An approach to multiscale modelling with graph grammars

Background and Aims

Functional–structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs.

Methods

A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL.

Key Results

Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas.

Conclusions

The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models.     

Dry matter partitioning models for the simulation of individual fruit growth in greenhouse cucumber canopies

Background and Aims

Growth imbalances between individual fruits are common in indeterminate plants such as cucumber (Cucumis sativus). In this species, these imbalances can be related to differences in two growth characteristics, fruit growth duration until reaching a given size and fruit abortion. Both are related to distribution, and environmental factors as well as canopy architecture play a key role in their differentiation. Furthermore, events leading to a fruit reaching its harvestable size before or simultaneously with a prior fruit can be observed. Functional–structural plant models (FSPMs) allow for interactions between environmental factors, canopy architecture and physiological processes. Here, we tested hypotheses which account for these interactions by introducing dominance and abortion thresholds for the partitioning of assimilates between growing fruits.

Methods

Using the L-System formalism, an FSPM was developed which combined a model for architectural development, a biochemical model of photosynthesis and a model for assimilate partitioning, the last including a fruit growth model based on a size-related potential growth rate (R_P). Starting from a distribution proportional to R_P, the model was extended by including abortion and dominance. Abortion was related to source strength and dominance to sink strength. Both thresholds were varied to test their influence on fruit growth characteristics. Simulations were conducted for a dense row and a sparse isometric canopy.

Key Results

The simple partitioning models failed to simulate individual fruit growth realistically. The introduction of abortion and dominance thresholds gave the best results. Simulations of fruit growth durations and abortion rates were in line with measurements, and events in which a fruit was harvestable earlier than an older fruit were reproduced.

Conclusions

Dominance and abortion events need to be considered when simulating typical fruit growth traits. By integrating environmental factors, the FSPM can be a valuable tool to analyse and improve existing knowledge about the dynamics of assimilates partitioning.     

Towards aspect-oriented functional--structural plant modelling

Background and Aims

Functional–structural plant models (FSPMs) are used to integrate knowledge and test hypotheses of plant behaviour, and to aid in the development of decision support systems. A significant amount of effort is being put into providing a sound methodology for building them. Standard techniques, such as procedural or object-oriented programming, are not suited for clearly separating aspects of plant function that criss-cross between different components of plant structure, which makes it difficult to reuse and share their implementations. The aim of this paper is to present an aspect-oriented programming approach that helps to overcome this difficulty.

Methods

The L-system-based plant modelling language L+C was used to develop an aspect-oriented approach to plant modelling based on multi-modules. Each element of the plant structure was represented by a sequence of L-system modules (rather than a single module), with each module representing an aspect of the element''s function. Separate sets of productions were used for modelling each aspect, with context-sensitive rules facilitated by local lists of modules to consider/ignore. Aspect weaving or communication between aspects was made possible through the use of pseudo-L-systems, where the strict-predecessor of a production rule was specified as a multi-module.

Key Results

The new approach was used to integrate previously modelled aspects of carbon dynamics, apical dominance and biomechanics with a model of a developing kiwifruit shoot. These aspects were specified independently and their implementation was based on source code provided by the original authors without major changes.

Conclusions

This new aspect-oriented approach to plant modelling is well suited for studying complex phenomena in plant science, because it can be used to integrate separate models of individual aspects of plant development and function, both previously constructed and new, into clearly organized, comprehensive FSPMs. In a future work, this approach could be further extended into an aspect-oriented programming language for FSPMs.     

Towards a functional-structural plant model of cut-rose: simulation of light environment, light absorption, photosynthesis and interference with the plant structure

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.     

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.     

Mathematical model of fructan biosynthesis and polymer length distribution in plants

Background and Aims

There are many unresolved issues concerning the biochemistry of fructan biosynthesis. The aim of this paper is to address some of these by means of modelling mathematically the biochemical processes.

Methods

A model has been constructed for the step-by-step synthesis of fructan polymers. This is run until a steady state is achieved for which a polymer distribution is predicted. It is shown how qualitatively different distributions can be obtained.

Key Results

It is demonstrated how a set of experimental results on polymer distribution can by simulated by a simple parameter adjustments.

Conclusions

Mathematical modelling of fructan biosynthesis can provide a useful tool for helping elucidate the details of the biosynthetic processes.     

Divergent selection in trailing- versus leading-edge populations of Biscutella laevigata

Background and Aims

Knowledge on how climate-induced range shifts might affect natural selection is crucial to understand the evolution of species ranges.

