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Background and Aims Maximizing photosynthesis at the canopy level is important for enhancing crop yield, and this requires insights into the limiting factors of photosynthesis. Using greenhouse cucumber (Cucumis sativus) as an example, this study provides a novel approach to quantify different components of photosynthetic limitations at the leaf level and to upscale these limitations to different canopy layers and the whole plant. Methods A static virtual three-dimensional canopy structure was constructed using digitized plant data in GroIMP. Light interception of the leaves was simulated by a ray-tracer and used to compute leaf photosynthesis. Different components of photosynthetic limitations, namely stomatal (SL), mesophyll (ML), biochemical (BL) and light (LL) limitations, were calculated by a quantitative limitation analysis of photosynthesis under different light regimes. Key Results In the virtual cucumber canopy, BL and LL were the most prominent factors limiting whole-plant photosynthesis. Diffusional limitations (SL + ML) contributed <15 % to total limitation. Photosynthesis in the lower canopy was more limited by the biochemical capacity, and the upper canopy was more sensitive to light than other canopy parts. Although leaves in the upper canopy received more light, their photosynthesis was more light restricted than in the leaves of the lower canopy, especially when the light condition above the canopy was poor. An increase in whole-plant photosynthesis under diffuse light did not result from an improvement of light use efficiency but from an increase in light interception. Diffuse light increased the photosynthesis of leaves that were directly shaded by other leaves in the canopy by up to 55 %. Conclusions Based on the results, maintaining biochemical capacity of the middle–lower canopy and increasing the leaf area of the upper canopy would be promising strategies to improve canopy photosynthesis in a high-wire cucumber cropping system. Further analyses using the approach described in this study can be expected to provide insights into the influences of horticultural practices on canopy photosynthesis and the design of optimal crop canopies. [ABSTRACT FROM AUTHOR]

Background and Aims The production system of cut-rose (Rosa × hybrida) involves a complex combination of plant material, management practice and environment. Plant structure is determined by bud break and shoot development while having an effect on local light climate. The aim of the present study is to cover selected aspects of the cut-rose system using functional–structural plant modelling (FSPM), in order to better understand processes contributing to produce quality and quantity. Methods The model describes the production system in three dimensions, including a virtual greenhouse environment with the crop, light sources (diffuse and direct sun light and lamps) and photosynthetically active radiation (PAR) sensors. The crop model is designed as a multiscaled FSPM with plant organs (axillary buds, leaves, internodes, flowers) as basic units, and local light interception and photosynthesis within each leaf. A Monte-Carlo light model was used to compute the local light climate for leaf photosynthesis, the latter described using a biochemical rate model. Key Results The model was able to reproduce PAR measurements taken at different canopy positions, different times of the day and different light regimes. Simulated incident and absorbed PAR as well as net assimilation rate in upright and bent shoots showed characteristic spatial and diurnal dynamics for different common cultivation scenarios. Conclusions The model of cut-rose presented allowed the creation of a range of initial structures thanks to interactive rules for pruning, cutting and bending. These static structures can be regarded as departure points for the dynamic simulation of production of flower canes. Furthermore, the model was able to predict local (per leaf) light absorption and photosynthesis. It can be used to investigate the physiology of ornamental plants, and provide support for the decisions of growers and consultants. [ABSTRACT FROM PUBLISHER]

Background and Aims Although quantitative trait loci (QTL) analysis of yield-related traits for rice has developed rapidly, crop models using genotype information have been proposed only relatively recently. As a first step towards a generic genotype–phenotype model, we present here a three-dimensional functional–structural plant model (FSPM) of rice, in which some model parameters are controlled by functions describing the effect of main-effect and epistatic QTLs. Methods The model simulates the growth and development of rice based on selected ecophysiological processes, such as photosynthesis (source process) and organ formation, growth and extension (sink processes). It was devised using GroIMP, an interactive modelling platform based on the Relational Growth Grammar formalism (RGG). RGG rules describe the course of organ initiation and extension resulting in final morphology. The link between the phenotype (as represented by the simulated rice plant) and the QTL genotype was implemented via a data interface between the rice FSPM and the QTLNetwork software, which computes predictions of QTLs from map data and measured trait data. Key Results Using plant height and grain yield, it is shown how QTL information for a given trait can be used in an FSPM, computing and visualizing the phenotypes of different lines of a mapping population. Furthermore, we demonstrate how modification of a particular trait feeds back on the entire plant phenotype via the physiological processes considered. Conclusions We linked a rice FSPM to a quantitative genetic model, thereby employing QTL information to refine model parameters and visualizing the dynamics of development of the entire phenotype as a result of ecophysiological processes, including the trait(s) for which genetic information is available. Possibilities for further extension of the model, for example for the purposes of ideotype breeding, are discussed. [ABSTRACT FROM PUBLISHER]

Abstract: In simulation models of plant development, physiological processes taking place in plants are typically described in terms of ODEs (Ordinary Differential Equations). On the one hand, those processes drive the development of the plant structure and on the other hand, the developed structure again influences these processes (e.g., photosynthesis, hormone synthesis and transport, and allocation of carbon, nitrogen, etc.). To study this dependence, simulation models, termed functional–structural plant models (FSPMs), are developed. Such models usually operate at the organ scale, considering the topology and the geometry of organs, while being validated at the scale of the plant individual. The open source modelling platform GroIMP was designed for the purpose of creating FSPMs. In GroIMP, the structure of a plant is described by the eXtended L-system language (XL) which is an extension of the Java programming language and works on a general graph structure. It is general enough to be used for many biological problems that can be described by graphs. Until now, to specify and solve ODEs, Java code had to be used and there was no general solution for doing this easily and conveniently in XL. Here we propose an extension to the XL language that allows the user to easily specify ODEs in terms of rule applications. Furthermore, their specification is separated from the numerical solution, with the possibility to choose between different integration methods. The new framework is illustrated with examples of auxin transport in Arabidopsis and gibberellic acid signal transduction in barley and compared with the conventional approach in FSPMs (Euler method). We show that besides the user-friendly specification of ODEs within rules by using a special operator, the results are computed faster, are more stable and accurate. The new framework is also compared with the mathematical formalism of differential L-systems (dL-systems). [Copyright &y& Elsevier]