Importance of the description of light interception in crop growth models.

Canopy light interception determines the amount of energy captured by a crop, and is thus critical to modeling crop growth and yield, and may substantially contribute to the prediction uncertainty of crop growth models (CGMs). We thus analyzed the canopy light interception models of the 26 wheat (Triticum aestivum) CGMs used by the Agricultural Model Intercomparison and Improvement Project (AgMIP). Twenty-one CGMs assume that the light extinction coefficient (K) is constant, varying from 0.37 to 0.80 depending on the model. The other models take into account the illumination conditions and assume either that all green surfaces in the canopy have the same inclination angle (θ) or that θ distribution follows a spherical distribution. These assumptions have not yet been evaluated due to a lack of experimental data. Therefore, we conducted a field experiment with five cultivars with contrasting leaf stature sown at normal and double row spacing, and analyzed θ distribution in the canopies from three-dimensional canopy reconstructions. In all the canopies, θ distribution was well represented by an ellipsoidal distribution. We thus carried out an intercomparison between the light interception models of the AgMIP-Wheat CGMs ensemble and a physically based K model with ellipsoidal leaf angle distribution and canopy clumping (KellC). Results showed that the KellC model outperformed current approaches under most illumination conditions and that the uncertainty in simulated wheat growth and final grain yield due to light models could be as high as 45%. Therefore, our results call for an overhaul of light interception models in CGMs.

Two maize cultivars of contrasting leaf size show different leaf elongation rates with identical patterns of extension dynamics and coordination.

Simulating leaf development from initiation to maturity opens new possibilities to model plant-environment interactions and the plasticity of plant architecture. This study analyses the dynamics of leaf production and extension along a maize (Zea mays) shoot to assess important modelling choices. Maize plants from two cultivars originating from the same inbred line, yet differing in the length of mature leaves were used in this study. We characterized the dynamics of the blade and sheath lengths of all phytomers by dissecting plants every 2-3 days. We analysed how differences in leaf size were built up and we examined the coordination between the emergence of organs and phases of their extension. Leaf extension rates were higher in the cultivar with longer leaves than in the cultivar with shorter leaves; no differences were found in other aspects. We found that (i) first post-embryonic leaves were initiated at a markedly higher rate than upper leaves; (ii) below ear position, sheaths were initiated at a time intermediate between tip emergence and appearance, while above the ear position, sheaths were initiated at a high rate, such that the time interval between the blade and sheath initiations decreased for these leaves; and (iii) ear position also marked a change in the correlation in size between successive phytomers with little correlation of size between upper and lower leaves. Our results identified leaf extension rate as the reason for the difference in size between the two cultivars. The two cultivars shared the same pattern for the timing of initiation events, which was more complex than previously thought. The differences described here may explain some inaccuracies reported in functional-structural plant models. We speculate that genotypic variation in behaviour for leaf and sheath initiation exists, which has been little documented in former studies.

Plant functional trait variability and trait syndromes among wheat varieties: the footprint of artificial selection.

Although widely used in ecology, trait-based approaches are seldom used to study agroecosystems. In particular, there is a need to evaluate how functional trait variability among varieties of a crop species compares to the variability among wild plant species and how variety selection can modify trait syndromes. Here, we quantified 18 above- and below-ground functional traits for 57 varieties of common wheat representative of different modern selection histories. We compared trait variability among varieties and among Pooideae species, and analyzed the effect of selection histories on trait values and trait syndromes. For traits under strong selection, trait variability among varieties was less than 10% of the variability observed among Pooideae species. However, for traits not directly selected, such as root N uptake capacity, the variability was up to 75% of the variability among Pooideae species. Ammonium absorption capacity by roots was counter-selected for conventional varieties compared with organic varieties and landraces. Artificial selection also altered some trait syndromes classically reported for Pooideae. Identifying traits that have high or low variability among varieties and characterizing the hidden effects of selection on trait values and syndromes will benefit the selection of varieties to be used especially for lower N input agroecosystems.

A functional structural model of grass development based on metabolic regulation and coordination rules.

