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

Unravelling drivers of local adaptation through evolutionary functional-structural plant modelling

Local adaptation to contrasting environmental conditions along environmental gradients is a widespread phenomenon in plant populations, yet we lack a mechanistic understanding of how individual agents of selection contribute to this evolutionary process. Here, we developed a novel evolutionary functional-structural plant (E-FSP) model that recreates local adaptation of virtual plants along an environmental gradient. First, we validate the model by testing if it can reproduce two elevational ecotypes of Dianthus carthusianorum occurring in the Swiss Alps. Second, we use the E-FSP model to disentangle the relative contribution of abiotic (temperature) and biotic (competition and pollination) selection pressures to elevational adaptation in D. carthusianorum. Our results suggest that elevational adaptation in D. carthusianorum is predominantly driven by the abiotic environment. The model reproduced the qualitative differences between the elevational ecotypes in two phenological (germination and flowering time) and one morphological trait (stalk height), as well as qualitative differences in four performance variables that emerge from G × E interactions (flowering time, number of stalks, rosette area and seed production). Our approach shows how E-FSP models incorporating physiological, ecological and evolutionary mechanisms can be used in combination with experiments to examine hypotheses about patterns of adaptation observed in the field.

Root plasticity improves maize nitrogen use when nitrogen is limiting: an analysis using 3D plant modelling

Plant phenotypic plasticity plays an important role in nitrogen (N) acquisition and use under nitrogen-limited conditions. However, this role has never been quantified as a function of N availability, leaving it unclear whether plastic responses should be considered as potential targets for selection. A combined modelling and experimentation approach was adopted to quantify the role of plasticity in N uptake and plant yield. Based on a greenhouse experiment we considered plasticity in two maize (Zea mays) traits: root-to-leaf biomass allocation ratio and emergence rate of axial roots. In a simulation experiment we individually enabled or disabled both plastic responses for maize stands grown across six N levels. Both plastic responses contributed to maintaining a higher N uptake, and plant productivity as N availability declined compared with stands in which plastic responses were disabled. We conclude that plastic responses quantified in this study may be a potential target trait in breeding programs for greater N uptake across N levels while it may only be important for the internal use of N under N-limited conditions in maize. Given the complexity of breeding for plastic responses, an a priori model analysis is useful to identify which plastic traits to target for enhanced plant performance.

Crop/Plant Modeling Supports Plant Breeding: II. Guidance of Functional Plant Phenotyping for Trait Discovery

Observable morphological traits are widely employed in plant phenotyping for breeding use, which are often the external phenotypes driven by a chain of functional actions in plants. Identifying and phenotyping inherently functional traits for crop improvement toward high yields or adaptation to harsh environments remains a major challenge. Prediction of whole-plant performance in functional-structural plant models (FSPMs) is driven by plant growth algorithms based on organ scale wrapped up with micro-environments. In particular, the models are flexible for scaling down or up through specific functions at the organ nexus, allowing the prediction of crop system behaviors from the genome to the field. As such, by virtue of FSPMs, model parameters that determine organogenesis, development, biomass production, allocation, and morphogenesis from a molecular to the whole plant level can be profiled systematically and made readily available for phenotyping. FSPMs can provide rich functional traits representing biological regulatory mechanisms at various scales in a dynamic system, e.g., Rubisco carboxylation rate, mesophyll conductance, specific leaf nitrogen, radiation use efficiency, and source-sink ratio apart from morphological traits. High-throughput phenotyping such traits is also discussed, which provides an unprecedented opportunity to evolve FSPMs. This will accelerate the co-evolution of FSPMs and plant phenomics, and thus improving breeding efficiency. To expand the great promise of FSPMs in crop science, FSPMs still need more effort in multiscale, mechanistic, reproductive organ, and root system modeling. In summary, this study demonstrates that FSPMs are invaluable tools in guiding functional trait phenotyping at various scales and can thus provide abundant functional targets for phenotyping toward crop improvement.

Use of 3D modeling to refine predictions of canopy light utilization: A comparative study on canopy photosynthesis models with different dimensions

Canopy photosynthesis integrates leaf functional and structural traits in space and time and correlates positively with yield formation. Many models with different levels of architectural details ranging from zero-dimensional (0D) to three-dimensional (3D) have been developed to simulate canopy light interception and photosynthesis. Based on these models, a crop growth model can be used to assess crop yield in response to genetic improvement, optimized practices, and environmental change. However, to what extent do architectural details influence light interception, photosynthetic production, and grain yield remains unknown. Here, we show that a crop growth model with high-resolution upscaling approach in space reduces the departure of predicted yield from actual yield and refines the simulation of canopy photosynthetic production. We found crop yield predictions decreased by 12.0-48.5% with increasing the resolution of light simulation, suggesting that a crop growth model without architectural details may result in a considerable departure from the actual photosynthetic production. A dramatic difference in light interception and photosynthetic production of canopy between cultivars was captured by the proposed 3D model rather than the 0D, 1D, and 2D models. Furthermore, we found that the overestimation of crop yield by the 0D model is caused by the overestimation of canopy photosynthetically active radiation (PAR) interception and the RUE and that by the 1D and 2D model is caused by the overestimated canopy photosynthesis rate that is possibly related to higher predicted PAR and fraction of sunlit leaves. Overall, this study confirms the necessity of taking detailed architecture traits into consideration when evaluating the strategies of genetic improvement and canopy configuration in improving crop yield by crop modeling.

CRISPR/Cas9-mediated mutagenesis of VvbZIP36 promotes anthocyanin accumulation in grapevine (Vitis vinifera)

Anthocyanins are plant secondary metabolites that have a variety of biological functions, including pigmentation. The accumulation of anthocyanins is regulated by both transcriptional activators and repressors. Studies have shown that the bZIP family act primarily as positive regulators of anthocyanin biosynthesis, but there are few reports of negative regulation. Here, we report that a grapevine (Vitis vinifera) bZIP gene from group K, VvbZIP36, acts as a negative regulator of anthocyanin biosynthesis. Knocking-out one allele of VvbZIP36 in grapevine utilizing the CRISPR/Cas9 technology promoted anthocyanin accumulation. Correlation analysis of transcriptome and metabolome data showed that, compared with wild type, a range of anthocyanin biosynthesis genes were activated in VvbZIP36 mutant plants, resulting in the accumulation of related metabolites, including naringenin chalcone, naringenin, dihydroflavonols and cyanidin-3-O-glucoside. Furthermore, the synthesis of stilbenes (α-viniferin), lignans and some flavonols (including quercetin-3-O-rhamnoside, kaempferol-3-O-rhamnoside and kaempferol-7-O-rhamnoside) was significantly inhibited and several genes linked to these metabolism, were down-regulated in the mutant plants. In summary, our results demonstrate that VvbZIP36, as a negative regulator of anthocyanin biosynthesis, plays a role in balancing the synthesis of stilbenes (α-viniferin), lignans, flavonols and anthocyanins.

