In Vivo Imaging and Quantification of Carbon Tracer Dynamics in Nodulated Root Systems of Pea Plants.

Legumes associate with root colonizing rhizobia that provide fixed nitrogen to its plant host in exchange for recently fixed carbon. There is a lack of understanding of how individual plants modulate carbon allocation to a nodulated root system as a dynamic response to abiotic stimuli. One reason is that most approaches are based on destructive sampling, making quantification of localised carbon allocation dynamics in the root system difficult. We established an experimental workflow for routinely using non-invasive Positron Emission Tomography (PET) to follow the allocation of leaf-supplied 11C tracer towards individual nodules in a three-dimensional (3D) root system of pea (Pisum sativum). Nitrate was used for triggering a reduction of biological nitrogen fixation (BNF), which was expected to rapidly affect carbon allocation dynamics in the root-nodule system. The nitrate treatment led to a decrease in 11C tracer allocation to nodules by 40% to 47% in 5 treated plants while the variation in control plants was less than 11%. The established experimental pipeline enabled for the first time that several plants could consistently be labelled and measured using 11C tracers in a PET approach to quantify C-allocation to individual nodules following a BNF reduction. Our study demonstrates the strength of using 11C tracers in a PET approach for non-invasive quantification of dynamic carbon allocation in several growing plants over several days. A major advantage of the approach is the possibility to investigate carbon dynamics in small regions of interest in a 3D system such as nodules in comparison to whole plant development.

Model-Based Design of Long-Distance Tracer Transport Experiments in Plants.

Studies of long-distance transport of tracer isotopes in plants offer a high potential for functional phenotyping, but so far measurement time is a bottleneck because continuous time series of at least 1 h are required to obtain reliable estimates of transport properties. Hence, usual throughput values are between 0.5 and 1 samples h-1. Here, we propose to increase sample throughput by introducing temporal gaps in the data acquisition of each plant sample and measuring multiple plants one after each other in a rotating scheme. In contrast to common time series analysis methods, mechanistic tracer transport models allow the analysis of interrupted time series. The uncertainties of the model parameter estimates are used as a measure of how much information was lost compared to complete time series. A case study was set up to systematically investigate different experimental schedules for different throughput scenarios ranging from 1 to 12 samples h-1. Selected designs with only a small amount of data points were found to be sufficient for an adequate parameter estimation, implying that the presented approach enables a substantial increase of sample throughput. The presented general framework for automated generation and evaluation of experimental schedules allows the determination of a maximal sample throughput and the respective optimal measurement schedule depending on the required statistical reliability of data acquired by future experiments.

Quantitative trait loci controlling leaf venation in Arabidopsis.

Leaf veins provide the mechanical support and are responsible for the transport of nutrients and water to the plant. High vein density is a prerequisite for plants to have C4 photosynthesis. We investigated the genetic variation and genetic architecture of leaf venation traits within the species Arabidopsis thaliana using natural variation. Leaf venation traits, including leaf vein density (LVD) were analysed in 66 worldwide accessions and 399 lines of the multi-parent advanced generation intercross population. It was shown that there is no correlation between LVD and photosynthesis parameters within A. thaliana. Association mapping was performed for LVD and identified 16 and 17 putative quantitative trait loci (QTLs) in the multi-parent advanced generation intercross and worldwide sets, respectively. There was no overlap between the identified QTLs suggesting that many genes can affect the traits. In addition, linkage mapping was performed using two biparental recombinant inbred line populations. Combining linkage and association mapping revealed seven candidate genes. For one of the candidate genes, RCI2c, we demonstrated its function in leaf venation patterning.

Finite volume schemes for the numerical simulation of tracer transport in plants.

Compartmental models can be used for inverse modeling of long distance tracer transport experiments in plants. Such transport models describe axial convection and diffusion as well as exchange between compartments, and are defined by partial differential equations (PDEs). Since for inverse modeling, the forward simulation needs to be evaluated frequently, a fast PDE solver is required. Here, we compare several different finite volumes schemes up to fifth order for spatial discretization with respect to accuracy, computation time and numerical oscillations. The comparison has been performed using initial conditions with varying steepness, and periodic boundary conditions. For time discretization, standard fifth order Runge-Kutta methods are used. For smooth initial conditions, fifth order upwind schemes for spatial discretization yield the most precise and fast solutions. For higher steepness of the initial condition, higher order upwind schemes produce spurious oscillations while flux limiter schemes as well as weighted essentially non-oscillating (WENO) schemes can suppress these oscillations, at the expense of comparably slower convergence rates and higher computation times.