Shoot architecture is a key component of the interactions between plants and their environment. We present a novel model of grass, which fully integrates shoot morphogenesis and the metabolism of carbon (C) and nitrogen (N) at organ scale, within a three-dimensional representation of plant architecture. Plant morphogenesis is seen as a self-regulated system driven by two main mechanisms. First, the rate of organ extension and the establishment of architectural traits are regulated by concentrations of C and N metabolites in the growth zones and the temperature. Second, the timing of extension is regulated by rules coordinating successive phytomers instead of a thermal time schedule. Local concentrations are calculated from a model of C and N metabolism at organ scale. The three-dimensional representation allows the accurate calculation of light and temperature distribution within the architecture. The model was calibrated for wheat (Triticum aestivum) and evaluated for early vegetative stages. This approach allowed the simulation of realistic patterns of leaf dimensions, extension dynamics, and organ mass and composition. The model simulated, as emergent properties, plant and agronomic traits. Metabolic activities of growing leaves were investigated in relation to whole-plant functioning and environmental conditions. The current model is an important step towards a better understanding of the plasticity of plant phenotype in different environments.

Architectural Response of Wheat Cultivars to Row Spacing Reveals Altered Perception of Plant Density.

Achieving novel improvements in crop management may require changing interrow distance in cultivated fields. Such changes would benefit from a better understanding of plant responses to the spatial heterogeneity in their environment. Our work investigates the architectural plasticity of wheat plants in response to increasing row spacing and evaluates the hypothesis of a foraging behavior in response to neighboring plants. A field experiment was conducted with five commercial winter wheat cultivars possessing unique architectures, grown under narrow (NI, 17.5 cm) or wide interrows (WI, 35 cm) at the same population density (170 seeds/m2). We characterized the development (leaf emergence, tillering), the morphology (dimension of organs, leaf area index), and the geometry (ground cover, leaf angle, organ spreading, and orientation). All cultivars showed a lower number of emerged tillers in WI compared to NI, which was later partly compensated by lower tiller mortality. Besides, the upper leaf blades were larger in WI. Finally the leaf area index at flowering showed little difference between WI and NI treatments. The rate of leaf emergence and the final leaf number were higher in WI compared to NI, except for one cultivar. Around the start of stem elongation, pseudo-stems were more erect in WI, while around the time of flowering, stems were more inclined and leaves were more planophile. Cultivars differed in their degrees of responses, with one appearing to prospect more specifically within the interrow space in WI treatment. Altogether, our results suggest that altering interrow distance leads to changes in the perceived extent of competition by plants, with responses first mimicking the effect of a higher plant density and later the effect of a lower plant density. Only one cultivar showed responses that suggested a perception of the heterogeneity of the environment. These findings improve our understanding of plant responses to spatial heterogeneity and provide novel information to simulate light capture in plant 3D models, depending on cultivar behavior.

Estimation of Plant and Canopy Architectural Traits Using the Digital Plant Phenotyping Platform.

The extraction of desirable heritable traits for crop improvement from high-throughput phenotyping (HTP) observations remains challenging. We developed a modeling workflow named "Digital Plant Phenotyping Platform" (D3P), to access crop architectural traits from HTP observations. D3P couples the Architectural model of DEvelopment based on L-systems (ADEL) wheat (Triticum aestivum) model (ADEL-Wheat), which describes the time course of the three-dimensional architecture of wheat crops, with simulators of images acquired with HTP sensors. We demonstrated that a sequential assimilation of the green fraction derived from Red-Green-Blue images of the crop into D3P provides accurate estimates of five key parameters (phyllochron, lamina length of the first leaf, rate of elongation of leaf lamina, number of green leaves at the start of leaf senescence, and minimum number of green leaves) of the ADEL-Wheat model that drive the time course of green area index and the number of axes with more than three leaves at the end of the tillering period. However, leaf and tiller orientation and inclination characteristics were poorly estimated. D3P was also used to optimize the observational configuration. The results, obtained from in silico experiments conducted on wheat crops at several vegetative stages, showed that the accessible traits could be estimated accurately with observations made at 0° and 60° zenith view inclination with a temporal frequency of 100 °Cd (degree day). This illustrates the potential of the proposed holistic approach that integrates all the available information into a consistent system for interpretation. The potential benefits and limitations of the approach are further discussed.