Analyzing the Impact of Greenhouse Planting Strategy and Plant Architecture on Tomato Plant Physiology and Estimated Dry Matter

Determine the level of significance of planting strategy and plant architecture and how they affect plant physiology and dry matter accumulation within greenhouses is essential to actual greenhouse plant management and breeding. We thus analyzed four planting strategies (plant spacing, furrow distance, row orientation, planting pattern) and eight different plant architectural traits (internode length, leaf azimuth angle, leaf elevation angle, leaf length, leaflet curve, leaflet elevation, leaflet number/area ratio, leaflet length/width ratio) with the same plant leaf area using a formerly developed functional-structural model for a Chinese Liaoshen-solar greenhouse and tomato plant, which used to simulate the plant physiology of light interception, temperature, stomatal conductance, photosynthesis, and dry matter. Our study led to the conclusion that the planting strategies have a more significant impact overall on plant radiation, temperature, photosynthesis, and dry matter compared to plant architecture changes. According to our findings, increasing the plant spacing will have the most significant impact to increase light interception. E-W orientation has better total light interception but yet weaker light uniformity. Changes in planting patterns have limited influence on the overall canopy physiology. Increasing the plant leaflet area by leaflet N/A ratio from what we could observe for a rose the total dry matter by 6.6%, which is significantly better than all the other plant architecture traits. An ideal tomato plant architecture which combined all the above optimal architectural traits was also designed to provide guidance on phenotypic traits selection of breeding process. The combined analysis approach described herein established the causal relationship between investigated traits, which could directly apply to provide management and breeding insights on other plant species with different solar greenhouse structures.

Determination of the Optimal Orientation of Chinese Solar Greenhouses Using 3D Light Environment Simulations

With the continuous use of resources, solar energy is expected to be the most used sustainable energy. To improve the solar energy efficiency in Chinese Solar Greenhouses (CSG), the effect of CSG orientation on intercepted solar radiation was systematically studied. By using a 3D CSG model and a detailed crop canopy model, the light environment within CSG was optimized. Taking the most widely used Liao-Shen type Chinese solar greenhouse (CSG-LS) as the prototype, the simulation was fully verified. The intercepted solar radiation of the maintenance structures and crops was used as the evaluation index. The results showed that the highest amount of solar radiation intercepted by the maintenance structures occurred in the CSG orientations of 4–6° south to west (S-W) in 36.8° N and 38° N areas, 8–10° S-W in 41.8° N areas, and 2–4° south to east (S-E) in 43.6° N areas. The solar radiation intercepted by the crop canopy displayed the highest value at an orientation of 2–4° S-W in 36.8° N, 38° N, 43.6° N areas, and 4–6° S-W in the 41.8° N area. Furthermore, the proposed model could provide scientific guidance for greenhouse crop modelling.

Functional-Structural Plant Models Mission in Advancing Crop Science: Opportunities and Prospects

Functional-structural plant models (FSPMs) have been evolving for over 2 decades and their future development, to some extent, depends on the value of potential applications in crop science. To date, stabilizing crop production by identifying valuable traits for novel cultivars adapted to adverse environments is topical in crop science. Thus, this study will examine how FSPMs are able to address new challenges in crop science for sustainable crop production. FSPMs developed to simulate organogenesis, morphogenesis, and physiological activities under various environments and are amenable to downscale to the tissue, cellular, and molecular level or upscale to the whole plant and ecological level. In a modeling framework with independent and interactive modules, advanced algorithms provide morphophysiological details at various scales. FSPMs are shown to be able to: (i) provide crop ideotypes efficiently for optimizing the resource distribution and use for greater productivity and less disease risk, (ii) guide molecular design breeding via linking molecular basis to plant phenotypes as well as enrich crop models with an additional architectural dimension to assist breeding, and (iii) interact with plant phenotyping for molecular breeding in embracing three-dimensional (3D) architectural traits. This study illustrates that FSPMs have great prospects in speeding up precision breeding for specific environments due to the capacity for guiding and integrating ideotypes, phenotyping, molecular design, and linking molecular basis to target phenotypes. Consequently, the promising great applications of FSPMs in crop science will, in turn, accelerate their evolution and vice versa.

Wheat morpho-physiological traits and radiation use efficiency under interactive effects of warming and tillage management

Understanding the interactive effects of different warming levels and tillage managements on crop morphological and physiological traits and radiation use efficiency (RUE) is essential for breeding climate-resilient cultivars. Here, we conducted temperature free-air controlled enhancement (T-FACE) experiments on winter wheat during two growth seasons in the North China Plain. The experiments consisted of three warming treatments and two tillage treatments (CT: conventional tillage and NT: no-tillage). In the normal season, warming had significant positive effects on major morphological and physiological traits and increased significantly RUE of yield (RUE_Y ) and biomass (RUE_DM ) by 13.3 and 11.3%, 19.3 and 12.4%, 42.3 and 43.7%, respectively, under the treatments of CTT1, CTT2 and NTT1 relative to the control (CTN, NTN). By contrast, in the warmer season, warming had negative effects on leaf width, light extinction coefficient, light-saturated net photosynthetic rate, aboveground, stems and spike biomass and RUE from anthesis to maturity, and consequently grain yield under conventional tillage, but positive effects under no-tillage. Our findings bring new insights into the mechanisms on the interactive effects of warming and tillage treatments on wheat growth and productivity; provide valuable information on crop ideotypic traits for breeding climate-resilient crop cultivars.

Estimating the contribution of plant traits to light partitioning in simultaneous maize/soybean intercropping

Spatial configuration and plant phenotypic plasticity contribute to increased light capture in relay intercropping, but there is little information on whether these factors also increase light capture in simultaneous intercropping. We developed and validated a three-dimensional functional-structural plant model to simulate light capture in maize and soybean sole crops and intercrop scenarios, using species traits observed in sole crops and intercrops. The intercrop maize phenotype had 2% greater light capture than the sole crop phenotype in a pure stand. The soybean intercrop phenotype had 5-10% lower light capture than the sole crop phenotype in a pure stand. The intercrop configuration increased the light capture of maize by 29% and reduced the light capture of soybean by 42%, compared with the light capture expected from sole crops. However, intercrop configuration only marginally affected total light capture by the intercrop system (+1%). Testing of individual soybean plant traits revealed that plasticity in leaf dimensions was the main reason for differences in light capture by soybean in simulated sole crops and intercrops. The results of this study illustrate a major shift of light capture from shorter species (soybean) to the taller component (maize) in a simultaneous strip intercrop. Plastic plant traits modulate this overall effect, but only marginally.

Light from below matters: Quantifying the consequences of responses to far-red light reflected upwards for plant performance in heterogeneous canopies

In vegetation stands, plants receive red to far-red ratio (R:FR) signals of varying strength from all directions. However, plant responses to variations in R:FR reflected from below have been largely ignored despite their potential consequences for plant performance. Using a heterogeneous rose canopy, which consists of bent shoots down in the canopy and vertically growing upright shoots, we quantified upward far-red reflection by bent shoots and its consequences for upright shoot architecture. With a three-dimensional plant model, we assessed consequences of responses to R:FR from below for plant photosynthesis. Bent shoots reflected substantially more far-red than red light, causing reduced R:FR in light reflected upwards. Leaf inclination angles increased in upright shoots which received low R:FR reflected from below. The increased leaf angle led to an increase in simulated plant photosynthesis only when this low R:FR was reflected off their own bent shoots and not when it reflected off neighbour bent shoots. We conclude that plant response to R:FR from below is an under-explored phenomenon which may have contrasting consequences for plant performance depending on the type of vegetation or crop system. The responses are beneficial for performance only when R:FR is reflected by lower foliage of the same plants.

