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Reducing planting distances is one of the strategies to increase yield in fruit orchards. The yield of an orchard increases with tree density, especially in the case of small tree canopies. However, orchard yield can decrease when trees planted at high densities have a large canopy size. In trees growing in optimal conditions, i.e., without water or nutrient stress, this yield reduction is likely to be the result of competition for light as well as an imbalance between vegetative and fruit growth. Separating these factors and their interactions in the field is not straightforward. Models of carbon acquisition and distribution between organs have been used to simulate and understand some factors affecting yield tree or within the tree. Modeling might help to understand better the effects of tree density and size on orchard yield. We employed a functional-structural tree model to simulate individual organ growth within the canopy as well as tree and orchard yield with different planting distances and tree size. This virtual plant combined sub-models of light interception, photosynthesis, potential relative growth rates of individual organs and inter-organ competition for carbon. Tree canopy architecture measured in the field was used to create several virtual orchard canopies with a range of tree sizes and planting distances. The model simulated growth and yield of individual trees and orchards during one growing season. Virtual experiments showed how different tree densities and sizes affected yield. It increased our understanding of and supported our hypotheses about the effects of planting distances and tree size on orchard yields, which can be useful for designing future field experiments and orchards.

Pine wilt disease caused by a forest-invasive alien species, the pine wood nematode (Bursaphelenchus xylophilus) is considered as one of the most destructive pest problems. In recent years, spectroscopic technologies have shown great potentials for the assessment of forest damage due to their nondestructive, noninvasive, cost-effective, and rapidly responsive nature. This paper first identified the hyperspectral characteristics of pine wilt disease by measuring and analyzing the changes in spectral reflectance of healthy and infected Pinus massoniana trees. Then 16 spectral features were extracted from the spectral bands covering the green region (510~580 nm), the red region (620~680 nm), the red edge (680~760 nm), the near-infrared region (780~1100 nm), and coded as genes composing the chromosome of a genetic algorithm (GA). Based on the optimal spectral features with suitable fitness from the GA, a partial least squares regression (PLSR) prediction model was built with highest determination coefficient R2c = 0.91, R2v = 0.82, relative prediction deviation RPD = 3.3 and lowest root mean square error RMSEc = 0.23, RMSEv = 0.33 on the calibration and validation datasets. Compared with other PLSR models, our proposed GA-based approach significantly improves the prediction accuracy with few input spectral features.

Functional–structural plant models (FSPM) explore the manifold relations between a plant’s structure and the processes that underlie its growth and development. Here we introduce selected papers presented at the 5th International Workshop on Functional–Structural Plant Models, held in Napier, New Zealand, 2007. The papers range from the microscopic scale of meristems to the macroscopic scales of whole plants and plant communities, and cover a wide range of plants, from algae to trees. The topics include examples of comprehensive functional–structural models, models of key processes such as partitioning of resources, software for modelling plants and plant environment, data acquisition techniques and applications of functional–structural plant models.

Macadamia canopies tend to grow large and complex due to vigorous recurrent flushes of vegetative growth. New shoot growth can occur at any time of the year from apical and axillary buds, elongating existing axes and forming new axis orders, respectively. The macadamia canopy is relatively unmodified and low yielding, thus yield efficiency and management practices would benefit from an increased understanding of canopy growth dynamics and architecture. Here we detail a range of investigations into the architectural development of macadamia over different scales, and methods for modifying architecture with a view to this information being incorporated into the design of improved orchard systems. For isolated shoots we have documented the elongation of internodes and the whole growth unit (GU), and their relationship to thermal time. We have also undertaken a detailed architectural study on two cultivars of young trees leading up to their first flowering, in an attempt to compare and understand patterns of early vegetative development. At the tree scale there were no differences in canopy volume or tree height between cultivars, however, detailed scales revealed differences in canopy components such as GU number, GU length and branching patterns. Shoot bending can modify vegetative architecture and reproductive development in temperate crops, although responses in subtropical crops could be more complicated. Bending first-order shoots in macadamia reduced apical growth and induced axillary release. When shoots are bent at the time of floral initiation raceme number was increased on the first-order shoot axis, possibly due to a coincidence between bending-induced axillary bud release and time-dependent floral signals. Observing interactions between components at different scales aids understanding of the mechanisms and relationships controlling the structure and function of the growing macadamia canopy, thus providing opportunities to modify macadamia growth for the benefit of production efficiency.