WALTer: a three-dimensional wheat model to study competition for light through the prediction of tillering dynamics.

BACKGROUND AND AIMS: Branching is a main morphogenetic process involved in the adaptation of plants to the environment. In grasses, tillering is divided into three phases: tiller emergence, cessation of tillering and tiller regression. Understanding and prediction of the tillering process is a major challenge to better control cereal yields. In this paper, we present and evaluate WALTer, an individual-based model of wheat built on simple self-adaptive rules for predicting the tillering dynamics at contrasting sowing densities. METHODS: WALTer simulates the three-dimensional (3-D) development of the aerial architecture of winter wheat. Tillering was modelled using two main hypotheses: (H1) a plant ceases to initiate new tillers when a critical Green Area Index (GAIc) is reached, and (H2) the regression of a tiller occurs if its interception of light is below a threshold (PARt). The development of vegetative organs follows descriptive rules adapted from the literature. A sensitivity analysis was performed to evaluate the impact of each parameter on tillering and GAI dynamics. WALTer was parameterized and evaluated using an initial dataset providing an extensive description of GAI dynamics, and another dataset describing tillering dynamics under a wide range of sowing densities. KEY RESULTS: Sensitivity analysis indicated the predominant importance of GAIc and PARt. Tillering and GAI dynamics of expt 1 were well fit by WALTer. Once calibrated based on the agronomic density of expt 2, tillering parameters allowed an adequate prediction of tillering dynamics at contrasting sowing densities. CONCLUSIONS: Using simple rules and a small number of parameters, WALTer efficiently simulated the wheat tillering dynamics observed at contrasting densities in experimental data. These results show that the definition of a critical GAI and a threshold of PAR is a relevant way to represent, respectively, cessation of tillering and tiller regression under competition for light.

Investigation of complex canopies with a functional-structural plant model as exemplified by leaf inclination effect on the functioning of pure and mixed stands of wheat during grain filling.

BACKGROUND AND AIMS: Because functional-structural plant models (FSPMs) take plant architecture explicitly into consideration, they constitute a promising approach for unravelling plant-plant interactions in complex canopies. However, existing FSPMs mainly address competition for light. The aim of the present work was to develop a comprehensive FSPM accounting for the interactions between plant architecture, environmental factors and the metabolism of carbon (C) and nitrogen (N). METHODS: We developed an original FSPM by coupling models of (1) 3-D wheat architecture, (2) light distribution within canopies and (3) C and N metabolism. Model behaviour was evaluated by simulating the functioning of theoretical canopies consisting of wheat plants of contrasting leaf inclination, arranged in pure and mixed stands and considering four culm densities and three sky conditions. KEY RESULTS: As an emergent property of the detailed description of metabolism, the model predicted a linear relationship between absorbed light and C assimilation, and a curvilinear relationship between grain mass and C assimilation, applying to both pure stands and each component of mixtures. Over the whole post-anthesis period, planophile plants tended to absorb more light than erectophile plants, resulting in a slightly higher grain mass. This difference was enhanced at low plant density and in mixtures, where the erectophile behaviour resulted in a loss of competitiveness. CONCLUSION: The present work demonstrates that FSPMs provide a framework allowing the analysis of complex canopies such as studying the impact of particular plant traits, which would hardly be feasible experimentally. The present FSPM can help in interpreting complex interactions by providing access to critical variables such as resource acquisition and allocation, internal metabolic concentrations, leaf life span and grain filling. Simulations were based on canopies identically initialized at flowering; extending the model to the whole cycle is thus required so that all consequences of a trait can be evaluated.

Estimation of Wheat Plant Density at Early Stages Using High Resolution Imagery.

Crop density is a key agronomical trait used to manage wheat crops and estimate yield. Visual counting of plants in the field is currently the most common method used. However, it is tedious and time consuming. The main objective of this work is to develop a machine vision based method to automate the density survey of wheat at early stages. RGB images taken with a high resolution RGB camera are classified to identify the green pixels corresponding to the plants. Crop rows are extracted and the connected components (objects) are identified. A neural network is then trained to estimate the number of plants in the objects using the object features. The method was evaluated over three experiments showing contrasted conditions with sowing densities ranging from 100 to 600 seeds⋅m-2. Results demonstrate that the density is accurately estimated with an average relative error of 12%. The pipeline developed here provides an efficient and accurate estimate of wheat plant density at early stages.