Disentangling the effects of photosynthetically active radiation and red to far-red ratio on plant photosynthesis under canopy shading: a simulation study using a functional-structural plant model

BACKGROUND AND AIMS

Shading by an overhead canopy (i.e. canopy shading) entails simultaneous changes in both photosynthetically active radiation (PAR) and red to far-red ratio (R:FR). As plant responses to PAR (e.g. changes in leaf photosynthesis) are different from responses to R:FR (e.g. changes in plant architecture), and these responses occur at both organ and plant levels, understanding plant photosynthesis responses to canopy shading needs separate analysis of responses to reductions in PAR and R:FR at different levels.

METHODS

In a glasshouse experiment we subjected plants of woody perennial rose (Rosa hybrida) to different light treatments, and so separately quantified the effects of reductions in PAR and R:FR on leaf photosynthetic traits and plant architectural traits. Using a functional-structural plant model, we separately quantified the effects of responses in these traits on plant photosynthesis, and evaluated the relative importance of changes of individual traits for plant photosynthesis under mild and heavy shading caused by virtual overhead canopies.

KEY RESULTS

Model simulations showed that the individual trait responses to canopy shading could have positive and negative effects on plant photosynthesis. Under mild canopy shading, trait responses to reduced R:FR on photosynthesis were generally negative and with a larger magnitude than effects of responses to reduced PAR. Conversely, under heavy canopy shading, the positive effects of trait responses to reduced PAR became dominant. The combined effects of low-R:FR responses and low-PAR responses on plant photosynthesis were not equal to the sum of the separate effects, indicating interactions between individual trait responses.

CONCLUSIONS

Our simulation results indicate that under canopy shading, the relative importance of plant responses to PAR and R:FR for plant photosynthesis changes with shade levels. This suggests that the adaptive significance of plant plasticity responses to one shading factor depends on plant responses to the other.

An overview of agent-based models in plant biology and ecology

Agent-based modelling (ABM) has become an established methodology in many areas of biology, ranging from the cellular to the ecological population and community levels. In plant science, two different scales have predominated in their use of ABM. One is the scale of populations and communities, through the modelling of collections of agents representing individual plants, interacting with each other and with the environment. The other is the scale of the individual plant, through the modelling, by functional-structural plant models (FSPMs), of agents representing plant building blocks, or metamers, to describe the development of plant architecture and functions within individual plants. The purpose of this review is to show key results and parallels in ABM for growth, mortality, carbon allocation, competition and reproduction across the scales from the plant organ to populations and communities on a range of spatial scales to the whole landscape. Several areas of application of ABMs are reviewed, showing that some issues are addressed by both population-level ABMs and FSPMs. Continued increase in the relevance of ABM to environmental science and management will be helped by greater integration of ABMs across these two scales.

Internal trophic pressure, a regulator of plant development? Insights from a stochastic functional-structural plant growth model applied to Coffea trees

BACKGROUND AND AIMS

Using internal trophic pressure as a regulating variable to model the complex interaction loops between organogenesis, production of assimilates and partitioning in functional-structural models of plant growth has attracted increasing interest in recent years. However, this approach is hampered by the fact that internal trophic pressure is a non-measurable quantity that can be assessed only through model parametric estimation, for which the methodology is not straightforward, especially when the model is stochastic.

METHODS

A stochastic GreenLab model of plant growth (called 'GL4') is developed with a feedback effect of internal trophic competition, represented by the ratio of biomass supply to demand (Q/D), on organogenesis. A methodology for its parameter estimation is presented and applied to a dataset of 15 two-year-old Coffea canephora trees. Based on the fitting results, variations in Q/D are reconstructed and analysed in relation to the estimated variations in organogenesis parameters.

KEY RESULTS

Our stochastic retroactive model was able to simulate realistically the progressive set-up of young plant architecture and the branch pruning effect. Parameter estimation using real data for Coffea trees provided access to the internal trophic dynamics. These dynamics correlated with the organogenesis probabilities during the establishment phase.

CONCLUSIONS

The model can satisfactorily reproduce the measured data, thus opening up promising avenues for further applying this original procedure to other experimental data. The framework developed can serve as a model-based toolkit to reconstruct the hidden internal trophic dynamics of plant growth.

Contrasting phenotypes emerging from stable rules: A model based on self-regulated control loops captures the dynamics of shoot extension in contrasting maize phenotypes

BACKGROUND AND AIMS

The dynamics of plant architecture is a central aspect of plant and crop models. Most models assume that whole shoot development is orchestrated by the leaf appearance rate, which follows a thermal time schedule. However, leaf appearance actually results from leaf extension and taking it as an input hampers our ability to understand shoot construction. The objective of the present study was to assess a modelling framework for grasses, in which the emergence of leaves and other organs is explicitly calculated as a result of their extension.

METHODS

The approach builds on a previous model, which uses a set of rules co-ordinating the timing of development within and between phytomers. We first assessed rule validity for four experimental datasets, including different cultivars, planting densities and environments, and accordingly revised the equations driving the extension of the upper leaves and of internodes. We then fitted model parameters for each dataset and evaluated the ability to simulate the measured phenotypes across time. Finally, we carried out a sensitivity analysis to identify the parameters that had the greatest impact and to investigate model behaviour.

KEY RESULTS

The modified version of the model simulated correctly the contrasting maize phenotypes. Co-ordination rules accounted for the observations in all studied cultivars. Factors with major impact on model output included extension rates, the time of tassel initiation and initial conditions. A large diversity of phenotypes could be simulated.

CONCLUSIONS

This work provides direct experimental evidence for co-ordination rules and illustrates the capacity of the model to represent contrasting phenotypes. These rules play an important role in patterning shoot architecture and some of them need to be assessed further, considering contrasting growth conditions. To make the model more predictive, several parameters could be considered in the future as internal variables driven by plant status.

Quantifying the contribution of bent shoots to plant photosynthesis and biomass production of flower shoots in rose (Rosa hybrida) using a functional-structural plant model

BACKGROUND AND AIMS

The success of using bent shoots in cut-rose (Rosa hybrida) production to improve flower shoot quality has been attributed to bent shoots capturing more light and thus providing more assimilates for flower shoot growth. We aimed at quantifying this contribution of photosynthesis by bent shoots to flower shoot growth.

METHODS

Rose plants were grown with four upright flower shoots and with no, one or three bent shoots per plant. Plant architectural traits, leaf photosynthetic parameters and organ dry weight were measured. A functional-structural plant (FSP) model of rose was used to calculate photosynthesis of upright shoots and bent shoots separately, taking into account the heterogeneous canopy structure of these plants.