Methods

Using historical demographic perspectives gathered from regional-scale phylogeography on the alpine herb Biscutella laevigata, indirect inferences on gene flow and signature of selection based on AFLP genotyping were compared between local populations persisting at the trailing edge and expanding at the leading edge.

Key Results

Spatial autocorrelation revealed that gene flow was two times more restricted at the trailing edge and genome scans indicated divergent selection in this persisting population. In contrast, no pattern of selection emerged in the expanding population at the leading edge.

Conclusions

Historical effects may determine different architecture of genetic variation and selective patterns within local populations, what is arguably important to understand evolutionary processes acting across the species ranges.     

A functional-structural model of rice linking quantitative genetic information with morphological development and physiological processes

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.Key words: Functional–structural plant model, ecophysiology, QTL analysis, plant modelling, quantitative genetics     

A probabilistic model of biological ageing of the lungs for analysing the effects of smoking,asthma and COPD

Background

Although a large body of literature is available that describes the effects of smoking, asthma and COPD on lung function, most studies are restricted to a small age range and to one factor. As a consequence, available results are incomplete and often difficult to compare, also due to the ways the effects are expressed. Furthermore, current approaches consider one type of measurement only or several types separately.

Methods

We propose a probabilistic model that expresses the effects as number of years added to chronological age or, in other words, that estimates the biological age of the lungs. Using biological age as a measure of the effects has the advantage of facilitating the understanding of their severity and comparison of results. In our model, chronological age and other factors affecting the health status of the lungs generate biological age, which in turn generates lung function measurements. This structure enables the use of multiple types of measurement to obtain a more precise estimate of the effects and parameter sharing for characterization over large age ranges and of co-occurrence of factors with little data. We treat the parameters that model smoking habits and lung diseases as random variables to obtain uncertainty in the estimated effects.

Results

We use the model to investigate the effects of smoking, asthma and COPD on the TwinsUK Registry. Our results suggest that the combination of smoking with lung disease(s) has higher effect than smoking or lung disease(s) alone, and that in smokers, co-occurrence of asthma and COPD is more detrimental than asthma or COPD alone.

Conclusions

The proposed model or other models based on a similar approach could be of help in improving the understanding of factors affecting lung function by enabling characterizations over large age ranges and of co-occurrence of factors with little data and the use of multiple types of measurement. The software implementing the model can be downloaded at the first author’s webpage.     

How plant architecture affects light absorption and photosynthesis in tomato: towards an ideotype for plant architecture using a functional-structural plant model

Background and Aims

Manipulation of plant structure can strongly affect light distribution in the canopy and photosynthesis. The aim of this paper is to find a plant ideotype for optimization of light absorption and canopy photosynthesis. Using a static functional structural plant model (FSPM), a range of different plant architectural characteristics was tested for two different seasons in order to find the optimal architecture with respect to light absorption and photosynthesis.

Methods

Simulations were performed with an FSPM of a greenhouse-grown tomato crop. Sensitivity analyses were carried out for leaf elevation angle, leaf phyllotaxis, leaflet angle, leaf shape, leaflet arrangement and internode length. From the results of this analysis two possible ideotypes were proposed. Four different vertical light distributions were also tested, while light absorption cumulated over the whole canopy was kept the same.

Key Results

Photosynthesis was augmented by 6 % in winter and reduced by 7 % in summer, when light absorption in the top part of the canopy was increased by 25 %, while not changing light absorption of the canopy as a whole. The measured plant structure was already optimal with respect to leaf elevation angle, leaflet angle and leaflet arrangement for both light absorption and photosynthesis while phyllotaxis had no effect. Increasing the length : width ratio of leaves by 1·5 or increasing internode length from 7 cm to 12 cm led to an increase of 6–10 % for light absorption and photosynthesis.

Conclusions

At high light intensities (summer) deeper penetration of light in the canopy improves crop photosynthesis, but not at low light intensities (winter). In particular, internode length and leaf shape affect the vertical distribution of light in the canopy. A new plant ideotype with more spacious canopy architecture due to long internodes and long and narrow leaves led to an increase in crop photosynthesis of up to 10 %.     

Modelling the structural response of cotton plants to mepiquat chloride and population density

Background and Aims

Cotton (Gossypium hirsutum) has indeterminate growth. The growth regulator mepiquat chloride (MC) is used worldwide to restrict vegetative growth and promote boll formation and yield. The effects of MC are modulated by complex interactions with growing conditions (nutrients, weather) and plant population density, and as a result the effects on plant form are not fully understood and are difficult to predict. The use of MC is thus hard to optimize.

