Assessing the effects of architectural variations on light partitioning within virtual wheat-pea mixtures

Improvement of cool-season food legumes for adaptation to intercropping systems: breeding faba bean for intercropping with durum wheat as a case study

Although the transition toward a more sustainable agricultural system is sparking the interest of scientists and farmers around the globe, breeding programs are still focusing on optimizing cultivars intended for the monoculture system, and most cultivars available on the market are not suitable for intercropping. The incorporation of versatile cool-season food legumes (CSFLs) in the intercropping system is a promising way toward more diversified and sustainable cropping systems. However, as the selection of good-performing cultivars under sole cropping does not always lead to a good performance in intercropping, the development of an alternative breeding scheme for intercropping is now a necessity. The case study of faba bean-wheat intercropping was used to select for traits associated with better performance of faba bean, resulting in identifying the combined grain yield, 100-seed weight, number of pods per plant, and canopy height as key traits for faba bean-wheat intercropping suitability. Incorporating these traits in the breeding programs would be the cornerstone of the prospective transition.

The Importance of Using Realistic 3D Canopy Models to Calculate Light Interception in the Field

Quantifying canopy light interception provides insight into the effects of plant spacing, canopy structure, and leaf orientation on radiation distribution. This is essential for increasing crop yield and improving product quality. Canopy light interception can be quantified using 3-dimensional (3D) plant models and optical simulations. However, virtual 3D canopy models (VCMs) have often been used to quantify canopy light interception because realistic 3D canopy models (RCMs) are difficult to obtain in the field. This study aims to compare the differences in light interception between VCMs and RCM. A realistic 3D maize canopy model (RCM) was reconstructed over a large area of the field using an advanced unmanned aerial vehicle cross-circling oblique (CCO) route and the structure from motion-multi-view stereo method. Three types of VCMs (VCM-1, VCM-4, and VCM-8) were then created by replicating 1, 4, and 8 individual realistic plants constructed by CCO in the center of the corresponding RCM. The daily light interception per unit area (DLI), as computed for the 3 VCMs, exhibited marked deviation from the RCM, as evinced by the relative root mean square error (rRMSE) values of 20.22%, 17.38%, and 15.48%, respectively. Although this difference decreased as the number of plants used to replicate the virtual canopy increased, rRMSE of DLI for VCM-8 and RCM still reached 15.48%. It was also found that the difference in light interception between RCMs and VCMs was substantially smaller in the early stage (48 days after sowing [DAS]) than in the late stage (70 DAS). This study highlights the importance of using RCM when calculating light interception in the field, especially in the later growth stages of plants.

More than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters: a computational study on wheat crop

Using in silico experiment in crop model, we identified different physiological regulations of yield and yield stability, as well as quantify the genotype and environment numbers required for analysing yield stability convincingly. Identifying target traits for breeding stable and high-yielded cultivars simultaneously is difficult due to limited knowledge of physiological mechanisms behind yield stability. Besides, there is no consensus about the adequacy of a stability index (SI) and the minimal number of environments and genotypes required for evaluating yield stability. We studied this question using the crop model APSIM-Wheat to simulate 9100 virtual genotypes grown under 9000 environments. By analysing the simulated data, we showed that the shape of phenotype distributions affected the correlation between SI and mean yield and the genotypic superiority measure (P_i) was least affected among 11 SI. P_i was used as index to demonstrate that more than 150 environments were required to estimate yield stability of a genotype convincingly and more than 1000 genotypes were necessary to evaluate the contribution of a physiological parameter to yield stability. Network analyses suggested that a physiological parameter contributed preferentially to yield or P_i. For example, soil water absorption efficiency and potential grain filling rate explained better the variations in yield than in P_i; while light extinction coefficient and radiation use efficiency were more correlated with P_i than with yield. The high number of genotypes and environments required for studying P_i highlight the necessity and potential of in silico experiments to better understand the mechanisms behind yield stability.