Fruit size is an important parameter affecting both yield and quality. Fruit of multiple sizes can be found within a tree canopy and this has been correlated with factors involving carbon availability, e.g., crop load, light and temperature. However, the underlying mechanisms determining fruit size distribution seem complex and not easy to identify. It is very difficult to carry out multi-factor field experiments to increase our understanding in this area due to time, economic and technical constraints. Functional-structural models of carbon acquisition and utilization have been previously employed to simulate and understand the effects of date of thinning and irrigation regime on size of individual fruits and fruit size distribution in the tree canopy. These models used concepts of potential relative growth rates of individual organs and inter-organ competition for carbon. We built a functional-structural model of canopy growth at the individual organ scale, and used this model to simulate and study patterns of fruit size distribution in tree canopies with different training systems, crop loads, light and temperature regimes. The functional-structural tree model combines models of light interception, photosynthesis, potential relative growth rates of individual organs and inter-organ competition for carbon within each shoot. Canopy architectural data were employed to reconstruct and visualize our trees in the modeling platform. These virtual canopies were selected as inputs for simulating the growth of individual shoots and fruits in the canopy during one growing season. Our model showed that we can simulate multi-factor experiments, allowing us to increase our understanding and test concepts about the effects of carbon availability on fruit size distribution in trees growing in orchard systems.

BACKGROUND AND AIMS: Transport of carbohydrates and water are essential aspects of plant function. The aim of this study was to develop and test the methods for mechanistic modelling of quasi-stationary coupled phloem/xylem transport in the context of functional–structural plant modelling. METHODS: The novelty of this approach is in combining analytical and computational methods. The plant structure is modelled at a metamer level with the internodes represented by conduit elements and the lateral organs represented by sources and sinks. Transport equations are solved analytically for each internode and then the solutions are adjusted and ‘sewn’ together using an iterative computational procedure taking into account concentration-dependent sinks and sources. The model is implemented in L-studio and uses the aspect-oriented modelling approach for phloem/xylem coupling. KEY RESULTS: To our knowledge, this is the first transport model that provides continuous distributions of the system variables in a complex developing structure. The model takes into account non-linear dependence of phloem resistance and osmotic potential on the local carbohydrate concentration. The model solutions show excellent agreement with the existing results of other analytical and numerical models. These comparisons confirm the validity of the approximations made in the model. Combining analytical and computational methods made it possible to take into account continuous sink/source distribution within internodes without much increase in the complexity of the computational procedure, because the necessary changes in the model were mostly in the analytical part. The results emphasize sensitivity of phloem flux and lateral xylem flux to the presence of distributed sinks and sources along the transport system. CONCLUSIONS: The presented approach provides a new insight into mechanistic modelling of phloem/xylem transport in growing plants. It will be useful for both fine-scale modelling of carbohydrate dynamics and for creating simpler models at a growth unit level.

Each leaf is both a sink and a source of carbon that determines the growth of plant structure. Therefore, simulation of individual leaf expansion is essential in modeling plant structural growth. Leaf expansion has been often fitted to logistic sigmoidal functions that require initial and final leaf length, and duration of elongation to be known. A different method, based on the compound interest law, determines leaf length using initial length, relative elongation rate and duration of elongation. We aimed to evaluate which factors are most important in explaining final leaf length variability. Elongation of individual leaves on peach shoots was monitored over 21 days. Individual leaf lengths were fitted to logistic functions to determine their initial and final lengths, and durations of elongation in growing degree hours. Parameters that could affect final leaf length were evaluated: shoot characteristics below the leaf, initial length, duration of elongation, and temperature during the initial days after leaf appearance. Final leaf length had significant relationships with leaf area and length of the shoot axis excluding sylleptic branches, but it was not significantly related to initial length or duration of elongation. Total shoot leaf area and temperature during the initial days after leaf appearance also affected final leaf length. Our results showed that final leaf length is mainly determined by factors acting during leaf elongation. Based on these data, we used compound interest law and carbon availability concepts to develop a mechanistic model of final lengths of individual leaves.

The Carbon Transport-Resistance Allocation Model (C-TRAM) developed for L-system plant models is based on an analogy between the equations for the osmoticpressure generated phloem-sap flow and Ohm's law. This analogy has proved to be rather confusing because some of the model variables, for example source/sink 'electromotive force', do not have any physiological interpretation. Also, the fact that the transport equations are formulated in terms of phloem-sap flow Jp, while organ growth rates are usually expressed in mass carbohydrate flux Js, does not improve model clarity and consistency. The current paper presents a direct way of solving transport equations based on the Munch hypothesis, consistent with boundary conditions in the form of Michaelis-Menten source/sink fluxes, and accounting for the effects of carbohydrate concentration on phloem resistance. Starting from a system of equations for steady-state coupled phloem/xylem flow (Hall and Minchin, 2013), for a constant water potential in the xylem, an equation for the solute mass flow Js in a conduit element can be obtained in a closed form. The boundary problem in the context of L-system plant models was solved using analytical transformations and computational methods similar to the folding/unfolding algorithm of C-TRAM but not based on the electric circuit analogy. The performance of the transport model was tested using a simple system where exact analytical solutions were available (Hall and Minchin, 2013). To our knowledge, this is the first L-system model that combines a rigorous treatment of the carbohydrate transport in a growing system with Michaelis-Menten source/sink functions. The model will be useful in cases where the actual value of the carbohydrate concentration in phloem is important, e.g., sugar signalling. Currently the model is being extended to take into account phloem/xylem coupling.

