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

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.

Mechanistic modeling reveals the importance of turgor-driven apoplastic water transport in wheat stem parenchyma during carbohydrate mobilization

During stem elongation, wheat (Triticum aestivum) increases its stem carbohydrate content before anthesis as a reserve for grain filling. Hydraulic functioning during this mobilization process is not well understood, and contradictory results exist on the direct effect of drought on carbohydrate mobilization. In a dedicated experiment, wheat plants were subjected to drought stress during carbohydrate mobilization. Measurements, important to better understand stem physiology, showed some unexpected patterns that could not be explained by our current knowledge on water transport. Traditional water flow and storage models failed to properly describe the drought response in wheat stems during carbohydrate mobilization. To explain the measured patterns, hypotheses were formulated and integrated in a dedicated model for wheat. The new mechanistic model simulates two hypothetical water storage compartments: one where water is quickly exchanged with the xylem and one that contains the carbohydrate storage. Water exchange between these compartments is turgor-driven. The model was able to simulate the measured increase in stored carbohydrate concentrations with a decrease in water content and stem diameter. Calibration of the model showed the importance of turgor-driven apoplastic water flow during carbohydrate mobilization. This resulted in an increase in stem hydraulic capacitance, which became more important under drought stress.

Turgor-limited predictions of tree growth, height and metabolic scaling over tree lifespans

Increasing evidence suggests that tree growth is sink-limited by environmental and internal controls rather than by carbon availability. However, the mechanisms underlying sink-limitations are not fully understood and thus not represented in large-scale vegetation models. We develop a simple, analytically solved, mechanistic, turgor-driven growth model (TDGM) and a phloem transport model (PTM) to explore the mechanics of phloem transport and evaluate three hypotheses. First, phloem transport must be explicitly considered to accurately predict turgor distributions and thus growth. Second, turgor-limitations can explain growth-scaling with size (metabolic scaling). Third, turgor can explain realistic growth rates and increments. We show that mechanistic, sink-limited growth schemes based on plant turgor limitations are feasible for large-scale model implementations with minimal computational demands. Our PTM predicted nearly uniform sugar concentrations along the phloem transport path regardless of phloem conductance, stem water potential gradients and the strength of sink-demands contrary to our first hypothesis, suggesting that phloem transport is not limited generally by phloem transport capacity per se but rather by carbon demand for growth and respiration. These results enabled TDGM implementation without explicit coupling to the PTM, further simplifying computation. We test the TDGM by comparing predictions of whole-tree growth rate to well-established observations (site indices) and allometric theory. Our simple TDGM predicts realistic tree heights, growth rates and metabolic scaling over decadal to centurial timescales, suggesting that tree growth is generally sink and turgor limited. Like observed trees, our TDGM captures tree-size- and resource-based deviations from the classical ¾ power-law metabolic scaling for which turgor is responsible.

Integrating terrestrial laser scanning with functional-structural plant models to investigate ecological and evolutionary processes of forest communities

BACKGROUND

Woody plants (trees and shrubs) play an important role in terrestrial ecosystems, but their size and longevity make them difficult subjects for traditional experiments. In the last 20 years functional-structural plant models (FSPMs) have evolved: they consider the interplay between plant modular structure, the immediate environment and internal functioning. However, computational constraints and data deficiency have long been limiting factors in a broader application of FSPMs, particularly at the scale of forest communities. Recently, terrestrial laser scanning (TLS), has emerged as an invaluable tool for capturing the 3-D structure of forest communities, thus opening up exciting opportunities to explore and predict forest dynamics with FSPMs.

SCOPE

The potential synergies between TLS-derived data and FSPMs have yet to be fully explored. Here, we summarize recent developments in FSPM and TLS research, with a specific focus on woody plants. We then evaluate the emerging opportunities for applying FSPMs in an ecological and evolutionary context, in light of TLS-derived data, with particular consideration of the challenges posed by scaling up from individual trees to whole forests. Finally, we propose guidelines for incorporating TLS data into the FSPM workflow to encourage overlap of practice amongst researchers.

CONCLUSIONS

We conclude that TLS is a feasible tool to help shift FSPMs from an individual-level modelling technique to a community-level one. The ability to scan multiple trees, of multiple species, in a short amount of time, is paramount to gathering the detailed structural information required for parameterizing FSPMs for forest communities. Conventional techniques, such as repeated manual forest surveys, have their limitations in explaining the driving mechanisms behind observed patterns in 3-D forest structure and dynamics. Therefore, other techniques are valuable to explore how forests might respond to environmental change. A robust synthesis between TLS and FSPMs provides the opportunity to virtually explore the spatial and temporal dynamics of forest communities.

Turgor-time controls grass leaf elongation rate and duration under drought stress

The process of leaf elongation in grasses is characterized by the creation and transformation of distinct cell zones. The prevailing turgor pressure within these cells is one of the key drivers for the rate at which these cells divide, expand and differentiate, processes that are heavily impacted by drought stress. In this article, a turgor-driven growth model for grass leaf elongation is presented, which combines mechanistic growth from the basis of turgor pressure with the ontogeny of the leaf. Drought-induced reductions in leaf turgor pressure result in a simultaneous inhibition of both cell expansion and differentiation, lowering elongation rate but increasing elongation duration due to the slower transitioning of cells from the dividing and elongating zone to mature cells. Leaf elongation is, therefore, governed by the magnitude of, and time spent under, growth-enabling turgor pressure, a metric which we introduce as turgor-time. Turgor-time is able to normalize growth patterns in terms of varying water availability, similar to how thermal time is used to do so under varying temperatures. Moreover, additional inclusion of temperature dependencies within our model pioneers a novel concept enabling the general expression of growth regardless of water availability or temperature.

Quartz Crystal Microbalance with Dissipation Monitoring of Dynamic Viscoelastic Changes of Tobacco BY-2 Cells under Different Osmotic Conditions

The plant cell mechanics, including turgor pressure and wall mechanical properties, not only determine the growth of plant cells, but also reflect the functional and structural changes of plant cells under biotic and abiotic stresses. However, there are currently no appropriate techniques allowing to monitor the complex mechanical properties of living plant cells non-invasively and continuously. In this work, quartz crystal microbalance with dissipation (QCM-D) monitoring technique with overtones (3-9) was used for the dynamic monitoring of adhesions of living tobacco BY-2 cells onto positively charged N,N-dimethyl-N-propenyl-2-propen-1-aminiumchloride homopolymer (PDADMAC)/SiO2 QCM crystals under different concentrations of mannitol (CM) and the subsequent effects of osmotic stresses. The cell viscoelastic index (CVIn) (CVIn = ΔD⋅n/ΔF) was used to characterize the viscoelastic properties of BY-2 cells under different osmotic conditions. Our results indicated that lower overtones of QCM could detect both the cell wall and cytoskeleton structures allowing the detection of plasmolysis phenomena; whereas higher overtones could only detect the cell wall's mechanical properties. The QCM results were further discussed with the morphological changes of the BY-2 cells by an optical microscopy. The dynamic changes of cell's generated forces or cellular structures of plant cells caused by external stimuli (or stresses) can be traced by non-destructive and dynamic monitoring of cells' viscoelasticity, which provides a new way for the characterization and study of plant cells. QCM-D could map viscoelastic properties of different cellular structures in living cells and could be used as a new tool to test the mechanical properties of plant cells.

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.