KEY RESULTS

Bent shoots contributed to 43-53 % of total assimilated CO2 by the plant. Plant photosynthesis increased by 73 and 117 % in plants with, respectively, one and three bent shoots compared with plants without bent shoots. Upright shoot photosynthesis was not significantly affected by the presence of bent shoots. However, upright shoot dry weight increased by 35 and 59 % in plants with, respectively, one and three bent shoots compared with plants without bent shoots. The increased upright shoot dry weight was entirely due to the contribution of extra photosynthesis by bent shoots, as this was the only source that could induce differences in upright shoot growth apart from their own photosynthesis. At least 47-51 % of the photosynthesis by bent shoots was translocated to upright shoots to support their biomass increase.

CONCLUSIONS

Based on model simulations, we conclude that the positive effect of shoot bending on flower shoot growth and quality in cut-rose production system can almost entirely be attributed to assimilate supply from bent shoots. FSP modelling is a useful tool to quantify the contributions of photosynthesis by different parts of heterogeneous canopies.

Two decades of functional-structural plant modelling: now addressing fundamental questions in systems biology and predictive ecology

BACKGROUND

Functional-structural plant models (FSPMs) explore and integrate relationships between a plant's structure and processes that underlie its growth and development. In the last 20 years, scientists interested in functional-structural plant modelling have expanded greatly the range of topics covered and now handle dynamical models of growth and development occurring from the microscopic scale, and involving cell division in plant meristems, to the macroscopic scales of whole plants and plant communities.

SCOPE

The FSPM approach occupies a central position in plant science; it is at the crossroads of fundamental questions in systems biology and predictive ecology. This special issue of Annals of Botany features selected papers on critical areas covered by FSPMs and examples of comprehensive models that are used to solve theoretical and applied questions, ranging from developmental biology to plant phenotyping and management of plants for agronomic purposes. Altogether, they offer an opportunity to assess the progress, gaps and bottlenecks along the research path originally foreseen for FSPMs two decades ago. This review also allows discussion of current challenges of FSPMs regarding (1) integration of multidisciplinary knowledge, (2) methods for handling complex models, (3) standards to achieve interoperability and greater genericity and (4) understanding of plant functioning across scales.

CONCLUSIONS

This approach has demonstrated considerable progress, but has yet to reach its full potential in terms of integration and heuristic knowledge production. The research agenda of functional-structural plant modellers in the coming years should place a greater emphasis on explaining robust emergent patterns, and on the causes of possible deviation from it. Modelling such patterns could indeed fuel both generic integration across scales and transdisciplinary transfer. In particular, it could be beneficial to emergent fields of research such as model-assisted phenotyping and predictive ecology in managed ecosystems.

Turgor-driven plant growth applied in a soybean functional-structural plant model

BACKGROUND AND AIMS

Turgor pressure within a plant cell represents the key to the mechanistical descriptiion of plant growth, combining the effects of both water and carbon availability. The high level of spatio-temporal variation and diurnal dynamics in turgor pressure within a single plant make it a challenge to model these on the fine spatial scale required for functional-structural plant models (FSPMs). A conceptual model for turgor-driven growth in FSPMs has been established previously, but its practical use has not yet been explored.

METHODS

A turgor-driven growth model was incorporated in a newly established FSPM for soybean. The FSPM simulates dynamics in photosynthesis, transpiration and turgor pressure in direct relation to plant growth. Comparisons of simulations with field data were used to evaluate the potential and shortcomings of the modelling approach.

KEY RESULTS

Model simulations revealed the need to include an initial seed carbon contribution, a more realistic sink function, an estimation of respiration, and the distinction between osmotic and structural sugars, in order to achieve a realistic model of plant growth. However, differences between simulations and observations remained in individual organ growth patterns and under different environmental conditions. This exposed the need to further investigate the assumptions of developmental and environmental (in)sensitivity of the parameters, which represent physiological and biophysical organ properties in the model, in future research.

CONCLUSIONS

The model in its current form is primarily a diagnostic tool, to better understand and model the behaviour of water relations on the scale of individual plant organs throughout the plant life cycle. Potential future applications include its use as a phenotyping tool to capture differences in plant performance between genotypes and growing environments in terms of specific plant characteristics. Additionally, focused experiments can be used to further improve the model mechanisms to lead to better predictive FSPMs, including scenarios of water deficit.

Identification of lncRNAs involved in wheat tillering development in two pairs of near-isogenic lines

Emerging evidence demonstrates that lncRNAs participate in various developmental processes in plants via post-transcription regulation. However, few lncRNAs have been identified as regulators of tiller development in wheat (Triticum aestivum L.). In this study, high-throughput ribosomal depleted RNA sequencing was performed on the tillering nodes of two pairs of near-isogenic lines that differed only in the tillering trait. We identified 5399 lncRNA transcripts using bioinformational analyses. KEGG pathway analysis revealed 74 common differentially expressed lncRNAs substantially enriched in photosynthesis-related, phenylpropanoid biosynthesis, phosphatidylinositol signaling, brassinosteroid biosynthesis, zeatin biosynthesis, and carotenoid biosynthesis pathways. Detailed functional annotations of target genes were used to identify 27 tillering-associated lncRNAs. Among these, 10 were in photosynthesis-related pathways; 15 were in secondary metabolite pathways; and 8 were in plant hormone pathways, with 6 enriched in two kinds of pathways. These findings contribute to identifying tillering-associated lncRNAs in wheat and enable further investigation into the functions and roles of key candidate lncRNAs, and more experimental evidence was also needed if breeders wanted to utilize these candidate lncRNAs in wheat crop yield improvement in the future.

Light Regulation of Axillary Bud Outgrowth Along Plant Axes: An Overview of the Roles of Sugars and Hormones

Apical dominance, the process by which the growing apical zone of the shoot inhibits bud outgrowth, involves an intricate network of several signals in the shoot. Auxin originating from plant apical region inhibits bud outgrowth indirectly. This inhibition is in particular mediated by cytokinins and strigolactones, which move from the stem to the bud and that respectively stimulate and repress bud outgrowth. The action of this hormonal network is itself modulated by sugar levels as competition for sugars, caused by the growing apical sugar sink, may deprive buds from sugars and prevents bud outgrowth partly by their signaling role. In this review, we analyze recent findings on the interaction between light, in terms of quantity and quality, and apical dominance regulation. Depending on growth conditions, light may trigger different pathways of the apical dominance regulatory network. Studies pinpoint to the key role of shoot-located cytokinin synthesis for light intensity and abscisic acid synthesis in the bud for R:FR in the regulation of bud outgrowth by light. Our analysis provides three major research lines to get a more comprehensive understanding of light effects on bud outgrowth. This would undoubtedly benefit from the use of computer modeling associated with experimental observations to deal with a regulatory system that involves several interacting signals, feedbacks, and quantitative effects.

