Jochem B. Evers

Functional–structural plant modelling: a new versatile tool in crop science

Plants react to their environment and to management interventions by adjusting physiological functions and structure. Functional-structural plant models (FSPM), combine the representation of three-dimensional (3D) plant structure with selected physiological functions. An FSPM consists of an architectural part (plant structure) and a process part (plant functioning). The first deals with (i) the types of organs that are initiated and the way these are connected (topology), (ii) co-ordination in organ expansion dynamics, and (iii) geometrical variables (e.g. leaf angles, leaf curvature). The process part may include any physiological or physical process that affects plant growth and development (e.g. photosynthesis, carbon allocation). This paper addresses the following questions: (i) how are FSPM constructed, and (ii) for what purposes are they useful? Static, architectural models are distinguished from dynamic models. Static models are useful in order to study the significance of plant structure, such as light distribution in the canopy, gas exchange, remote sensing, pesticide spraying studies, and interactions between plants and biotic agents. Dynamic models serve quantitatively to integrate knowledge on plant functions and morphology as modulated by environment. Applications are in the domain of plant sciences, for example the study of plant plasticity as related to changes in the red:far red ratio of light in the canopy. With increasing availability of genetic information, FSPM will play a role in the assessment of the significance towards plant performance of variation in genetic traits across environments. In many crops, growers actively manipulate plant structure. FSPM is a promising tool to explore divergent management strategies.

Functional-Structural Plant Modelling in Crop Production

Functional-structural plant models (FSPMs) describe in quantitative terms the development over time of the three-dimensional (3D) structure of plants as governed by physiological processes and affected by environmental factors. FSPMs are particularly suited to analyse problems in which the spatial structure of the plant or its canopy is an essential factor to explain, e.g., plant competition (intra-plant, inter-plant, inter-species) and the effects of plant configuration and plant manipulation (e.g., pruning and harvesting) on yield and produce quality. This book describes the philosophy of functional-structural plant modelling and several tools for making FSPMs; it outlines methods for measuring essential parameters, including those pertaining to plant structure. As FSPMs offer new opportunities to model sinksource interactions, the physiological theory and modelling approaches regarding partitioning of carbon are given specific attention. Examples of application of FSPMs include wheat modelling in the context of remote sensing and the analysis of predatorprey insect interactions on glasshouse plants. The book will be useful for scientists and advanced students interested in innovative approaches in plant and crop modelling.

Using combined measurements of gas exchange and chlorophyll fluorescence to estimate parameters of a biochemical C3 photosynthesis model: a critical appraisal and a new integrated approach applied to leaves in a wheat (Triticum aestivum) canopy

We appraised the literature and described an approach to estimate the parameters of the Farquhar, von Caemmerer and Berry model using measured CO(2) assimilation rate (A) and photosystem II (PSII) electron transport efficiency (Phi(2)). The approach uses curve fitting to data of A and Phi(2) at various levels of incident irradiance (I(inc)), intercellular CO(2) (C(i)) and O(2). Estimated parameters include day respiration (R(d)), conversion efficiency of I(inc) into linear electron transport of PSII under limiting light [kappa(2(LL))], electron transport capacity (J(max)), curvature factor (theta) for the non-rectangular hyperbolic response of electron flux to I(inc), ribulose 1.5-bisphosphate carboxylase/oxygenase (Rubisco) CO(2)/O(2) specificity (S(c/o)), Rubisco carboxylation capacity (V(cmax)), rate of triose phosphate utilization (T(p)) and mesophyll conductance (g(m)). The method is used to analyse combined gas exchange and chlorophyll fluorescence measurements on leaves of various ages and positions in wheat plants grown at two nitrogen levels. Estimated S(c/o) (25 degrees C) was 3.13 mbar microbar(-1); R(d) was lower than respiration in the dark; J(max) was lower and theta was higher at 2% than at 21% O(2); kappa(2(LL)), V(cmax), J(max) and T(p) correlated to leaf nitrogen content; and g(m) decreased with increasing C(i) and with decreasing I(inc). Based on the parameter estimates, we surmised that there was some alternative electron transport.

Simulation of wheat growth and development based on organ-level photosynthesis and assimilate allocation

Intimate relationships exist between form and function of plants, determining many processes governing their growth and development. However, in most crop simulation models that have been created to simulate plant growth and, for example, predict biomass production, plant structure has been neglected. In this study, a detailed simulation model of growth and development of spring wheat (Triticum aestivum) is presented, which integrates degree of tillering and canopy architecture with organ-level light interception, photosynthesis, and dry-matter partitioning. An existing spatially explicit 3D architectural model of wheat development was extended with routines for organ-level microclimate, photosynthesis, assimilate distribution within the plant structure according to organ demands, and organ growth and development. Outgrowth of tiller buds was made dependent on the ratio between assimilate supply and demand of the plants. Organ-level photosynthesis, biomass production, and bud outgrowth were simulated satisfactorily. However, to improve crop simulation results more efforts are needed mechanistically to model other major plant physiological processes such as nitrogen uptake and distribution, tiller death, and leaf senescence. Nevertheless, the work presented here is a significant step forwards towards a mechanistic functional-structural plant model, which integrates plant architecture with key plant processes.