A method to estimate plant density and plant spacing heterogeneity: application to wheat crops.

BACKGROUND: Plant density and its non-uniformity drive the competition among plants as well as with weeds. They need thus to be estimated with small uncertainties accuracy. An optimal sampling method is proposed to estimate the plant density in wheat crops from plant counting and reach a given precision. RESULTS: Three experiments were conducted in 2014 resulting in 14 plots across varied sowing density, cultivars and environmental conditions. The coordinates of the plants along the row were measured over RGB high resolution images taken from the ground level. Results show that the spacing between consecutive plants along the row direction are independent and follow a gamma distribution under the varied conditions experienced. A gamma count model was then derived to define the optimal sample size required to estimate plant density for a given precision. Results suggest that measuring the length of segments containing 90 plants will achieve a precision better than 10%, independently from the plant density. This approach appears more efficient than the usual method based on fixed length segments where the number of plants are counted: the optimal length for a given precision on the density estimation will depend on the actual plant density. The gamma count model parameters may also be used to quantify the heterogeneity of plant spacing along the row by exploiting the variability between replicated samples. Results show that to achieve a 10% precision on the estimates of the 2 parameters of the gamma model, 200 elementary samples corresponding to the spacing between 2 consecutive plants should be measured. CONCLUSIONS: This method provides an optimal sampling strategy to estimate the plant density and quantify the plant spacing heterogeneity along the row.

CN-Wheat, a functional-structural model of carbon and nitrogen metabolism in wheat culms after anthesis. I. Model description.

Background and Aims Improving crops requires better linking of traits and metabolic processes to whole plant performance. In this paper, we present CN-Wheat, a comprehensive and mechanistic model of carbon (C) and nitrogen (N) metabolism within wheat culms after anthesis. Methods The culm is described by modules that represent the roots, photosynthetic organs and grains. Each of them includes structural, storage and mobile materials. Fluxes of C and N among modules occur through a common pool and through transpiration flow. Metabolite variations are represented by differential equations that depend on the physiological processes occurring in each module. A challenging aspect of CN-Wheat lies in the regulation of these processes by metabolite concentrations and the environment perceived by organs. Key Results CN-Wheat simulates the distribution of C and N into wheat culms in relation to photosynthesis, N uptake, metabolite turnover, root exudation and tissue death. Regulation of physiological activities by local concentrations of metabolites appears to be a valuable feature for understanding how the behaviour of the whole plant can emerge from local rules. Conclusions The originality of CN-Wheat is that it proposes an integrated view of plant functioning based on a mechanistic approach. The formalization of each process can be further refined in the future as knowledge progresses. This approach is expected to strengthen our capacity to understand plant responses to their environment and investigate plant traits adapted to changes in agronomical practices or environmental conditions. A companion paper will evaluate the model.

CN-Wheat, a functional-structural model of carbon and nitrogen metabolism in wheat culms after anthesis. II. Model evaluation.

Background and Aims Simulating resource allocation in crops requires an integrated view of plant functioning and the formalization of interactions between carbon (C) and nitrogen (N) metabolisms. This study evaluates the functional-structural model CN-Wheat developed for winter wheat after anthesis. Methods In CN-Wheat the acquisition and allocation of resources between photosynthetic organs, roots and grains are emergent properties of sink and source activities and transfers of mobile metabolites. CN-Wheat was calibrated for field plants under three N fertilizations at anthesis. Model parameters were taken from the literature or calibrated on the experimental data. Key Results The model was able to predict the temporal variations and the distribution of resources in the culm. Thus, CN-Wheat accurately predicted the post-anthesis kinetics of dry masses and N content of photosynthetic organs and grains in response to N fertilization. In our simulations, when soil nitrates were non-limiting, N in grains was ultimately determined by availability of C for root activity. Dry matter accumulation in grains was mostly affected by photosynthetic organ lifespan, which was regulated by protein turnover and C-regulated root activity. Conclusions The present study illustrates that the hypotheses implemented in the model were able to predict realistic dynamics and spatial patterns of C and N. CN-Wheat provided insights into the interplay of C and N metabolism and how the depletion of mobile metabolites due to grain filling ultimately results in the cessation of resource capture. This enabled us to identify processes that limit grain mass and protein content and are potential targets for plant breeding.