Variation in plastic responses to light results from selection in different competitive environments-A game theoretical approach using virtual plants

Phenotypic plasticity is a vital strategy for plants to deal with changing conditions by inducing phenotypes favourable in different environments. Understanding how natural selection acts on variation in phenotypic plasticity in plants is therefore a central question in ecology, but is often ignored in modelling studies. Here we present a new modelling approach that allows for the analysis of selection for variation in phenotypic plasticity as a response strategy. We assess selection for shade avoidance strategies of Arabidopsis thaliana in response to future neighbour shading signalled through a decrease in red:far-red (R:FR) ratio. For this, we used a spatially explicit 3D virtual plant model that simulates individual Arabidopsis plants competing for light in different planting densities. Plant structure and growth were determined by the organ-specific interactions with the light environment created by the vegetation structure itself. Shade avoidance plastic responses were defined by a plastic response curve relating petiole elongation and lamina growth to R:FR perceived locally. Different plasticity strategies were represented by different shapes of the response curve that expressed different levels of R:FR sensitivity. Our analyses show that the shape of the selected shade avoidance strategy varies with planting density. At higher planting densities, more sensitive response curves are selected for than at lower densities. In addition, the balance between lamina and petiole responses influences the sensitivity of the response curves selected for. Combining computational virtual plant modelling with a game theoretical analysis represents a new step towards analysing how natural selection could have acted upon variation in shade avoidance as a response strategy, which can be linked to genetic variation and underlying physiological processes.

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

BACKGROUND AND AIMS

Branching is a main morphogenetic process involved in the adaptation of plants to the environment. In grasses, tillering is divided into three phases: tiller emergence, cessation of tillering and tiller regression. Understanding and prediction of the tillering process is a major challenge to better control cereal yields. In this paper, we present and evaluate WALTer, an individual-based model of wheat built on simple self-adaptive rules for predicting the tillering dynamics at contrasting sowing densities.

METHODS

WALTer simulates the three-dimensional (3-D) development of the aerial architecture of winter wheat. Tillering was modelled using two main hypotheses: (H1) a plant ceases to initiate new tillers when a critical Green Area Index (GAIc) is reached, and (H2) the regression of a tiller occurs if its interception of light is below a threshold (PARt). The development of vegetative organs follows descriptive rules adapted from the literature. A sensitivity analysis was performed to evaluate the impact of each parameter on tillering and GAI dynamics. WALTer was parameterized and evaluated using an initial dataset providing an extensive description of GAI dynamics, and another dataset describing tillering dynamics under a wide range of sowing densities.

KEY RESULTS

Sensitivity analysis indicated the predominant importance of GAIc and PARt. Tillering and GAI dynamics of expt 1 were well fit by WALTer. Once calibrated based on the agronomic density of expt 2, tillering parameters allowed an adequate prediction of tillering dynamics at contrasting sowing densities.

CONCLUSIONS

Using simple rules and a small number of parameters, WALTer efficiently simulated the wheat tillering dynamics observed at contrasting densities in experimental data. These results show that the definition of a critical GAI and a threshold of PAR is a relevant way to represent, respectively, cessation of tillering and tiller regression under competition for light.

Understanding and optimizing species mixtures using functional-structural plant modelling

Plant species mixtures improve productivity over monocultures by exploiting species complementarities for resource capture in time and space. Complementarity results in part from competition avoidance responses that maximize resource capture and growth of individual plants. Individual organs accommodate to local resource levels, e.g. with regard to nitrogen content and photosynthetic capacity or by size (e.g. shade avoidance). As a result, the resource acquisition in time and space is improved and performance of the community as a whole is increased. Modelling is needed to unravel the primary drivers and subsequent dynamics of complementary growth responses in mixtures. Here, we advocate using functional-structural plant (FSP) modelling to analyse the functioning of plant mixtures. In FSP modelling, crop performance is a result of the behaviour of the individual plants interacting through competitive and complementary resource acquisition. FSP models can integrate the interactions between structural and physiological plant responses to the local resource availability and strength of competition, which drive resource capture and growth of individuals in species mixtures. FSP models have the potential to accelerate mixed-species plant research, and thus support the development of knowledge that is needed to promote the use of mixtures towards sustainably increasing crop yields at acceptable input levels.

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

BACKGROUND AND AIMS

Because functional-structural plant models (FSPMs) take plant architecture explicitly into consideration, they constitute a promising approach for unravelling plant-plant interactions in complex canopies. However, existing FSPMs mainly address competition for light. The aim of the present work was to develop a comprehensive FSPM accounting for the interactions between plant architecture, environmental factors and the metabolism of carbon (C) and nitrogen (N).

METHODS

We developed an original FSPM by coupling models of (1) 3-D wheat architecture, (2) light distribution within canopies and (3) C and N metabolism. Model behaviour was evaluated by simulating the functioning of theoretical canopies consisting of wheat plants of contrasting leaf inclination, arranged in pure and mixed stands and considering four culm densities and three sky conditions.

KEY RESULTS

As an emergent property of the detailed description of metabolism, the model predicted a linear relationship between absorbed light and C assimilation, and a curvilinear relationship between grain mass and C assimilation, applying to both pure stands and each component of mixtures. Over the whole post-anthesis period, planophile plants tended to absorb more light than erectophile plants, resulting in a slightly higher grain mass. This difference was enhanced at low plant density and in mixtures, where the erectophile behaviour resulted in a loss of competitiveness.

CONCLUSION

The present work demonstrates that FSPMs provide a framework allowing the analysis of complex canopies such as studying the impact of particular plant traits, which would hardly be feasible experimentally. The present FSPM can help in interpreting complex interactions by providing access to critical variables such as resource acquisition and allocation, internal metabolic concentrations, leaf life span and grain filling. Simulations were based on canopies identically initialized at flowering; extending the model to the whole cycle is thus required so that all consequences of a trait can be evaluated.

An Accurate Skeleton Extraction Approach From 3D Point Clouds of Maize Plants

Accurate and high-throughput determination of plant morphological traits is essential for phenotyping studies. Nowadays, there are many approaches to acquire high-quality three-dimensional (3D) point clouds of plants. However, it is difficult to estimate phenotyping parameters accurately of the whole growth stages of maize plants using these 3D point clouds. In this paper, an accurate skeleton extraction approach was proposed to bridge the gap between 3D point cloud and phenotyping traits estimation of maize plants. The algorithm first uses point cloud clustering and color difference denoising to reduce the noise of the input point clouds. Next, the Laplacian contraction algorithm is applied to shrink the points. Then the key points representing the skeleton of the plant are selected through adaptive sampling, and neighboring points are connected to form a plant skeleton composed of semantic organs. Finally, deviation skeleton points to the input point cloud are calibrated by building a step forward local coordinate along the tangent direction of the original points. The proposed approach successfully generates accurately extracted skeleton from 3D point cloud and helps to estimate phenotyping parameters with high precision of maize plants. Experimental verification of the skeleton extraction process, tested using three cultivars and different growth stages maize, demonstrates that the extracted matches the input point cloud well. Compared with 3D digitizing data-derived morphological parameters, the NRMSE of leaf length, leaf inclination angle, leaf top length, leaf azimuthal angle, leaf growth height, and plant height, estimated using the extracted plant skeleton, are 5.27, 8.37, 5.12, 4.42, 1.53, and 0.83%, respectively, which could meet the needs of phenotyping analysis. The time required to process a single maize plant is below 100 s. The proposed approach may play an important role in further maize research and applications, such as genotype-to-phenotype study, geometric reconstruction, functional structural maize modeling, and dynamic growth animation.