Background and Aims Functional–structural plant (FSP) models provide insights into the complex interactions between plant architecture and underlying developmental mechanisms. However, parameter estimation of FSP models remains challenging. We therefore used pattern-oriented modelling (POM) to test whether parameterization of FSP models can be made more efficient, systematic and powerful. With POM, a set of weak patterns is used to determine uncertain parameter values, instead of measuring them in experiments or observations, which often is infeasible. Methods We used an existing FSP model of avocado (Persea americana ‘Hass’) and tested whether POM parameterization would converge to an existing manual parameterization. The model was run for 10 000 parameter sets and model outputs were compared with verification patterns. Each verification pattern served as a filter for rejecting unrealistic parameter sets. The model was then validated by running it with the surviving parameter sets that passed all filters and then comparing their pooled model outputs with additional validation patterns that were not used for parameterization. Key Results POM calibration led to 22 surviving parameter sets. Within these sets, most individual parameters varied over a large range. One of the resulting sets was similar to the manually parameterized set. Using the entire suite of surviving parameter sets, the model successfully predicted all validation patterns. However, two of the surviving parameter sets could not make the model predict all validation patterns. Conclusions Our findings suggest strong interactions among model parameters and their corresponding processes, respectively. Using all surviving parameter sets takes these interactions into account fully, thereby improving model performance regarding validation and model output uncertainty. We conclude that POM calibration allows FSP models to be developed in a timely manner without having to rely on field or laboratory experiments, or on cumbersome manual parameterization. POM also increases the predictive power of FSP models.

Food security and the sustainability of native ecosystems depends on plant-insect interactions in countless ways. Recently reported rapid and immense declines in insect numbers due to climate change, the use of pesticides and herbicides, the introduction of agricultural monocultures, and the destruction of insect native habitat, are all potential contributors to this grave situation. Some researchers are working towards a future where natural insect pollinators might be replaced with free-flying robotic bees, an ecologically problematic proposal. We argue instead that creating environments that are friendly to bees and exploring the use of other species for pollination and bio-control, particularly in non-European countries, are more ecologically sound approaches. The computer simulation of insect-plant interactions is a far more measured application of technology that may assist in managing, or averting, ‘Insect Armageddon' from both practical and ethical viewpoints.

Background and AimsMany experimental studies assume that some topological units are autonomous with regard to carbon because it is convenient. Some plant models simulate carbon allocation, employing complex approaches that require calibration and fitted parameters. For whole-tree canopy simulations, simpler carbon allocation models can provide useful insights.MethodsWe propose a new method for simulating carbon allocation in the whole tree canopy considering various scales of carbon autonomy, i.e. branchlets, branches, limbs, and no autonomy. This method was implemented in a functional–structural plant model of growth of individual organs for studying macadamia tree growth during one growing season.Key ResultsThis model allows the simulation of various scales of carbon autonomy in a simple tree canopy, showing organ within-tree variability according to the scale of autonomy. Using a real tree canopy, we observed differences in growth variability within the tree and in tree growth, with several scales of carbon autonomy. The simulations that assumed autonomy at branch scale, i.e. 2-year-old wood, showed the most realistic results.ConclusionsSimulations using this model were employed to investigate and explain aspects of differences in carbon autonomy between trees, organ growth variability, competition between shoot and fruit growth, and time of autonomy.

Retention of sprays on plants is a critical component influencing the effectiveness of agrichemical applications. Previous simulations of spray retention by plants gave poor agreement for hard-to-wet species when compared with actual measured retention. A new model is developed here that accounts for: species wettability, impaction angle, droplet bounce, partial retention on shatter, a variable time to shatter, and the number of daughter droplets produced. The aim of this study was to compare predictions from the new model with data obtained by spraying five mixtures via five nozzles onto easy-to-wet cotton (Gossypium hirsutum L.), and hard-to-wet wheat (Triticum aestivum L.) and fat hen (Chenopodium album L.). The new model correctly predicts retention to be highest on cotton and lowest on wheat. The trend in both measured data and the model predictions is for retention to decrease with increasing droplet size, on all three plant species. Formulation is correctly predicted to have little influence on retention by easy-to-wet cotton plants and to enhance retention by the harder-to-wet wheat and fat hen plants. The parameters that describe partial retention on shatter and variable time to shatter have a substantial influence on retention, as they affect primary or secondary droplet capture. A better understanding of the kinetic energy effects and the interactions between the formulation and the leaf surface are needed to refine their input values.