Leaf, plant, to canopy: A mechanistic study on aboveground plasticity and plant density within a maize-soybean intercrop system for the Midwest, USA

Plants have evolved to adapt to their neighbours through plastic trait responses. In intercrop systems, plant growth occurs at different spatial and temporal dimensions, creating a competitive light environment where aboveground plasticity may support complementarity in light-use efficiency, realizing yield gains per unit area compared with monoculture systems. Physiological and architectural plasticity including the consequences for light-use efficiency and yield in a maize-soybean solar corridor intercrop system was compared, empirically, with the standard monoculture systems of the Midwest, USA. The impact of reducing maize plant density on yield was investigated in the following year. Intercropped maize favoured physiological plasticity over architectural plasticity, which maintained harvest index (HI) but reduced light interception efficiency (ɛ_i ) and conversion efficiency (ɛ_c ). Intercropped soybean invested in both plasticity responses, which maintained ɛ_i , but HI and ɛ_c decreased. Reducing maize plant density within the solar corridor rows did not improve yields under monoculture and intercrop systems. Overall, the intercrop decreased land-use efficiency by 9%-19% and uncoordinated investment in aboveground plasticity by each crop under high maize plant density does not support complementarity in light-use efficiency. Nonetheless, the mechanistic understanding gained from this study may improve crop cultivars and intercrop designs for the Midwest to increase yield.

Application of Crop Growth Models to Assist Breeding for Intercropping: Opportunities and Challenges

Intercropping of two or more species on the same piece of land can enhance biodiversity and resource use efficiency in agriculture. Traditionally, intercropping systems have been developed and improved by empirical methods within a specific local context. To support the development of promising intercropping systems, the individual species that are part of an intercrop can be subjected to breeding. Breeding for intercropping aims at resource foraging traits of the admixed species to maximize niche complementarity, niche facilitation, and intercrop performance. The breeding process can be facilitated by modeling tools that simulate the outcome of the combination of different species' (or genotypes') traits for growth and yield development, reducing the need of extensive field testing. Here, we revisit the challenges associated with breeding for intercropping, and give an outlook on applying crop growth models to assist breeding for intercropping. We conclude that crop growth models can assist breeding for intercropping, provided that (i) they incorporate the relevant plant features and mechanisms driving interspecific plant-plant interactions; (ii) they are based on model parameters that are closely linked to the traits that breeders would select for; and (iii) model calibration and validation is done with field data measured in intercrops. Minimalist crop growth models are more likely to incorporate the above elements than comprehensive but parameter-intensive crop growth models. Their lower complexity and reduced parameter requirement facilitate the exploration of mechanisms at play and fulfil the model requirements for calibration of the appropriate crop growth models.

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.

Functional-Structural Plant Modeling Highlights How Diversity in Leaf Dimensions and Tillering Capability Could Promote the Efficiency of Wheat Cultivar Mixtures

Increasing the cultivated diversity has been identified as a major leverage for the agroecological transition as it can help improve the resilience of low input cropping systems. For wheat, which is the most cultivated crop worldwide in terms of harvested area, the use of cultivar mixtures is spreading in several countries, but studies have seldom focused on establishing mixing rules based on plant architecture. Yet, the aerial architecture of plants and the overall canopy structure are critical for field performance as they greatly influence light interception, plant interactions and yield. The very high number of trait combinations in wheat mixtures makes it difficult to conduct experimentations on this issue, which is why a modeling approach appears to be an appropriate solution. In this study, we used WALTer, a functional structural plant model (FSPM), to simulate wheat cultivar mixtures and try to better understand how differences between cultivars in key traits of the aerial architecture influence mixture performance. We simulated balanced binary mixtures of cultivars differing for different critical plant traits: final height, leaf dimensions, leaf insertion angle and tillering capability. Our study highlights the impact of the leaf dimensions and the tillering capability on the performance of the simulated mixtures, which suggests that traits impacting the plants' leaf area index (LAI) have more influence on the performance of the stand than traits impacting the arrangement of the leaves. Our results show that the performance of mixtures is very variable depending on the values of the explored architectural traits. In particular, the best performances were achieved by mixing cultivars with different leaf dimensions and different tillering capability, which is in agreement with numerous studies linking the diversity of functional traits in plant communities to their productivity. However, some of the worst performances were also achieved by mixing varieties differing in their aerial architecture, which suggests that diversity is not a sufficient criterion to design efficient mixtures. Overall, these results highlight the importance of simulation-based explorations for establishing assembly rules to design efficient mixtures.