Ecological significance of light quality in optimizing plant defence

Plants balance the allocation of resources between growth and defence to optimize fitness in a competitive environment. Perception of neighbour-detection cues, such as a low ratio of red to far-red (R:FR) radiation, activates a suite of shade-avoidance responses that include stem elongation and upward leaf movement, whilst simultaneously downregulating defence. This downregulation is hypothesized to benefit the plant either by mediating the growth-defence balance in favour of growth in high plant densities or, alternatively, by mediating defence of individual leaves such that those most photosynthetically productive are best protected. To test these hypotheses, we used a 3D functional-structural plant model of Brassica nigra that mechanistically simulates the interactions between plant architecture, herbivory, and the light environment. Our results show that plant-level defence expression is a strong determinant of plant fitness and that leaf-level defence mediation by R:FR can provide a fitness benefit in high densities. However, optimal plant-level defence expression does not decrease monotonically with plant density, indicating that R:FR mediation of defence alone is not enough to optimize defence between densities. Therefore, assessing the ecological significance of R:FR-mediated defence is paramount to better understand the evolution of this physiological linkage and its implications for crop breeding.

Ecological interactions shape the adaptive value of plant defence: Herbivore attack versus competition for light

Plants defend themselves against diverse communities of herbivorous insects. This requires an investment of limited resources, for which plants also compete with neighbours. The consequences of an investment in defence are determined by the metabolic costs of defence as well as indirect or ecological costs through interactions with other organisms. These ecological costs have a potentially strong impact on the evolution of defensive traits, but have proven to be difficult to quantify.We aimed to quantify the relative impact of the direct and indirect or ecological costs and benefits of an investment in plant defence in relation to herbivory and intergenotypic competition for light. Additionally, we evaluated how the benefits of plant defence balance its costs in the context of herbivory and intergenotypic competition.To this end, we utilised a functional-structural plant (FSP) model of Brassica nigra that simulates plant growth and development, morphogenesis, herbivory and plant defence. In the model, a simulated investment in defences affected plant growth by competing with other plant organs for resources and affected the level and distribution of herbivore damage.Our results show that the ecological costs of intergenotypic competition for light are highly detrimental to the fitness of defended plants, as it amplifies the size difference between defended and undefended plants. This leads to herbivore damage counteracting the effects of intergenotypic competition under the assumption that herbivore damage scales with plant size. Additionally, we show that plant defence relies on reducing herbivore damage rather than the dispersion of herbivore damage, which is only beneficial under high levels of herbivore damage.We conclude that the adaptive value of plant defence is highly dependent on ecological interactions and is predominantly determined by the outcome of competition for light. plain language summary is available for this article.

Modelling leaf spectral properties in a soybean functional-structural plant model by integrating the prospect radiative transfer model

Background and Aims

Currently, functional-structural plant models (FSPMs) mostly resort to static descriptions of leaf spectral characteristics, which disregard the influence of leaf physiological changes over time. In many crop species, including soybean, these time-dependent physiological changes are of particular importance as leaf chlorophyll content changes with leaf age and vegetative nitrogen is remobilized to the developing fruit during pod filling.

Methods

PROSPECT, a model developed to estimate leaf biochemical composition from remote sensing data, is well suited to allow a dynamic approximation of leaf spectral characteristics in terms of leaf composition. In this study, measurements of the chlorophyll content index (CCI) were linked to leaf spectral characteristics within the 400-800 nm range by integrating the PROSPECT model into a soybean FSPM alongside a wavelength-specific light model.

Key Results

Straightforward links between the CCI and the parameters of the PROSPECT model allowed us to estimate leaf spectral characteristics with high accuracy using only the CCI as an input. After integration with an FSPM, this allowed digital reconstruction of leaf spectral characteristics on the scale of both individual leaves and the whole canopy. As a result, accurate simulations of light conditions within the canopy were obtained.

Conclusions

The proposed approach resulted in a very accurate representation of leaf spectral properties, based on fast and simple measurements of the CCI. Integration of accurate leaf spectral characteristics into a soybean FSPM leads to a better, dynamic understanding of the actual perceived light within the canopy in terms of both light quantity and quality.

A 3-D functional-structural grapevine model that couples the dynamics of water transport with leaf gas exchange

Background and Aims

Predicting both plant water status and leaf gas exchange under various environmental conditions is essential for anticipating the effects of climate change on plant growth and productivity. This study developed a functional-structural grapevine model which combines a mechanistic understanding of stomatal function and photosynthesis at the leaf level (i.e. extended Farqhuhar-von Caemmerer-Berry model) and the dynamics of water transport from soil to individual leaves (i.e. Tardieu-Davies model).

Methods

The model included novel features that account for the effects of xylem embolism (fPLC) on leaf hydraulic conductance and residual stomatal conductance (g0), variable root and leaf hydraulic conductance, and the microclimate of individual organs. The model was calibrated with detailed datasets of leaf photosynthesis, leaf water potential, xylem sap abscisic acid (ABA) concentration and hourly whole-plant transpiration observed within a soil drying period, and validated with independent datasets of whole-plant transpiration under both well-watered and water-stressed conditions.

Key Results

The model well captured the effects of radiation, temperature, CO2 and vapour pressure deficit on leaf photosynthesis, transpiration, stomatal conductance and leaf water potential, and correctly reproduced the diurnal pattern and decline of water flux within the soil drying period. In silico analyses revealed that decreases in g0 with increasing fPLC were essential to avoid unrealistic drops in leaf water potential under severe water stress. Additionally, by varying the hydraulic conductance along the pathway (e.g. root and leaves) and changing the sensitivity of stomatal conductance to ABA and leaf water potential, the model can produce different water use behaviours (i.e. iso- and anisohydric).

Conclusions

The robust performance of this model allows for modelling climate effects from individual plants to fields, and for modelling plants with complex, non-homogenous canopies. In addition, the model provides a basis for future modelling efforts aimed at describing the physiology and growth of individual organs in relation to water status.

Quantifying within-plant spatial heterogeneity in carbohydrate availability in cotton using a local-pool model

Background and Aims

Within-plant spatial heterogeneity in the production of and demand for assimilates may have major implications for the formation of fruits. Spatial heterogeneity is related to organ age, but also to position on the plant. This study quantifies the variation in local carbohydrate availability for the phytomers in the same cohort using a cotton growth model that captures carbohydrate production in phytomers and carbohydrate movement between phytomers.