The effect of carbohydrate sources on vegetative growth in macadamia at two major flushing times (March and September in southern hemisphere) were studied indirectly by measuring the growth rate of individual flushes in response to girdling and defoliation treatments during the vegetative growth period. Internode length and girth of a single flush were affected significantly by girdling and defoliation treatments. Two sources of carbohydrate were hypothesised for vegetative growth of the single flush; reserved carbohydrate and current photosynthate. The contribution of these sources to vegetative growth were defined and calculated from the differences between the combinations of girdling and defoliation treatments over time. Based on the results for two major flushing times, reserved carbohydrate contributes more to vegetative growth of macadamia than current photosynthesis.

A self-organising model of macadamia, expressed using L-Systems, was used to explore aspects of canopy management. A small set of parameters control the basic architecture of the model, with a high degree of self-organisation occurring to determine the fate and growth of buds. Light was sensed at the leaf level and used to represent vigour and accumulated basipetally. Buds also sensed light so as to provide demand in the subsequent redistribution of the vigour. Empirical relationships were derived from a set of 24 completely digitised trees after conversion to multiscale tree graphs (MTG) and analysis with the OpenAlea software library. The ability to write MTG files was embedded within the model so that various tree statistics could be exported for each run of the model. To explore the parameter space a series of runs was completed using a high-throughput computing platform. When combined with MTG generation and analysis with OpenAlea it provided a convenient way in which thousands of simulations could be explored. We allowed the model trees to develop using self-organisation and simulated cultural practices such as hedging, topping, removal of the leader and limb removal within a small representation of an orchard. The model provides insight into the impact of these practices on potential for growth and the light distribution within the canopy and to the orchard floor by coupling the model with a path-tracing program to simulate the light environment. The lessons learnt from this will be applied to other evergreen, tropical fruit and nut trees.

Biomass partitioning is a pivotal part of the function-structure feedback mechanism. To improve the simulation of aboveground biomass partitioning in growth models for rapeseed (Brassica napus L.), we developed an aboveground biomass partitioning coefficient model for main stem and primary branches, and the stems, leaves, and pods on them, by quantifying the relationships between the biomass partitioning coefficient of major organs aboveground and physiological day of development (DPD). To realize this goal, dry matter data of organs were derived from an outdoor experiment with rapeseed cultivars Ningyou18 and Ningza19 under different fertilizer and transplanting density treatments in the 2012–2015 growing seasons. The model was fitted by calculating the partitioning coefficients of different organs as the ratio of the biomass of organs and their superior organs and normalizing DPD into the [0, 1] interval. Various model variables were parameterized to explain the effects of cultivar and environmental conditions on biomass partitioning coefficients for different organs. Our descriptive models were validated with independent experimental data, the correlation (r) of simulation and observation values all had significant level at P

Since their inception in 1968, L-systems have become a key conceptual, mathematical and software tool for modeling plant development at different levels of plant organization spanning molecular genetics, plant physiology, whole plant architecture and plant communities. The models can be descriptive, directly recapitulating observations and measurements of plants; mechanistic, explaining higher-level processes in terms of lower-level ones; or they may combine features of both classes. We present the basic idea of L-systems, motivate and outline some of their most useful extensions, and give a taste of current techniques for modeling with L-systems. The sample models progress in the scale of organization from a bacterium to a herbaceous plant to a tree, and simulate different forms of information transfer during the development, from communication between adjacent cells to bidirectional information exchange with the environment.

Visual representations of plant architectural data are useful for different reasons, e.g. data verification, preliminary analysis, or demonstrating and communicating research. Architectural data are the result of measurements in the field or simulations with plant growth models, which are often recorded in multiscale tree graphs (MTG). L-studio is a modelling platform that includes a simulation program called lpfg based on L-systems. Lpfg has been employed to create tree-like structures, and simulate the dynamical growth and development of plants, i.e. their changes in time. This program incorporates several features that would make it a very useful tool for visualizing plant architectures measured in the field. Our aims are to show some examples of the use of L-systems as a visualization tool for field data; and modify architectural data to create architectures resulting from applying different management practices, e.g. mechanical pruning and tree shape. We employed a field measured architecture recorded in an MTG as an example of our approach to visualize and modify plant architectures. These ideas can be employed for field data verification, preliminary analysis, demonstrative purposes, and to start subsequent simulations of plant growth with architectures modified to represent different management practices.