A modelling framework to simulate foliar fungal epidemics using functional-structural plant models.

BACKGROUND AND AIMS: Sustainable agriculture requires the identification of new, environmentally responsible strategies of crop protection. Modelling of pathosystems can allow a better understanding of the major interactions inside these dynamic systems and may lead to innovative protection strategies. In particular, functional-structural plant models (FSPMs) have been identified as a means to optimize the use of architecture-related traits. A current limitation lies in the inherent complexity of this type of modelling, and thus the purpose of this paper is to provide a framework to both extend and simplify the modelling of pathosystems using FSPMs. METHODS: Different entities and interactions occurring in pathosystems were formalized in a conceptual model. A framework based on these concepts was then implemented within the open-source OpenAlea modelling platform, using the platform's general strategy of modelling plant-environment interactions and extending it to handle plant interactions with pathogens. New developments include a generic data structure for representing lesions and dispersal units, and a series of generic protocols to communicate with objects representing the canopy and its microenvironment in the OpenAlea platform. Another development is the addition of a library of elementary models involved in pathosystem modelling. Several plant and physical models are already available in OpenAlea and can be combined in models of pathosystems using this framework approach. KEY RESULTS: Two contrasting pathosystems are implemented using the framework and illustrate its generic utility. Simulations demonstrate the framework's ability to simulate multiscaled interactions within pathosystems, and also show that models are modular components within the framework and can be extended. This is illustrated by testing the impact of canopy architectural traits on fungal dispersal. CONCLUSIONS: This study provides a framework for modelling a large number of pathosystems using FSPMs. This structure can accommodate both previously developed models for individual aspects of pathosystems and new ones. Complex models are deconstructed into separate 'knowledge sources' originating from different specialist areas of expertise and these can be shared and reassembled into multidisciplinary models. The framework thus provides a beneficial tool for a potential diverse and dynamic research community.

Towards modelling the flexible timing of shoot development: simulation of maize organogenesis based on coordination within and between phytomers.

BACKGROUND AND AIMS: Experimental evidence challenges the approximation, central in crop models, that developmental events follow a fixed thermal time schedule, and indicates that leaf emergence events play a role in the timing of development. The objective of this study was to build a structural development model of maize (Zea mays) based on a set of coordination rules at organ level that regulate duration of elongation, and to show how the distribution of leaf sizes emerges from this. METHODS: A model of maize development was constructed based on three coordination rules between leaf emergence events and the dynamics of organ extension. The model was parameterized with data from maize grown at a low plant population density and tested using data from maize grown at high population density. KEY RESULTS: The model gave a good account of the timing and duration of organ extension. By using initial conditions associated with high population density, the model reproduced well the increase in blade elongation duration and the delay in sheath extension in high-density populations compared with low-density populations. Predictions of the sizes of sheaths at high density were accurate, whereas predictions of the dynamics of blade length were accurate up to rank 9; moderate overestimation of blade length occurred at higher ranks. CONCLUSIONS: A set of simple rules for coordinated growth of organs is sufficient to simulate the development of maize plant structure without taking into account any regulation by assimilates. In this model, whole-plant architecture is shaped through initial conditions that feed a cascade of coordination events.

Multiple pathways regulate shoot branching.

Shoot branching patterns result from the spatio-temporal regulation of axillary bud outgrowth. Numerous endogenous, developmental and environmental factors are integrated at the bud and plant levels to determine numbers of growing shoots. Multiple pathways that converge to common integrators are most probably involved. We propose several pathways involving not only the classical hormones auxin, cytokinins and strigolactones, but also other signals with a strong influence on shoot branching such as gibberellins, sugars or molecular actors of plant phase transition. We also deal with recent findings about the molecular mechanisms and the pathway involved in the response to shade as an example of an environmental signal controlling branching. We propose the TEOSINTE BRANCHED1, CYCLOIDEA, PCF transcription factor TB1/BRC1 and the polar auxin transport stream in the stem as possible integrators of these pathways. We finally discuss how modeling can help to represent this highly dynamic system by articulating knowledges and hypothesis and calculating the phenotype properties they imply.

