networks have to interfere with the mechanical properties of the individual cells of developing organs and tissues, but how this is achieved is not well known. We study this issue here in the shoot meristem of higher plants, a group of undifferentiated cells where complex changes in growth rates and directions lead to the continuous formation of new organs. Here, we show that the plant hormone auxin plays an important role in this process via a dual, local effect on the extracellular matrix, the cell wall, which determines cell shape. Our study reveals that auxin not only causes a limited reduction in wall stiffness but also directly interferes with wall anisotropy via the regulation of cortical microtubule dynamics. We further show that to induce growth isotropy and organ outgrowth, auxin somehow interferes with the cortical microtubule-ordering activity of a network of proteins, including AUXIN BINDING PROTEIN 1 and KATANIN 1. Numerical simulations further indicate that the induced isotropy is sufficient to amplify the effects of the relatively minor changes in wall stiffness to promote organogenesis and the establishment of new growth axes in a robust manner.

L-py: an L-system simulation framework for modeling plant architecture development based on a dynamic language.

The study of plant development requires increasingly powerful modeling tools to help understand and simulate the growth and functioning of plants. In the last decade, the formalism of L-systems has emerged as a major paradigm for modeling plant development. Previous implementations of this formalism were made based on static languages, i.e., languages that require explicit definition of variable types before using them. These languages are often efficient but involve quite a lot of syntactic overhead, thus restricting the flexibility of use for modelers. In this work, we present an adaptation of L-systems to the Python language, a popular and powerful open-license dynamic language. We show that the use of dynamic language properties makes it possible to enhance the development of plant growth models: (i) by keeping a simple syntax while allowing for high-level programming constructs, (ii) by making code execution easy and avoiding compilation overhead, (iii) by allowing a high-level of model reusability and the building of complex modular models, and (iv) by providing powerful solutions to integrate MTG data-structures (that are a common way to represent plants at several scales) into L-systems and thus enabling to use a wide spectrum of computer tools based on MTGs developed for plant architecture. We then illustrate the use of L-Py in real applications to build complex models or to teach plant modeling in the classroom.

Understanding patchy landscape dynamics: towards a landscape language.

Patchy landscapes driven by human decisions and/or natural forces are still a challenge to be understood and modelled. No attempt has been made up to now to describe them by a coherent framework and to formalize landscape changing rules. Overcoming this lacuna was our first objective here, and this was largely based on the notion of Rewriting Systems, also called Formal Grammars. We used complicated scenarios of agricultural dynamics to model landscapes and to write their corresponding driving rule equations. Our second objective was to illustrate the relevance of this landscape language concept for landscape modelling through various grassland managements, with the final aim to assess their respective impacts on biological conservation. For this purpose, we made the assumptions that a higher grassland appearance frequency and higher land cover connectivity are favourable to species conservation. Ecological results revealed that dairy and beef livestock production systems are more favourable to wild species than is hog farming, although in different ways. Methodological results allowed us to efficiently model and formalize these landscape dynamics. This study demonstrates the applicability of the Rewriting System framework to the modelling of agricultural landscapes and, hopefully, to other patchy landscapes. The newly defined grammar is able to explain changes that are neither necessarily local nor Markovian, and opens a way to analytical modelling of landscape dynamics.

OpenAlea: a visual programming and component-based software platform for plant modelling.

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.