BACKGROUND AND AIMS: Functional–structural plant (FSP) models have been widely used to understand the complex interactions between plant architecture and underlying developmental mechanisms. However, to obtain evidence that a model captures these mechanisms correctly, a clear distinction must be made between model outputs used for calibration and thus verification, and outputs used for validation. In pattern-oriented modelling (POM), multiple verification patterns are used as filters for rejecting unrealistic model structures and parameter combinations, while a second, independent set of patterns is used for validation. METHODS: To test the potential of POM for FSP modelling, a model of avocado (Persea americana ‘Hass’) was developed. The model of shoot growth is based on a conceptual model, the annual growth module (AGM), and simulates photosynthesis and adaptive carbon allocation at the organ level. The model was first calibrated using a set of observed patterns from a published article. Then, for validation, model predictions were compared with a different set of empirical patterns from various field studies that were not used for calibration. KEY RESULTS: After calibration, our model simultaneously reproduced multiple observed architectural patterns. The model then successfully predicted, without further calibration, the validation patterns. The model supports the hypothesis that carbon allocation can be modelled as being dependent on current organ biomass and sink strength of each organ type, and also predicted the observed developmental timing of the leaf sink–source transition stage. CONCLUSIONS: These findings suggest that POM can help to improve the ‘structural realism’ of FSP models, i.e. the likelihood that a model reproduces observed patterns for the right reasons. Structural realism increases predictive power so that the response of an AGM to changing environmental conditions can be predicted. Accordingly, our FSP model provides a better but still parsimonious understanding of the mechanisms underlying known patterns of AGM growth.

Allometric relationships of plant organs reflect internal coordination of different aspects of organ development, allowing the linking of plant structural development and underlying physiological processes for the development of functional-structural plant models (FSPMs). This paper aims to (i) explore the allometric relationships between organ morphology and fresh biomass in maize; (ii) develop equations to describe these relationships; and (iii) examine the response of allometric relationships to crop water availability and plant density. Datasets were obtained from field experiments in which three commercial maize cultivars (Pioneer 34N43, Pioneer 31H50 and NongDa 108) were grown under different water regimes and plant densities. Relationships are described between (i) lamina length and biomass for all phytomers by a power function, (ii) lamina maximum width and biomass by a power and a logarithmic function separated at ear position, (iii) sheath length and biomass by power and logarithmic functions separated at eighth sheath position where the sheath length peaked, and (iv) internode length and biomass by two power functions separated at the ear position across water regimes and plant densities. The allometric relationships of organ development were not affected by the mild water stress, but were modified by the increased plant densities. Consequently, the allometric relationships found in this study and their expressions using mathematical equations enable plant morphology to be predicted from physiological output (biomass accumulation), which provides a biologically robust mechanism of realizing functional-structural communication used in FSPMs.

Pesticides used in agricultural systems must be applied in economically viable and environmentally sensitive ways, and this often requires expensive field trials on spray deposition and retention by plant foliage. Computational models to describe whether a spray droplet sticks (adheres), bounces or shatters on impact, and if any rebounding parent or shatter daughter droplets are recaptured, would provide an estimate of spray retention and thereby act as a useful guide prior to any field trials. Parameter-driven interactive software has been implemented to enable the end-user to study and visualise droplet interception and impaction on a single, horizontal leaf. Living chenopodium, wheat and cotton leaves have been scanned to capture the surface topography and realistic virtual leaf surface models have been generated. Individual leaf models have then been subjected to virtual spray droplets and predictions made of droplet interception with the virtual plant leaf. Thereafter, the impaction behaviour of the droplets and the subsequent behaviour of any daughter droplets, up until re-capture, are simulated to give the predicted total spray retention by the leaf. A series of critical thresholds for the stick, bounce, and shatter elements in the impaction process have been developed for different combinations of formulation, droplet size and velocity, and leaf surface characteristics to provide this output. The results show that droplet properties, spray formulations and leaf surface characteristics all influence the predicted amount of spray retained on a horizontal leaf surface. Overall the predicted spray retention increases as formulation surface tension, static contact angle, droplet size and velocity decreases. Predicted retention on cotton is much higher than on chenopodium. The average predicted retention on a single horizontal leaf across all droplet size, velocity and formulations scenarios tested, is 18, 30 and 85% for chenopodium, wheat and cotton, respectively.

Pesticides are commonly applied by using hydraulic nozzles to generate droplets. The properties of these spray droplets can influence the effectiveness and risks associated with the use of pesticides. Initial spray characteristics (initial droplet size and velocity, fan angle and spray liquid density) were therefore measured for a range of hydraulic nozzles and spray mixtures. Particle Image Velocimetry (PIV) was used to measure the spray sheet velocity.There was a significant difference between a standard hydraulic nozzle, Turbo TeeJet® and air induction nozzle for all measured spray characteristics. The standard hydraulic nozzle generated the smallest droplet sizes, the highest velocity and the highest spray liquid density. The air induction nozzle generated the largest droplet size, the slowest velocity and the lowest spray liquid density. The type of air induction nozzle and spray formulation was also found to influence spray characteristics.This work has demonstrated that initial spray characteristics such as droplet size and velocity, liquid density, fan angle and included air can vary depending on nozzle design, operating parameters and spray formulations. Initial droplet velocity was found to be significantly correlated to droplet size (Dv0.5) and spray pressure.