Pea Breeding for Intercropping With Cereals: Variation for Competitive Ability and Associated Traits, and Assessment of Phenotypic and Genomic Selection Strategies

Mixed stand (MS) cropping of pea with small-grain cereals can produce more productive and environment-friendly grain crops relative to pure stand (PS) crops but may require selection to alleviate the pea competitive disadvantage. This study aimed to assess the pea variation for competitive ability and its associated traits and the efficiency of four phenotypic or genomic selection strategies. A set of 138 semi-leafless, semi-dwarf pea lines belonging to six recombinant inbred line populations and six parent lines were genotyped using genotyping-by-sequencing and grown in PS and in MS simultaneously with one barley and one bread wheat cultivar in two autumn-sown trials in Northern Italy. Cereal companions were selected in a preliminary study that highlighted the paucity of cultivars with sufficient earliness for association. Pea was severely outcompeted in both years albeit with variation for pea proportion ranging from nearly complete suppression (<3%) to values approaching a balanced mixture. Greater pea proportion in MS was associated with greater total yield of the mixture (r ≥ 0.46). The genetic correlation for pea yield across MS and PS conditions slightly exceeded 0.40 in both years. Later onset of flowering and taller plant height at flowering onset displayed a definite correlation with pea yield in MS (r ≥ 0.46) but not in PS, whereas tolerance to ascochyta blight exhibited the opposite pattern. Comparisons of phenotypic selection strategies within or across populations based on predicted or actual yield gains for independent years indicated an efficiency of 52-64% for indirect selection based on pea yield in PS relative to pea yield selection in MS. The efficiency of an indirect selection index including onset of flowering, plant height, and grain yield in PS was comparable to that of pea yield selection in MS. A genome-wide association study based on 5,909 SNP markers revealed the substantial diversity of genomic areas associated with pea yield in MS and PS. Genomic selection for pea yield in MS displayed an efficiency close to that of phenotypic selection for pea yield in MS, and nearly two-fold greater efficiency when also taking into account its shorter selection cycle and smaller evaluation cost.

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.

Breeding Beyond Monoculture: Putting the "Intercrop" Into Crops

Intercropping is both a well-established and yet novel agricultural practice, depending on one's perspective. Such perspectives are principally governed by geographic location and whether monocultural practices predominate. Given the negative environmental effects of monoculture agriculture (loss of biodiversity, reliance on non-renewable inputs, soil degradation, etc.), there has been a renewed interest in cropping systems that can reduce the impact of modern agriculture while maintaining (or even increasing) yields. Intercropping is one of the most promising practices in this regard, yet faces a multitude of challenges if it is to compete with and ultimately replace the prevailing monocultural norm. These challenges include the necessity for more complex agricultural designs in space and time, bespoke machinery, and adapted crop cultivars. Plant breeding for monocultures has focused on maximizing yield in single-species stands, leading to highly productive yet specialized genotypes. However, indications suggest that these genotypes are not the best adapted to intercropping systems. Re-designing breeding programs to accommodate inter-specific interactions and compatibilities, with potentially multiple different intercropping partners, is certainly challenging, but recent technological advances offer novel solutions. We identify a number of such technology-driven directions, either ideotype-driven (i.e., "trait-based" breeding) or quantitative genetics-driven (i.e., "product-based" breeding). For ideotype breeding, plant growth modeling can help predict plant traits that affect both inter- and intraspecific interactions and their influence on crop performance. Quantitative breeding approaches, on the other hand, estimate breeding values of component crops without necessarily understanding the underlying mechanisms. We argue that a combined approach, for example, integrating plant growth modeling with genomic-assisted selection and indirect genetic effects, may offer the best chance to bridge the gap between current monoculture breeding programs and the more integrated and diverse breeding programs of the future.

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

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

Towards intercrop ideotypes: non-random trait assembly can promote overyielding and stability of species proportion in simulated legume-based mixtures

BACKGROUNDS AND AIMS

A major challenge when supporting the development of intercropping systems remains the design of efficient species mixtures. The ecological processes that sustain overyielding of legume-based mixtures compared to pure crops are well known, but their links to plant traits remain to be unravelled. A common assumption is that enhancing trait divergence among species for resource acquisition when assembling plant mixtures should increase species complementarity and improve community performance.

METHODS

The Virtual Grassland model was used to assess how divergence in trait values between species on four physiological functions (namely light and mineral N acquisition, temporal development, and C-N use efficiency) affected overyielding and mixture stability in legume-based binary mixtures. A first step allowed us to identify the model parameters that were most important to interspecies competition. A second step involved testing the impact of convergent and divergent parameter (or trait) values between species on virtual mixture performance.