Methods

To explore crop responses to plant density and MC, a functional–structural plant model (FSPM) for cotton (named CottonXL) was designed. The model was calibrated using 1 year''s field data, and validated by using two additional years of detailed experimental data on the effects of MC and plant density in stands of pure cotton and in intercrops of cotton with wheat. CottonXL simulates development of leaf and fruits (square, flower and boll), plant height and branching. Crop development is driven by thermal time, population density, MC application, and topping of the main stem and branches.

Key Results

Validation of the model showed good correspondence between simulated and observed values for leaf area index with an overall root-mean-square error of 0·50 m² m⁻², and with an overall prediction error of less than 10 % for number of bolls, plant height, number of fruit branches and number of phytomers. Canopy structure became more compact with the decrease of leaf area index and internode length due to the application of MC. Moreover, MC did not have a substantial effect on boll density but increased lint yield at higher densities.

Conclusions

The model satisfactorily represents the effects of agronomic measures on cotton plant structure. It can be used to identify optimal agronomic management of cotton to achieve optimal plant structure for maximum yield under varying environmental conditions.     

Genome-wide association mapping of quantitative resistance to sudden death syndrome in soybean

Background

Sudden death syndrome (SDS) is a serious threat to soybean production that can be managed with host plant resistance. To dissect the genetic architecture of quantitative resistance to the disease in soybean, two independent association panels of elite soybean cultivars, consisting of 392 and 300 unique accessions, respectively, were evaluated for SDS resistance in multiple environments and years. The two association panels were genotyped with 52,041 and 5,361 single nucleotide polymorphisms (SNPs), respectively. Genome-wide association mapping was carried out using a mixed linear model that accounted for population structure and cryptic relatedness.

Result

A total of 20 loci underlying SDS resistance were identified in the two independent studies, including 7 loci localized in previously mapped QTL intervals and 13 novel loci. One strong peak of association on chromosome 18, associated with all disease assessment criteria across the two panels, spanned a physical region of 1.2 Mb around a previously cloned SDS resistance gene (GmRLK18-1) in locus Rfs2. An additional variant independently associated with SDS resistance was also found in this genomic region. Other peaks were within, or close to, sequences annotated as homologous to genes previously shown to be involved in plant disease resistance. The identified loci explained an average of 54.5% of the phenotypic variance measured by different disease assessment criteria.

Conclusions

This study identified multiple novel loci and refined the map locations of known loci related to SDS resistance. These insights into the genetic basis of SDS resistance can now be used to further enhance durable resistance to SDS in soybean. Additionally, the associations identified here provide a basis for further efforts to pinpoint causal variants and to clarify how the implicated genes affect SDS resistance in soybean.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-809) contains supplementary material, which is available to authorized users.     

Tree girdling responses simulated by a water and carbon transport model

Background and Aims

Girdling, or the removal of a strip of bark around a tree''s outer circumference, is often used to study carbon relationships, as it triggers several carbon responses which seem to be interrelated.

Methods

An existing plant model describing water and carbon transport in a tree was used to evaluate the mechanisms behind the girdling responses. Therefore, the (un)loading functions of the original model were adapted and became a function of the phloem turgor pressure.

Key Results

The adapted model successfully simulated the measured changes in stem growth induced by girdling. The model indicated that the key driving variables for the girdling responses were changes in turgor pressure due to local changes in sugar concentrations. Information about the local damage to the phloem system was transferred to the other plant parts (crown and roots) by a change in phloem pressure. After girdling, the loading rate was affected and corresponded to the experimentally observed feedback inhibition. In addition, the unloading rate decreased after girdling and even reversed in some instances. The model enabled continuous simulation of changes in starch content, although a slight underestimation was observed compared with measured values.

Conclusions

For the first time a mechanistic plant model enabled simulation of tree girdling responses, which have thus far only been experimentally observed and fragmentally reported in literature. The close agreement between measured and simulated data confirms the underlying mechanisms introduced in the model.     

Modelling seagrass growth and development to evaluate transplanting strategies for restoration

Background and Aims

Seagrasses are important marine plants that are under threat globally. Restoration by transplanting vegetative fragments or seedlings into areas where seagrasses have been lost is possible, but long-term trial data are limited. The goal of this study is to use available short-term data to predict long-term outcomes of transplanting seagrass.

Methods

A functional–structural plant model of seagrass growth that integrates data collected from short-term trials and experiments is presented. The model was parameterized for the species Posidonia australis, a limited validation of the model against independent data and a sensitivity analysis were conducted and the model was used to conduct a preliminary evaluation of different transplanting strategies.