Trajectories of dispersing seeds begin at the positions of their fruits on the maternal plant. Mechanistic simulation models usually assume that seed release is restricted to a characteristic, species-specific height. However, real canopies constitute distributed rather than point sources, which may have important consequences for dispersal kernels. Fruit positions are determined by plant architecture, which is under both genetic control and environmental influence. Competition with other plants has a major modifying influence on canopy structure. We used quantitative methods to describe the positions of fruits on plants of Raphanus raphanistrum L., examined how fruit spatial distributions change when plants grow under interspecific competition and explored how this is related to changes in the structural geometry and topology of the plant. Raphanus raphanistrum was grown either as individual plants or in a wheat crop. Branching structures and fruit positions were captured using a three-dimensional digitizer. Propagule locations were also mapped on the ground after dispersal. Fruit distributions pre-dispersal were analysed using various statistical approaches; plant topological and geometrical indices were calculated for the branching structures. Plants grown under competition were smaller, but the reduced size was because fewer modules were produced rather than because individual branches were in some way different. The distribution of these branches was also different under competition, with more apical dominance resulting in less branching along dominant modules. Under competition, fruits were concentrated in the upper parts of the canopy and closer, in the horizontal plane, to the base of the plant. This resulted in much more restricted local seed shadows post-dispersal. Synthesis. The effect of competition on plant size is primarily a result of a reduction in initiation of branches. For species with limited dispersal ability, this results in a greatly modified seed shadow at short distances. In the case of agricultural weeds, the concentration of fruits at greater heights when competing with a crop might result in a greater proportion being dispersed long distances by harvesting machinery, but they would be fewer in number. © 2013 The Authors. Journal of Ecology

UMR AGAP - équipe AFEF - Architecture et fonctionnement des espèces fruitièresUMR AGAP - équipe AFEF - Architecture et fonctionnement des espèces fruitières; Flowering is a key process that determines yield in fruit trees, and a negative relationship between crop load and floral induction has been observed in many species. In apple tree, hormonal signals coming from seeds, which are assumed to be transported within the tree, are suspected to inhibit floral induction. To analyze the intertwined effects of tree architecture, crop load and inhibitory signal on floral induction we developed a generic model based on the L-system formalism. The model simulates both the basipetal and acropetal flux of the signal as well as its partitioning at each branching point and between successive metamers. First simulations on apple tree, using architectures generated by the MappleT model, showed that the model was able to reproduce well-known results of the literature, such as the variability in floral induction rate according to shoot length and type, and to reproduce experimental observations of the impact of crop load on floral induction. Moreover, the model also has the ability to simulate contrasted behavior in term of flowering patterns at the branch scale that could be related to genotypic characteristics. Although new experiments are needed to fully calibrate the model, it gives insights into interactions between plant development, architecture and floral induction that could be useful in the future for plant breeders and growers to adjust thinning intensity.

Computational modelling is becoming increasingly significant in improving our understanding of natural systems, and in making predictions to manage them. Many computational models have been used in various areas for these purposes. However, it has been suggested that models should not be either too simple or too complex, if they are to be useful. Thus, it is of importance to construct models with an optimised model structure that sufficiently well represents their real world counterparts. To do that, better modelling strategies are needed. The pattern-oriented modelling (POM) strategy is an approach that has been proposed to address these issues. It has been used widely to develop agent-based models (ABMs), aiming to make the models more comprehensive and rigorous, and increasing their predictive power. Functional-structural plant models (FSPMs) can be identified as ABMs, if organs/growth units of a plant are considered as agents. To test the feasibility and demonstrate the value of using the POM strategy for functional-structural plant modelling, this study focuses on modelling of avocado (Persea americana, cv. Hass), because of its clear modular construction and its economic significance to subtropical and tropical horticulture world-wide. Our study focuses on the systematic development of techniques to apply the POM strategy to functional-structural plant modelling. The overall objective was to determine whether the POM strategy could be used to construct FSPMs in order to increase their predictive power. In the present study, a functional-structural plant model of the annual growth module of avocado was constructed using the POM strategy. The model was able to reproduce multiple observed patterns of architecture and shoot growth simultaneously, and to make independent predictions providing insights into branching architecture, which were consistent with independently generated findings of other studies. Comparison of model outcomes to multiple observed patterns of modular construction at different scales, e.g. metamer level, growth unit level and branch level, increases our confidence that the model performed well. Those independent predictions can be strong indicators that the model is structurally realistic.