RESULTS

Maximal overyielding was achieved in cases where trait values were divergent for the physiological functions controlling N acquisition and temporal development but convergent for light interception. It was also found that trait divergence should not affect competitive abilities of legume and non-legumes at random. Indeed, random trait combinations frequently led to reduced mixture yields when compared to a perfectly convergent neutral model. Combinations with the highest overyielding also tended to be associated with mixture instability and decreasing legume biomass proportion. Achieving both high overyielding and mixture stability was only found to be possible under low or moderate N levels, using combinations of traits adapted to each environment.

CONCLUSIONS

No simple assembly rule based on trait divergence could be confirmed. Plant models able to infer plant-plant interactions can be helpful for the identification of major interaction traits and the definition of ideotypes adapted to a targeted intercropping system.

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.

Influence of irrigation regimes on competition indexes of winter and summer intercropping system under semi-arid regions of Pakistan

An assessment of the competitive indexes in intercropping of different winter and summer based intercropping systems were studied, with the aim of increasing the productivity of these crops. Four winter crops, wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), fababean (Vicia faba) and rapeseed (Brassica napus) and four summer crops, sorghum (Sorghum bicolor L.), pearl millet (Pennisetum typhoidum L.), pigeonpea (Cajanus cajan L.) and mungbean (Vigna radiate L.) were grown under two irrigation regimes with the pattern of two crops in each intercropping system, at Agronomy Research Farm, The University of Agriculture, Peshawar, Pakistan in both winter and summer season during 2015-16 to 2016-17. The results showed that higher grain yield (kg ha^-1) were recorded under sole cropping than intercropping. Higher grain yield was recorded in sole cropping, for all four crops. All crops grown in intercropping produced comparatively higher grains head^-1 and seeds pod^-1 than sole crop except pigeonpea. Intercropping systems were performed different in term of competition indexes which determined land utilization efficiency. Competition indexes revealed that in winter season wheat intercropped with fababean showed highest advantages of intercropping in term of land equivalent ratio (30%), relative crowding co-efficient (60%), actual yield loss (60%), area time equivalent ratio (27%), land utilization efficiency (83%), intercropping advantages (1060), monetary advantage index (Pakistani rupees (PKR) 46456) and system productivity index (3684) while in summer sorghum/pearl millet intercropped with pigeonpea was the most dominant intercropping systems in term of relative  crowding co-Efficient (40%), actual yield loss (50%), land utilization efficiency (60%) intercropping advantages (1150) and system productivity index (1914). Aggressivity and competition ratio showed that cereals especially barley in winter and sorghum in summer season was highly competitive crops in the intercropping system. Most of the competition indexes values were higher for winter crops under limited irrigated condition while in case of summer crops intercropping indexes were higher under full irrigated condition. It was concluded that wheat intercropped with fababean, and sorghum/millet intercropped with mung bean was the most successful intercropping systems in winter and summer seasons, respectively under both irrigation regimes, for the semiarid region of Pakistan.

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.

A generic individual-based model can predict yield, nitrogen content, and species abundance in experimental grassland communities

Functional-structural plant models are increasingly being used to analyse relationships between plant functioning and the topological and spatial organisation of their modular structure. In this study, the performance of an individual-based model accounting for the the architecture and population dynamics of forage legumes in multi-species grasslands was assessed. Morphogenetic shoot and root parameters were calibrated for seven widely used species. Other model parameters concerning C and N metabolism were obtained from the literature. The model was evaluated using a series of independent experiments combining the seven species in binary mixtures that were subject to regular defoliation. For all the species, the model could accurately simulate phytomer demography, leaf area dynamics, and root growth under conditions of weak competition. In addition, the plastic changes induced by competition for light and N in terms of plant development, leaf area, N uptake, and total plant biomass were correctly predicted. The different species displayed contrasting sensitivities to defoliation, and the model was able to predict the superior ability of creeping species to sustain regular defoliation. As a result of competition and management, the balance between species changed over time and was strongly dependent on the pair of species used. The model proved able to capture these differences in community dynamics. Overall, the results demonstrate that integrating the individual components of population dynamics in a process-based model can provide good predictive capacity regarding mixtures of cultivated species.

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.

Use of computational modeling combined with advanced visualization to develop strategies for the design of crop ideotypes to address food security

Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have led to discoveries in "big data" analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. This survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields.

A generic individual-based model to simulate morphogenesis, C-N acquisition and population dynamics in contrasting forage legumes

Background and Aims

Individual-based models (IBMs) are promising tools to disentangle plant interactions in multi-species grasslands and foster innovative species mixtures. This study describes an IBM dealing with the morphogenesis, growth and C-N acquisition of forage legumes that integrates plastic responses from functional-structural plant models.