Methods

Based on field observations, we developed a functional-structural plant model of cotton that simulates production and storage of carbohydrates in individual phytomers and transport of surplus to other phytomers. Simulated total leaf area, total above-ground dry mass, dry mass distribution along the stem, and dry mass allocation fractions to each organ at the plant level were compared with field observations for plants grown at different densities. The distribution of local carbohydrate availability throughout the plant was characterized and a sensitivity analysis was conducted regarding the value of the carbohydrate transport coefficient.

Key Results

The model reproduced cotton leaf expansion and dry mass allocation across plant densities adequately. Individual leaf area was underestimated at very high plant densities. Best correspondence with measured plant traits was obtained for a value of the transport coefficient of 0.1 d-1. The simulated translocation of carbohydrates agreed well with results from C-labelling studies. Moreover, simulation results revealed the heterogeneous pattern of local carbohydrate availability over the plant as an emergent model property.

Conclusions

This modelling study shows how heterogeneity in local carbohydrate production within the plant structure in combination with limitations in transport result in heterogeneous satisfaction of demand over the plant. This model provides a tool to explore phenomena in cotton that are thought to be determined by local carbohydrate availability, such as branching pattern and fruit abortion in relation to climate and crop management.

Elucidating the interaction between light competition and herbivore feeding patterns using functional-structural plant modelling

Background and Aims

Plants usually compete with neighbouring plants for resources such as light as well as defend themselves against herbivorous insects. This requires investment of limiting resources, resulting in optimal resource distribution patterns and trade-offs between growth- and defence-related traits. A plant's competitive success is determined by the spatial distribution of its resources in the canopy. The spatial distribution of herbivory in the canopy in turn differs between herbivore species as the level of herbivore specialization determines their response to the distribution of resources and defences in the canopy. Here, we investigated to what extent competition for light affects plant susceptibility to herbivores with different feeding preferences.

Methods

To quantify interactions between herbivory and competition, we developed and evaluated a 3-D spatially explicit functional-structural plant model for Brassica nigra that mechanistically simulates competition in a dynamic light environment, and also explicitly models leaf area removal by herbivores with different feeding preferences. With this novel approach, we can quantitatively explore the extent to which herbivore feeding location and light competition interact in their effect on plant performance.

Key Results

Our results indicate that there is indeed a strong interaction between levels of plant-plant competition and herbivore feeding preference. When plants did not compete, herbivory had relatively small effects irrespective of feeding preference. Conversely, when plants competed, herbivores with a preference for young leaves had a strong negative effect on the competitiveness and subsequent performance of the plant, whereas herbivores with a preference for old leaves did not.

Conclusions

Our study predicts how plant susceptibility to herbivory depends on the composition of the herbivore community and the level of plant competition, and highlights the importance of considering the full range of dynamics in plant-plant-herbivore interactions.

Effects of rare earth and acid rain pollution on plant chloroplast ATP synthase and element contents at different growth stages

Combined rare earth and acid rain pollution has become a new environmental problem, seriously affecting plant survival. The effects of these two kinds of pollutants on plant photosynthesis have been reported, but the micro mechanisms are not very clear. In this research, we studied the effects of lanthanum [La(III), 0.08, 1.20 and 2.40 mM] and acid rain (pH value = 2.5, 3.5 and 4.5) on the ATPase activity and gene transcription level and the functional element contents in rice leaf chloroplasts. The results showed that the combined 0.08 mM La(III) and pH 4.5 acid rain increased the ATPase activity and gene transcription level as well as contents of some functional elements. But other combined treatments of acid rain and La(III) reduced the ATPase activity and gene transcription level as well as functional element contents. The change magnitude of the above indexes at rice booting stage was greater than that in seedling stage or grain filling stage. These results reveal that effects of La(III) and acid rain on ATPase activity and functional element contents in rice leaf chloroplasts are related to the combination of La(III) dose and acid rain intensity and the plant growth stage. In addition, the changes in the ATPase activity were related to ATPase gene transcription level. This study would provide a reference for understanding the microcosmic mechanism of rare earth and acid rain pollution on plant photosynthesis and contribute to evaluate the possible environmental risks associated with combined La(III) and acid rain pollution.

ONE SENTENCE SUMMARY

The effects of La(III) and acid rain on activity and gene transcription level of rice chloroplast ATPase and contents of functional elements were different at different growth stages.

A Photosynthesis-based Two-leaf Canopy Stomatal Conductance Model for Meteorology and Air Quality Modeling with WRF/CMAQ PX LSM

A coupled photosynthesis-stomatal conductance model with single layer sunlit and shaded leaf canopy scaling is developed for the Pleim-Xiu land surface model (LSM) option in the meteorology and air quality modeling system - WRF/CMAQ (Weather Research and Forecast model and Community Multiscale Air Quality model). The photosynthesis-based model for the PX LSM (PX PSN) is implemented and evaluated in a diagnostic box model that has evapotranspiration and ozone deposition components taken directly from WRF/CMAQ. We evaluate PX PSN for latent heat (LH) estimation at four FLUXNET sites with different vegetation types and landscape characteristics and at one FLUXNET site with ozone flux measurements against the simple Jarvis approach used in the current PX LSM. Overall, the PX PSN simulates LH as well as the PX Jarvis approach. The PX PSN, however, shows distinct advantages over the PX Jarvis approach on grassland that likely results from its treatment of C₃ and C₄ plants for CO₂ assimilation estimation. Simulations using Moderate Resolution Imaging Spectroradiometer (MODIS) LAI rather than LAI observations assess how the model would perform with the grid averaged data available in the Eulerian grid model (WRF/CMAQ). While MODIS LAI generally follows the seasonality of the observed LAI, it cannot capture the extreme highs and lows of the site measurements. MODIS LAI estimates degrade model performance at all sites but one site having old and tall trees. Ozone deposition velocity and ozone flux along with LH are simulated especially well by PX PSN as compared to significant PX Jarvis overestimation.

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

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

Quantifying the effect of crop spatial arrangement on weed suppression using functional-structural plant modelling

Suppression of weed growth in a crop canopy can be enhanced by improving crop competitiveness. One way to achieve this is by modifying the crop planting pattern. In this study, we addressed the question to what extent a uniform planting pattern increases the ability of a crop to compete with weed plants for light compared to a random and a row planting pattern, and how this ability relates to crop and weed plant density as well as the relative time of emergence of the weed. To this end, we adopted the functional-structural plant modelling approach which allowed us to explicitly include the 3D spatial configuration of the crop-weed canopy and to simulate intra- and interspecific competition between individual plants for light. Based on results of simulated leaf area development, canopy photosynthesis and biomass growth of the crop, we conclude that differences between planting pattern were small, particularly if compared to the effects of relative time of emergence of the weed, weed density and crop density. Nevertheless, analysis of simulated weed biomass demonstrated that a uniform planting of the crop improved the weed-suppression ability of the crop canopy. Differences in weed suppressiveness between planting patterns were largest with weed emergence before crop emergence, when the suppressive effect of the crop was only marginal. With simultaneous emergence a uniform planting pattern was 8 and 15 % more competitive than a row and a random planting pattern, respectively. When weed emergence occurred after crop emergence, differences between crop planting patterns further decreased as crop canopy closure was reached early on regardless of planting pattern. We furthermore conclude that our modelling approach provides promising avenues to further explore crop-weed interactions and aid in the design of crop management strategies that aim at improving crop competitiveness with weeds.