Climate change influences on pests and pathogens are mainly plant-mediated. Rising carbon dioxide and temperature and altered precipitation modifies plant growth and development with concomitant changes in canopy architecture, size, density, microclimate and the quantity of susceptible tissue. The modified host physiology and canopy microclimate at elevated carbon dioxide influences production, dispersal and survival of pathogen inoculum and feeding behaviour of insect pests. Elevated temperature accelerates plant growth and developmental rates to modify canopy architecture and pest and pathogen development. Altered precipitation affects canopy architecture through either drought or flooding stress with corresponding effects on pests and pathogens. But canopy-level interactions are largely ignored in epidemiology models used to project climate change impacts. Nevertheless, models based on rules of plant morphogenesis have been used to explore pest and pathogen dynamics and their trophic interactions under elevated carbon dioxide. The prospect of modifying canopy architecture for pest and disease management has also been raised. We offer a conceptual framework incorporating canopy characteristics in the traditional disease triangle concept to advance understanding of host-pathogen-environment interactions and explore how climate change may influence these interactions. From a review of recent literature we summarize interrelationships between canopy architecture of cultivated crops, pest and pathogen biology and climate change under four areas of research: (a) relationships between canopy architecture, microclimate and host-pathogen interaction; (b) effect of climate change related variables on canopy architecture; (c) development of pests and pathogens in modified canopy under climate change; and (d) pests and pathogen management under climate change.

Interacting with and translating across multiple representations is an essential characteristic of expertise and representational fluency. In this study, we explored the effect of interacting with and translating between representations in a computer simulation or in a paper-based assignment on scientific accuracy of undergraduate science students’ explanations regarding the underlying mechanisms of action potential. The study proposed that a simulation designed with scaffolded inquiry and with multiple dynamically linked representations fosters students to use greater scientific accuracy in speaking about a complex scientific phenomenon as well as to work with this complex knowledge in higher cognitive domains. Student explanations were analysed for use of accurate scientific language as they worked with the instructional tool as well as under test conditions. We also investigated the cognitive domain that students worked within as they created explanations of the phenomenon under study. The proportion of elaborations that occurred in higher-level cognitive domains such as applying, analysing, evaluating and synthesising was used to denote representational fluency. The rationale for this approach is discussed. Findings suggest that the simulation prompted students towards operating in higher cognitive domains in order to construct new knowledge and therefore promoted representational fluency. It also suggests that translating between representations in a simulation in a collaborative social setting contributes towards students’ use of accurate scientific language. Students’ perceptions expressed during the interviews confirmed the findings.

To quantify the relationships between rice plant architecture parameters and the corresponding organ biomass, and to research on functional structural plant models of rice plant, this paper presented a biomass-based model of aboveground architectural parameters of rice ( Oryza sativa L.) in the young seedling stage, designed to explain effects of cultivars and environmental conditions on rice aboveground morphogenesis at the individual leaf level. Various model variables, including biomass of blade and blade length, were parameterized for rice based on data derived from an outdoor experiment with rice cv . Liangyou 108, 86You 8, Nanjing 43, and Yangdao 6. The organ dimensions of rice aboveground were modelled taking corresponding organ biomass as an independent variable. Various variables in rice showed marked consistency in observation and simulation, suggesting possibilities for a general rice architectural model in the young seedling stage. Our descriptive model was suitable for our objective. However, they can set the stage for connection to physiological model via biomass and development of functional structural rice models (FSRM), and start with the localized production and partitioning of assimilates as affected by abiotic growth factors. The finding of biomass-based rice architectural parameter models also can be used in morphological models of blade, sheath, and tiller of the other stages in rice life.

In this paper, the many indices used in validation of crop models, such as RMSE (root mean square errors), Sd (standard error of absolute difference), da (mean absolute difference), dap (ratio of da to the mean observation), r (correlation), and R2 (determination coefficient), are compared for the same rice architectural parameter model, and their advantages and disadvantages are analyzed. A new index for validation of crop models, dap between the observed and the simulated values, is proposed, with dap

This study used an interactive dynamic simulation of action potential to explore social practices of learning among first year undergraduate biology students. It aimed to create a learning environment that fosters knowledge building discourse through working with multiple concept-specific representations. Three hundred and eighty-nine students and twenty-four tutors from different tutorial classes in Queensland, Australia participated in the study. Students were randomly allocated to two experimental groups and a comparison group. In the experimental groups, pairs of students used the interactive simulation to explore action potential. Only one of the experimental groups received instruction that modelled the scientific and visual language conventions of the representations within the simulation. In the comparison group, small groups of students used a traditional paper-based activity. Students across all groups were audio recorded using a think-aloud protocol while completing the group activity. Individual learning gains in the experimental groups and the comparison group were similar. However, the experimental groups showed a significantly greater frequency of knowledge construction discourse that included explanatory answers, evaluations, interpretation, testing and synthesis compared to the comparison group, indicating a deeper understanding of action potential. Analysis of misconceptions on the post-test and tutors’ reflections revealed that the experimental group receiving instruction modelling the scientific and visual language conventions around the representations had a better grasp of the terminology associated with the concepts compared with the other groups. The findings suggest that instruction focussing on the language conventions of concept-specific representations fosters the development of disciplinary discourse by transforming students’ social practices of working with scientific knowledge.