Methods

A generic model was developed to account for herbaceous legume species with contrasting above- and below-ground morphogenetic syndromes and to integrate the responses of plants to light, water and N. Through coupling with a radiative transfer model and a three-dimensional virtual soil, the model allows dynamic resolution of competition for multiple resources at individual plant level within a plant community. The behaviour of the model was assessed on a range of monospecific stands grown along gradients of light, water and N availability.

Key Results

The model proved able to capture the diversity of morphologies encountered among the forage legumes. The main density-dependent features known about even-age plant populations were correctly anticipated. The model predicted (1) the 'reciprocal yield' law relating average plant mass to density, (2) a self-thinning pattern close to that measured for herbaceous species and (3) consistent changes in the size structure of plant populations with time and pedo-climatic conditions. In addition, plastic changes in the partitioning of dry matter, the N acquisition mode and in the architecture of shoots and roots emerged from the integration of plant responses to their local environment. This resulted in taller plants and thinner roots when competition was dominated by light, and shorter plants with relatively more developed root systems when competition was dominated by soil resources.

Conclusions

A population dynamic model considering growth and morphogenesis responses to multiple resources heterogeneously distributed in the environment was presented. It should allow scaling plant-plant interactions from individual to community levels without the inconvenience of average plant models.

Computational botany: advancing plant science through functional–structural plant modelling

The need to integrate the ever-expanding body of knowledge in the plant sciences has led to the development of sophisticated modelling approaches. This special issue focuses on functional–structural plant (FSP) models, which are the result of cross-fertilization between the domains of plant science, computer science and mathematics. FSP models simulate growth and morphology of individual plants that interact with their environment, from which complex plant community properties emerge. FSP models can be used for a broad range of research questions across disciplines related to plant science. This special issue presents the latest developments in FSP modelling, including the novel incorporation of plant ecophysiological concepts and the application of FSP models to address new scientific questions. Additionally, it illustrates the breadth of model evaluation approaches that are performed. FSP modelling is a very active domain of plant research which brings together a wide range of scientific disciplines. It offers the opportunity to address questions in complex plant systems that cannot be addressed by empirical approaches alone, including questions on fundamental concepts related to plant development such as regulation of morphogenesis, as well as on applied concepts such as the relationship between crop performance and plant competition for resources.

Image-based 3D canopy reconstruction to determine potential productivity in complex multi-species crop systems

Background and Aims

Intercropping systems contain two or more species simultaneously in close proximity. Due to contrasting features of the component crops, quantification of the light environment and photosynthetic productivity is extremely difficult. However it is an essential component of productivity. Here, a low-tech but high-resolution method is presented that can be applied to single- and multi-species cropping systems to facilitate characterization of the light environment. Different row layouts of an intercrop consisting of Bambara groundnut ( Vigna subterranea ) and proso millet ( Panicum miliaceum ) have been used as an example and the new opportunities presented by this approach have been analysed.

Methods

Three-dimensional plant reconstruction, based on stereo cameras, combined with ray tracing was implemented to explore the light environment within the Bambara groundnut-proso millet intercropping system and associated monocrops. Gas exchange data were used to predict the total carbon gain of each component crop.

Key Results

The shading influence of the tall proso millet on the shorter Bambara groundnut results in a reduction in total canopy light interception and carbon gain. However, the increased leaf area index (LAI) of proso millet, higher photosynthetic potential due to the C4 pathway and sub-optimal photosynthetic acclimation of Bambara groundnut to shade means that increasing the number of rows of millet will lead to greater light interception and carbon gain per unit ground area, despite Bambara groundnut intercepting more light per unit leaf area.

Conclusions

Three-dimensional reconstruction combined with ray tracing provides a novel, accurate method of exploring the light environment within an intercrop that does not require difficult measurements of light interception and data-intensive manual reconstruction, especially for such systems with inherently high spatial possibilities. It provides new opportunities for calculating potential productivity within multi-species cropping systems, enables the quantification of dynamic physiological differences between crops grown as monoculture and those within intercrops, and enables the prediction of new productive combinations of previously untested crops.