Key Results

The limited validation was successful, and reasonable long-term outcomes could be predicted, based only on short-term data.

Conclusions

This approach for modelling seagrass growth and development enables long-term predictions of the outcomes to be made from different strategies for transplanting seagrass, even when empirical long-term data are difficult or impossible to collect. More validation is required to improve confidence in the model''s predictions, and inclusion of more mechanism will extend the model''s usefulness. Marine restoration represents a novel application of functional–structural plant modelling.     

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.     

Interspecific gene flow in a multispecies oak hybrid zone in the Sierra Tarahumara of Mexico

Background and Aims

Interspecific gene flow can occur in many combinations among species within the genus Quercus, but simultaneous hybridization among more than two species has been rarely analysed. The present study addresses the genetic structure and morphological variation in a triple hybrid zone formed by Q. hypoleucoides, Q. scytophylla and Q. sideroxyla in north-western Mexico.

Methods

A total of 247 trees from ten reference and 13 presumed intermediate populations were characterized using leaf shape variation and geometric morphometrics, and seven nuclear microsatellites as genetic markers. Discriminant function analysis was performed for leaf shape variation, and estimates of genetic diversity and structure, and individual Bayesian genetic assignments were obtained.

Key Results

Reference populations formed three completely distinct groups according to discriminant function analysis based on the morphological data, and showed low, but significant, genetic differentiation. Populations from the zone of contact contained individuals morphologically intermediate between pairs of species in different combinations, or even among the three species. The Bayesian admixture analysis found that three main genetic clusters best fitted the data, with good correspondence of reference populations of each species to one of the genetic clusters, but various degrees of admixture evidenced in populations from the contact area.

Conclusions

The three oak species have formed a complex hybrid zone that is geographically structured as a mosaic, and comprising a wide range of genotypes, including hybrids between different species pairs, backcrosses and probable triple hybrids.     

A Risk Assessment Model for Type 2 Diabetes in Chinese

Aims

To develop a risk assessment model for persons at risk from type 2 diabetes in Chinese.

Materials and Methods

The model was generated from the cross-sectional data of 16246 persons aged from 20 years old and over. C4.5 algorithm and multivariate logistic regression were used for variable selection. Relative risk value combined with expert decision constructed a comprehensive risk assessment for evaluating the individual risk category. The validity of the model was tested by cross validation and a survey performed six years later with some participants.

Results

Nine variables were selected as risk variables. A mathematical model was established to calculate the average probability of diabetes in each cluster''s group divided by sex and age. A series of criteria combined with relative RR value (2.2) and level of risk variables stratified individuals into four risk groups (non, low, medium and high risk). The overall accuracy reached 90.99% evaluated by cross-validation inside the model population. The incidence of diabetes for each risk group increased from 1.5 (non-risk group) to 28.2(high-risk group) per one thousand persons per year with six years follow-up.

Discussion

The model could determine the individual risk for type 2 diabetes by four risk degrees. This model could be used as a technique tool not only to support screening persons at different risk, but also to evaluate the result of the intervention.     

Specificity of extrafloral nectar induction by herbivores differs among native and invasive populations of tallow tree

Background and Aims

Invasive plants can be released from specialist herbivores and encounter novel generalists in their introduced ranges, leading to variation in defence among native and invasive populations. However, few studies have examined how constitutive and induced indirect defences change during plant invasion, especially during the juvenile stage.

Methods

Constitutive extrafloral nectar (EFN) production of native and invasive populations of juvenile tallow tree (Triadica sebifera) were compared, and leaf clipping, and damage by a native specialist (Noctuid) and two native generalist caterpillars (Noctuid and Limacodid) were used to examine inducible EFN production.

Key results

Plants from introduced populations had more leaves producing constitutive EFN than did native populations, but the content of soluble solids of EFN did not differ. Herbivores induced EFN production more than simulated herbivory. The specialist (Noctuid) induced more EFN than either generalist for native populations. The content of soluble solids in EFN was higher (2·1 times), with the specialist vs. the generalists causing the stronger response for native populations, but the specialist response was always comparable with the generalist responses for invasive populations.

Conclusions

These results suggest that constitutive and induced indirect defences are retained in juvenile plants of invasive populations even during plant establishment, perhaps due to generalist herbivory in the introduced range. However, responses specific to a specialist herbivore may be reduced in the introduced range where specialists are absent. This decreased defence may benefit specialist insects that are introduced for classical biological control of invasive plants.     

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.