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.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.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.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.

Canopy-level interactions have been largely ignored in epidemiological models and their applications in defining disease risks under climate change, although these interactions are important for disease management. This paper uses anthracnose of Stylosanthes scabra as a case study and reviews research on dynamics of the pathogen (Colletotrichum gloeosporioides) at the canopy level and pathogen evolution under changing climate. It argues that linking of pathogen dynamics, crop growth and climate models is essential in predicting disease risks under climate change. A plant functional-structural model was used to couple S. scabra growth and architecture with disease under ambient and elevated CO(2). A level of induced resistance in plants with enlarged canopy determined anthracnose severity at elevated CO(2). Moisture-related microclimatic variables determined infection at ambient but not at elevated CO(2). At high CO(2) increased disease level from raised pathogen fecundity in enlarged canopy accelerated pathogen evolution after 25 sequential infection cycles. Modelling of pathogen dynamics under climate change currently suffers from a paucity of quantitative data, mismatch of scales in coupling climate and disease models, and model uncertainties. Further experimental research on interactions of biotic and abiotic factors on plant diseases under climate change and validation of models are essential prior to their use in climate-change prediction. Understanding and anticipating trends in host-pathogen evolution under climate change will improve the durability of resistance and lay the foundation for increased crop adaptation through pre-emptive plant breeding.

Autoregulation of nodulation is a long-distance shoot-root signalling regulatory system that regulates nodule meristem proliferation in legume plants. However, due to the intricacy and subtleness of the signalling nature in plants, molecular and biochemical details underlying mechanisms of autoregulation of nodulation remain largely unknown. The purpose of this study is to use functional-structural plant modelling to investigate the complexity of this signalling system. There are two major challenges to be met: modelling the 3D architecture of legume roots with nodulation and co-ordinating signalling-developmental processes with various rates.Soybean (Glycine max) was chosen as the target legume. Its root system was observed to capture lateral root branching and nodule distribution patterns. L-studio, a software tool supporting context-sensitive L-system modelling, was used for the construction of the architectural model and integration with the internal signalling.A branching pattern with regular radial angles was found between soybean lateral roots, from which a root mapping method was developed to characterize the laterals. Nodules were mapped based on 'nodulation section' to reveal nodule distribution. A root elongation algorithm was then developed for simulation of root development. Based on the use of standard sub-modules, a synchronization algorithm was developed to co-ordinate multi-rate signalling and developmental processes.The modelling methods developed here not only allow recreation of legume root architecture with lateral branching and nodulation details, but also enable parameterization of internal signalling to produce different regulation results. This provides the basis for using virtual experiments to help in investigating the signalling mechanisms at work.

Locomotory behaviour of 1st instar Helicoverpa armigera is influenced by a complex of micro-attributes, the leaf “environment”, comprising odours, wax chemistry, trichomes and grip texture. Larval movement speeds on leaves of different types varied more than eight fold. On garden pea, Pisum sativum, there is a hierarchy of stimuli perceived by larvae resulting in differing behavioural responses. Light and angle are paramount in responses to micro-environment. These influence responses to local stimuli. Experiments in darkness produce different responses from those under laboratory light. In darkness, on horizontal surfaces as found for most leaves, preference for leaf surface is driven by micro-environment associated with leaf waxes. Larvae prefer the abaxial surface. In light, on horizontal surfaces, larvae seek enclosed spaces and foray under leaf surfaces. They wander more openly in the dark. Such information is important in building a model of larval behaviour and predicting behaviour on differing plant architectures.

The distribution and movement of 1st instar Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) larvae on whole garden pea (Pisum sativum L.) plants were determined in glasshouse trials. This economically-important herbivore attacks a wide variety of agricultural, horticultural and indigenous plants. To investigate the mechanisms underlying larval intra-plant movement, we used early-flowering and wild-type plant genotypes and placed eggs at different vertical heights within the plants, one egg per plant. Leaf water and nitrogen content and cuticle hardness were measured at the different plant heights. Of 92 individual larvae, 41% did not move from the node of eclosion, 49% moved upwards and 10% moved downwards with the distance moved being between zero and ten plant nodes. Larvae from eggs placed on the lower third of the plant left the natal leaf more often and moved further than larvae from eggs placed in the middle or upper thirds. The low nutritive value of leaves was the most likely explanation for more movement away from lower plant regions. Although larvae on flowering plants did not move further up or down than larvae on non-flowering plants, they more often departed the leaflet (within a leaf) where they eclosed. The final distribution of larvae was affected by plant genotype, with larvae on flowering plants found less often on leaflets and more often on stipules, tendrils and reproductive structures. Understanding intra-plant movement by herbivorous insects under natural conditions is important because such movement determines the value of economic loss to host crops. Knowing the behaviour underlying the spatial distribution of herbivores on plants will assist us to interpret field data and should lead to better informed pest management decisions.