Understanding shoot branching by modelling form and function

Shoot branching plays a pivotal role in the development of the aboveground plant structure. Therefore, to understand branching in relation to the environment, it is not only necessary to integrate the knowledge on mechanisms that regulate branching at multiple levels of biological organisation, but also to include plant structure explicitly. To this end, we propose the application of an established methodology called functional-structural plant modelling.

Plant neighbor detection through touching leaf tips precedes phytochrome signals

Plants in dense vegetation compete for resources, including light, and optimize their growth based on neighbor detection cues. The best studied of such behaviors is the shade-avoidance syndrome that positions leaves in optimally lit zones of a vegetation. Although proximate vegetation is known to be sensed through a reduced ratio between red and far-red light, we show here through computational modeling and manipulative experiments that leaves of the rosette species Arabidopsis thaliana first need to move upward to generate sufficient light reflection potential for subsequent occurrence and perception of a reduced red to far-red ratio. This early hyponastic leaf growth response is not induced by known neighbor detection cues under both climate chamber and natural sunlight conditions, and we identify a unique way for plants to detect future competitors through touching of leaf tips. This signal occurs before light signals and appears to be the earliest means of above-ground plant–plant signaling in horizontally growing rosette plants.

The contribution of phenotypic plasticity to complementary light capture in plant mixtures

Interspecific differences in functional traits are a key factor for explaining the positive diversity-productivity relationship in plant communities. However, the role of intraspecific variation attributable to phenotypic plasticity in diversity-productivity relationships has largely been overlooked. By taking a wheat (Triticum aestivum)-maize (Zea mays) intercrop as an elementary example of mixed vegetation, we show that plasticity in plant traits is an important factor contributing to complementary light capture in species mixtures. We conceptually separated net biodiversity effect into the effect attributable to interspecific trait differences and species distribution (community structure effect), and the effect attributable to phenotypic plasticity. Using a novel plant architectural modelling approach, whole-vegetation light capture was simulated for scenarios with and without plasticity based on empirical plant trait data. Light capture was 23% higher in the intercrop with plasticity than the expected value from monocultures, of which 36% was attributable to community structure and 64% was attributable to plasticity. For wheat, plasticity in tillering was the main reason for increased light capture, whereas for intercropped maize, plasticity induced a major reduction in light capture. The results illustrate the potential of plasticity for enhancing resource acquisition in mixed stands, and indicate the importance of plasticity in the performance of species-diverse plant communities.

Early competition shapes maize whole-plant development in mixed stands

Mixed cropping is practised widely in developing countries and is gaining increasing interest for sustainable agriculture in developed countries. Plants in intercrops grow differently from plants in single crops, due to interspecific plant interactions, but adaptive plant morphological responses to competition in mixed stands have not been studied in detail. Here the maize (Zea mays) response to mixed cultivation with wheat (Triticum aestivum) is described. Evidence is provided that early responses of maize to the modified light environment in mixed stands propagate throughout maize development, resulting in different phenotypes compared with pure stands. Photosynthetically active radiation (PAR), red:far-red ratio (R:FR), leaf development, and final organ sizes of maize grown in three cultivation systems were compared: pure maize, an intercrop with a small distance (25cm) between maize and wheat plants, and an intercop with a large distance (44cm) between the maize and the wheat. Compared with maize in pure stands, maize in the mixed stands had lower leaf and collar appearance rates, increased blade and sheath lengths at low ranks and smaller sizes at high ranks, increased blade elongation duration, and decreased R:FR and PAR at the plant base during early development. Effects were strongest in the treatment with a short distance between wheat and maize strips. The data suggest a feedback between leaf initiation and leaf emergence at the plant level and coordination between blade and sheath growth at the phytomer level. A conceptual model, based on coordination rules, is proposed to explain the development of the maize plant in pure and mixed stands.

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 years 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 m(2) 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.

Neighbor detection at the leaf tip adaptively regulates upward leaf movement through spatial auxin dynamics

Significance Plants often grow at high plant densities where they risk being shaded by surrounding plants. Neighbors are detected through changes in the composition of reflected light, and plants respond to such changes by growing their photosynthetic organs away from their competitors. This research shows that Arabidopsis plants first detect these light cues in the tips of their leaves and that this information then is transmitted through the mobile plant hormone auxin to the very base of the organ, where it induces an upward leaf movement response. 3D computational models show that this spatial separation in signal detection and response is adaptive for plant performance in dense stands. Vegetation stands have a heterogeneous distribution of light quality, including the red/far-red light ratio (R/FR) that informs plants about proximity of neighbors. Adequate responses to changes in R/FR are important for competitive success. How the detection and response to R/FR are spatially linked and how this spatial coordination between detection and response affects plant performance remains unresolved. We show in Arabidopsis thaliana and Brassica nigra that localized FR enrichment at the lamina tip induces upward leaf movement (hyponasty) from the petiole base. Using a combination of organ-level transcriptome analysis, molecular reporters, and physiology, we show that PIF-dependent spatial auxin dynamics are key to this remote response to localized FR enrichment. Using computational 3D modeling, we show that remote signaling of R/FR for hyponasty has an adaptive advantage over local signaling in the petiole, because it optimizes the timing of leaf movement in response to neighbors and prevents hyponasty caused by self-shading.