Leaf age dependent changes in within-canopy variation in leaf functional traits: a meta-analysis

Within-canopy variation in leaf structural and photosynthetic characteristics is a major means by which whole canopy photosynthesis is maximized at given total canopy nitrogen. As key acclimatory modifications, leaf nitrogen content (N A) and photosynthetic capacity (A A) per unit area increase with increasing light availability in the canopy and these increases are associated with increases in leaf dry mass per unit area (M A) and/or nitrogen content per dry mass and/or allocation. However, leaf functional characteristics change with increasing leaf age during leaf development and aging, but the importance of these alterations for within-canopy trait gradients is unknown. I conducted a meta-analysis based on 71 canopies that were sampled at different time periods or, in evergreens, included measurements for different-aged leaves to understand how within-canopy variations in leaf traits (trait plasticity) depend on leaf age. The analysis demonstrated that in evergreen woody species, M A and N A plasticity decreased with increasing leaf age, but the change in A A plasticity was less suggesting a certain re-acclimation of A A to altered light. In deciduous woody species, M A and N A gradients in flush-type species increased during leaf development and were almost invariable through the rest of the season, while in continuously leaf-forming species, the trait gradients increased constantly with increasing leaf age. In forbs, N A plasticity increased, while in grasses, N A plasticity decreased with increasing leaf age, reflecting life form differences in age-dependent changes in light availability and in nitrogen resorption for growth of generative organs. Although more work is needed to improve the coverage of age-dependent plasticity changes in some plant life forms, I argue that the age-dependent variation in trait plasticity uncovered in this study is large enough to warrant incorporation in simulations of canopy photosynthesis through the growing period.

How can we make plants grow faster? A source-sink perspective on growth rate

Growth is a major component of fitness in all organisms, an important mediator of competitive interactions in plant communities, and a central determinant of yield in crops. Understanding what limits plant growth is therefore of fundamental importance to plant evolution, ecology, and crop science, but each discipline views the process from a different perspective. This review highlights the importance of source-sink interactions as determinants of growth. The evidence for source- and sink-limitation of growth, and the ways in which regulatory molecular feedback systems act to maintain an appropriate source:sink balance, are first discussed. Evidence clearly shows that future increases in crop productivity depend crucially on a quantitative understanding of the extent to which sources or sinks limit growth, and how this changes during development. To identify bottlenecks limiting growth and yield, a holistic view of growth is required at the whole-plant scale, incorporating mechanistic interactions between physiology, resource allocation, and plant development. Such a holistic perspective on source-sink interactions will allow the development of a more integrated, whole-system level understanding of growth, with benefits across multiple disciplines.

High temperature and vapor pressure deficit aggravate architectural effects but ameliorate non-architectural effects of salinity on dry mass production of tomato

Tomato (Solanum lycopersicum L.) is an important vegetable crop and often cultivated in regions exposed to salinity and high temperatures (HT) which change plant architecture, decrease canopy light interception and disturb physiological functions. However, the long-term effects of salinity and HT combination (S+HT) on plant growth are still unclear. A dynamic functional-structural plant model (FSPM) of tomato was parameterized and evaluated for different levels of S+HT combinations. The evaluated model was used to quantify the contributions of morphological changes (architectural effects) and physiological disturbances (non-architectural effects) on the reduction of shoot dry mass under S+HT. The model predicted architectural variables with high accuracy (>85%), which ensured the reliability of the model analyses. HT enhanced architectural effects but reduced non-architectural effects of salinity on dry mass production. The stronger architectural effects of salinity under HT could not be counterbalanced by the smaller non-architectural effects. Therefore, long-term influences of HT on shoot dry mass under salinity were negative at the whole plant level. Our model analysis highlights the importance of plant architecture at canopy level in studying the plant responses to the environments and shows the merits of dynamic FSPMs as heuristic tools.

An empirical model that uses light attenuation and plant nitrogen status to predict within-canopy nitrogen distribution and upscale photosynthesis from leaf to whole canopy

Modelling the spatial and temporal distribution of leaf nitrogen (N) is central to specify photosynthetic parameters and simulate canopy photosynthesis. Leaf photosynthetic parameters depend on both local light availability and whole-plant N status. The interaction between these two levels of integration has generally been modelled by assuming optimal canopy functioning, which is not supported by experiments. During this study, we examined how a set of empirical relationships with measurable parameters could be used instead to predict photosynthesis at the leaf and whole-canopy levels. The distribution of leaf N per unit area (Na) within the canopy was related to leaf light irradiance and to the nitrogen nutrition index (NNI), a whole-plant variable accounting for plant N status. Na was then used to determine the photosynthetic parameters of a leaf gas exchange model. The model was assessed on alfalfa canopies under contrasting N nutrition and with N2-fixing and non-fixing plants. Three experiments were carried out to parameterize the relationships between Na, leaf irradiance, NNI and photosynthetic parameters. An additional independent data set was used for model evaluation. The N distribution model showed that it was able to predict leaf N on the set of leaves tested. The Na at the top of the canopy appeared to be related linearly to the NNI, whereas the coefficient accounting for N allocation remained constant. Photosynthetic parameters were related linearly to Na irrespective of N nutrition and the N acquisition mode. Daily patterns of gas exchange were simulated accurately at the leaf scale. When integrated at the whole-canopy scale, the model predicted that raising N availability above an NNI of 1 did not result in increased net photosynthesis. Overall, the model proposed offered a solution for a dynamic coupling of leaf photosynthesis and canopy N distribution without requiring any optimal functioning hypothesis.

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.

Quantification of the effects of architectural traits on dry mass production and light interception of tomato canopy under different temperature regimes using a dynamic functional-structural plant model

There is increasing interest in evaluating the environmental effects on crop architectural traits and yield improvement. However, crop models describing the dynamic changes in canopy structure with environmental conditions and the complex interactions between canopy structure, light interception, and dry mass production are only gradually emerging. Using tomato (Solanum lycopersicum L.) as a model crop, a dynamic functional-structural plant model (FSPM) was constructed, parameterized, and evaluated to analyse the effects of temperature on architectural traits, which strongly influence canopy light interception and shoot dry mass. The FSPM predicted the organ growth, organ size, and shoot dry mass over time with high accuracy (>85%). Analyses of this FSPM showed that, in comparison with the reference canopy, shoot dry mass may be affected by leaf angle by as much as 20%, leaf curvature by up to 7%, the leaf length:width ratio by up to 5%, internode length by up to 9%, and curvature ratios and leaf arrangement by up to 6%. Tomato canopies at low temperature had higher canopy density and were more clumped due to higher leaf area and shorter internodes. Interestingly, dry mass production and light interception of the clumped canopy were more sensitive to changes in architectural traits. The complex interactions between architectural traits, canopy light interception, dry mass production, and environmental conditions can be studied by the dynamic FSPM, which may serve as a tool for designing a canopy structure which is 'ideal' in a given environment.