Rose bush leaf and internode expansion dynamics: analysis and development of a model capturing interplant variability.

Rose bush architecture, among other factors, such as plant health, determines plant visual quality. The commercial product is the individual plant and interplant variability may be high within a crop. Thus, both mean plant architecture and interplant variability should be studied. Expansion is an important feature of architecture, but it has been little studied at the level of individual organs in rose bushes. We investigated the expansion kinetics of primary shoot organs, to develop a model reproducing the organ expansion of real crops from non-destructive input variables. We took interplant variability in expansion kinetics and the model's ability to simulate this variability into account. Changes in leaflet and internode dimensions over thermal time were recorded for primary shoot expansion, on 83 plants from three crops grown in different climatic conditions and densities. An empirical model was developed, to reproduce organ expansion kinetics for individual plants of a real crop of rose bush primary shoots. Leaflet or internode length was simulated as a logistic function of thermal time. The model was evaluated by cross-validation. We found that differences in leaflet or internode expansion kinetics between phytomer positions and between plants at a given phytomer position were due mostly to large differences in time of organ expansion and expansion rate, rather than differences in expansion duration. Thus, in the model, the parameters linked to expansion duration were predicted by values common to all plants, whereas variability in final size and organ expansion time was captured by input data. The model accurately simulated leaflet and internode expansion for individual plants (RMSEP = 7.3 and 10.2% of final length, respectively). Thus, this study defines the measurements required to simulate expansion and provides the first model simulating organ expansion in rosebush to capture interplant variability.

Modelling the effect of wheat canopy architecture as affected by sowing density on Septoria tritici epidemics using a coupled epidemic-virtual plant model.

BACKGROUND AND AIMS: The relationship between Septoria tritici, a splash-dispersed disease, and its host is complex because of the interactions between the dynamic plant architecture and the vertical progress of the disease. The aim of this study was to test the capacity of a coupled virtual wheat-Septoria tritici epidemic model (Septo3D) to simulate disease progress on the different leaf layers for contrasted sowing density treatments. METHODS: A field experiment was performed with winter wheat 'Soissons' grown at three contrasted densities. Plant architecture was characterized to parameterize the wheat model, and disease dynamic was monitored to compare with simulations. Three simulation scenarios, differing in the degree of detail with which plant variability of development was represented, were defined. KEY RESULTS: Despite architectural differences between density treatments, few differences were found in disease progress; only the lower-density treatment resulted in a slightly higher rate of lesion development. Model predictions were consistent with field measurements but did not reproduce the higher rate of lesion progress in the low density. The canopy reconstruction scenario in which inter-plant variability was taken into account yielded the best agreement between measured and simulated epidemics. Simulations performed with the canopy represented by a population of the same average plant deviated strongly from the observations. CONCLUSIONS: It was possible to compare the predicted and measured epidemics on detailed variables, supporting the hypothesis that the approach is able to provide new insights into the processes and plant traits that contribute to the epidemics. On the other hand, the complex and dynamic responses to sowing density made it difficult to test the model precisely and to disentangle the various aspects involved. This could be overcome by comparing more contrasted and/or simpler canopy architectures such as those resulting from quasi-isogenic lines differing by single architectural traits.

NEMA, a functional-structural model of nitrogen economy within wheat culms after flowering. II. Evaluation and sensitivity analysis.