A Conserved Potential Development Framework Applies to Shoots of Legume Species with Contrasting Morphogenetic Strategies

A great variety of legume species are used for forage production and grown in multi-species grasslands. Despite their close phylogenetic relationship, they display a broad range of morphologies that markedly affect their competitive abilities and persistence in mixtures. Little is yet known about the component traits that control the deployment of plant architecture in most of these species. During the present study, we compared the patterns of shoot organogenesis and shoot organ growth in contrasting forage species belonging to the four morphogenetic groups previously identified in herbaceous legumes (i.e., stolon-formers, rhizome-formers, crown-formers tolerant to defoliation and crown-formers intolerant to defoliation). To achieve this, three greenhouse experiments were carried out using plant species from each group (namely alfalfa, birdsfoot trefoil, sainfoin, kura clover, red clover, and white clover) which were grown at low density under non-limiting water and soil nutrient availability. The potential morphogenesis of shoots characterized under these conditions showed that all the species shared a number of common morphogenetic features. All complied with a generalized classification of shoot axes into three types (main axis, primary and secondary axes). A common quantitative framework for vegetative growth and development involved: (i) the regular development of all shoot axes in thermal time and a deterministic branching pattern in the absence of stress; (ii) a temporal coordination of organ growth at the phytomer level that was highly conserved irrespective of phytomer position, and (iii) an identical allometry determining the surface area of all the leaves. The species differed in their architecture as a consequence of the values taken by component traits of morphogenesis. Assessing the relationships between the traits studied showed that these species were distinct from each other along two main PCA axes which explained 68% of total variance: the first axis captured a trade-off between maximum leaf size and the ability to produce numerous phytomers, while the second distinguished morphogenetic strategies reliant on either petiole or internode expansion to achieve space colonization. The consequences of this quantitative framework are discussed, along with its possible applications regarding plant phenotyping and modeling.

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.

Contrasting Strategies of Alfalfa Stem Elongation in Response to Fall Dormancy in Early Growth Stage: The Tradeoff between Internode Length and Internode Number

Fall dormancy (FD) in alfalfa (Medicago sativa L.) can be described using 11 FD ratings, is widely used as an important indicator of stress resistance, productive performance and spring growth. However, the contrasting growth strategies in internode length and internode number in alfalfa cultivars with different FD rating are poorly understood. Here, a growth chamber study was conducted to investigate the effect of FD on plant height, aboveground biomass, internode length, and internode number in alfalfa individuals in the early growth stages. In order to simulate the alfalfa growth environment in the early stage, 11 alfalfa cultivars with FD ratings from one to 11 were chosen and seeded at the greenhouse, and then were transplanted into an artificial growth chamber. The experimental design was a randomized complete block in a split-plot arrangement with three replicates. Plant height, above-ground biomass, internode length, and internode number were measured in early growth stage in all individuals. Our findings showed that plant height and the aboveground biomass of alfalfa did not significantly differ among 11 different FD rated cultivars. Also, internode length and internode number positively affected plant height and the aboveground biomass of alfalfa individuals and the average internode length significantly increased with increasing FD rating. However, internode number tended to sharply decline when the FD rating increased. Moreover, there were no correlations, slightly negative correlations, and strongly negative correlations between internode length and internode number in alfalfa individuals among the three scales, including within-FD ratings, within-FD categories and inter-FD ratings, respectively. Therefore, our results highlighted that contrasting growth strategies in stem elongation were adopted by alfalfa with different FD ratings in the early growth stage. Alfalfa cultivars with a high FD rating have longer internodes, whereas more dormant alfalfa cultivars have a larger number of internodes. There were tradeoffs between internode length and internode number in response to FD in alfalfa, which reflected certain scale-dependence.

Functional-structural plant models: a growing paradigm for plant studies

A number of research groups in various areas of plant biology as well as computer science and applied mathematics have addressed modelling the spatiotemporal dynamics of growth and development of plants. This has resulted in development of functional-structural plant models (FSPMs). In FSPMs, the plant structure is always explicitly represented in terms of a network of elementary units. In this respect, FSPMs are different from more abstract models in which a simplified representation of the plant structure is frequently used (e.g. spatial density of leaves, total biomass, etc.). This key feature makes it possible to build modular models and creates avenues for efficient exchange of model components and experimental data. They are being used to deal with the complex 3-D structure of plants and to simulate growth and development occurring at spatial scales from cells to forest areas, and temporal scales from seconds to decades and many plant generations. The plant types studied also cover a broad spectrum, from algae to trees. This special issue of Annals of Botany features selected papers on FSPM topics such as models of morphological development, models of physical and biological processes, integrated models predicting dynamics of plants and plant communities, modelling platforms, methods for acquiring the 3-D structures of plants using automated measurements, and practical applications for agronomic purposes.