BACKGROUND AND AIMS: Simulating nitrogen economy in crop plants requires formalizing the interactions between soil nitrogen availability, root nitrogen acquisition, distribution between vegetative organs and remobilization towards grains. This study evaluates and analyses the functional-structural and mechanistic model of nitrogen economy, NEMA (Nitrogen Economy Model within plant Architecture), developed for winter wheat (Triticum aestivum) after flowering. METHODS: NEMA was calibrated for field plants under three nitrogen fertilization treatments at flowering. Model behaviour was investigated and sensitivity to parameter values was analysed. KEY RESULTS: Nitrogen content of all photosynthetic organs and in particular nitrogen vertical distribution along the stem and remobilization patterns in response to fertilization were simulated accurately by the model, from Rubisco turnover modulated by light intercepted by the organ and a mobile nitrogen pool. This pool proved to be a reliable indicator of plant nitrogen status, allowing efficient regulation of nitrogen acquisition by roots, remobilization from vegetative organs and accumulation in grains in response to nitrogen treatments. In our simulations, root capacity to import carbon, rather than carbon availability, limited nitrogen acquisition and ultimately nitrogen accumulation in grains, while Rubisco turnover intensity mostly affected dry matter accumulation in grains. CONCLUSIONS: NEMA enabled interpretation of several key patterns usually observed in field conditions and the identification of plausible processes limiting for grain yield, protein content and root nitrogen acquisition that could be targets for plant breeding; however, further understanding requires more mechanistic formalization of carbon metabolism. Its strong physiological basis and its realistic behaviour support its use to gain insights into nitrogen economy after flowering.

NEMA, a functional-structural model of nitrogen economy within wheat culms after flowering. I. Model description.

BACKGROUND AND AIMS: Models simulating nitrogen use by plants are potentially efficient tools to optimize the use of fertilizers in agriculture. Most crop models assume that a target nitrogen concentration can be defined for plant tissues and formalize a demand for nitrogen, depending on the difference between the target and actual nitrogen concentrations. However, the teleonomic nature of the approach has been criticized. This paper proposes a mechanistic model of nitrogen economy, NEMA (Nitrogen Economy Model within plant Architecture), which links nitrogen fluxes to nitrogen concentration and physiological processes. METHODS: A functional-structural approach is used: plant aerial parts are described in a botanically realistic way and physiological processes are expressed at the scale of each aerial organ or root compartment as a function of local conditions (light and resources). KEY RESULTS: NEMA was developed for winter wheat (Triticum aestivum) after flowering. The model simulates the nitrogen (N) content of each photosynthetic organ as regulated by Rubisco turnover, which depends on intercepted light and a mobile N pool shared by all organs. This pool is enriched by N acquisition from the soil and N release from vegetative organs, and is depleted by grain uptake and protein synthesis in vegetative organs; NEMA accounts for the negative feedback from circulating N on N acquisition from the soil, which is supposed to follow the activities of nitrate transport systems. Organ N content and intercepted light determine dry matter production via photosynthesis, which is distributed between organs according to a demand-driven approach. CONCLUSIONS: NEMA integrates the main feedbacks known to regulate plant N economy. Other novel features are the simulation of N for all photosynthetic tissues and the use of an explicit description of the plant that allows how the local environment of tissues regulates their N content to be taken into account. We believe this represents an appropriate frame for modelling nitrogen in functional-structural plant models. A companion paper will present model evaluation and analysis.

A comparative analysis of leaf shape of wheat, barley and maize using an empirical shape model.

BACKGROUND AND AIMS: The phenotypes of grasses show differences depending on growth conditions and ontogenetic stage. Understanding these responses and finding suitable mathematical formalizations are an essential part of the development of plant and crop models. Usually, a marked change in architecture between juvenile and adult plants is observed, where dimension and shape of leaves are likely to change. In this paper, the plasticity of leaf shape is analysed according to growth conditions and ontogeny. METHODS: Leaf shape of Triticum aestivum, Hordeum vulgare and Zea mays cultivars grown under varying conditions was measured using digital image processing. An empirical leaf shape model was fitted to measured shape data of single leaves. Obtained values of model parameters were used to analyse the patterns in leaf shape. KEY RESULTS: The model was able to delineate leaf shape of all studied species. The model error was small. Differences in leaf shape between juvenile and adult leaves in T. aestivum and H. vulgare were observed. Varying growth conditions impacted leaf dimensions but did not impact leaf shape of the respective species. CONCLUSIONS: Leaf shape of the studied T. aestivum and H. vulgare cultivars was remarkably stable for a comparable ontogenetic stage (leaf rank), but differed between stages. Along with other aspects of grass architecture, leaf shape changed during the transition from juvenile to adult growth phase. Model-based analysis of leaf shape is a method to investigate these differences. Presented results can be integrated into architectural models of plant development to delineate leaf shape for different species, cultivars and environmental conditions.