Quantitative 3D Analysis of Plant Roots Growing in Soil Using Magnetic Resonance Imaging.

Precise measurements of root system architecture traits are an important requirement for plant phenotyping. Most of the current methods for analyzing root growth require either artificial growing conditions (e.g. hydroponics), are severely restricted in the fraction of roots detectable (e.g. rhizotrons), or are destructive (e.g. soil coring). On the other hand, modalities such as magnetic resonance imaging (MRI) are noninvasive and allow high-quality three-dimensional imaging of roots in soil. Here, we present a plant root imaging and analysis pipeline using MRI together with an advanced image visualization and analysis software toolbox named NMRooting. Pots up to 117 mm in diameter and 800 mm in height can be measured with the 4.7 T MRI instrument used here. For 1.5 l pots (81 mm diameter, 300 mm high), a fully automated system was developed enabling measurement of up to 18 pots per day. The most important root traits that can be nondestructively monitored over time are root mass, length, diameter, tip number, and growth angles (in two-dimensional polar coordinates) and spatial distribution. Various validation measurements for these traits were performed, showing that roots down to a diameter range between 200 µm and 300 µm can be quantitatively measured. Root fresh weight correlates linearly with root mass determined by MRI. We demonstrate the capabilities of MRI and the dedicated imaging pipeline in experimental series performed on soil-grown maize (Zea mays) and barley (Hordeum vulgare) plants.

phenoVein-A Tool for Leaf Vein Segmentation and Analysis.

Precise measurements of leaf vein traits are an important aspect of plant phenotyping for ecological and genetic research. Here, we present a powerful and user-friendly image analysis tool named phenoVein. It is dedicated to automated segmenting and analyzing of leaf veins in images acquired with different imaging modalities (microscope, macrophotography, etc.), including options for comfortable manual correction. Advanced image filtering emphasizes veins from the background and compensates for local brightness inhomogeneities. The most important traits being calculated are total vein length, vein density, piecewise vein lengths and widths, areole area, and skeleton graph statistics, like the number of branching or ending points. For the determination of vein widths, a model-based vein edge estimation approach has been implemented. Validation was performed for the measurement of vein length, vein width, and vein density of Arabidopsis (Arabidopsis thaliana), proving the reliability of phenoVein. We demonstrate the power of phenoVein on a set of previously described vein structure mutants of Arabidopsis (hemivenata, ondulata3, and asymmetric leaves2-101) compared with wild-type accessions Columbia-0 and Landsberg erecta-0. phenoVein is freely available as open-source software.

Belowground plant development measured with magnetic resonance imaging (MRI): exploiting the potential for non-invasive trait quantification using sugar beet as a proxy.

Both structural and functional properties of belowground plant organs are critical for the development and yield of plants but, compared to the shoot, much more difficult to observe due to soil opacity. Many processes concerning the belowground plant performance are not fully understood, in particular spatial and temporal dynamics and their interrelation with environmental factors. We used Magnetic Resonance Imaging (MRI) as a noninvasive method to evaluate which traits can be measured when a complex plant organ is monitored in-vivo while growing in the soil. We chose sugar beet (Beta vulgaris ssp. vulgaris) as a model system. The beet consists mainly of root tissues, is rather complex regarding tissue structure and responses to environmental factors, and thereby a good object to test the applicability of MRI for 3D phenotyping approaches. Over a time period of up to 3 months, traits such as beet morphology or anatomy were followed in the soil and the effect of differently sized pots on beet fresh weight calculated from MRI data was studied. There was a clear positive correlation between the pot size and the increase in fresh weight of a sugar beet over time. Since knowledge of the development of internal beet structures with several concentric cambia, vascular and parenchyma rings is still limited, we consecutively acquired 3D volumetric images on individual plants using the MRI contrast parameter T2 to map the development of rings at the tissue level. This demonstrates that MRI provides versatile protocols to non-invasively measure plant traits in the soil. It opens new avenues to investigate belowground plant performance under adverse environmental conditions such as drought, nutrient shortage, or soil compaction to seek for traits of belowground organs making plants more resilient to stress.

A class of compartmental models for long-distance tracer transport in plants.

Studies of long-distance tracer transport in plants result in spatio-temporal data sets. Compartmental tracer transport models can be used to quantitatively characterize or compare such data sets derived from different experiments. Depending on the specific experimental situation it might be necessary to apply different models. Here, we present a general class of compartmental tracer transport models which allows a systematic comparison of different models regarding the quality of fitting to the experimental data. This model class is defined by a system of partial differential equations (PDEs) for an arbitrary number of parallel compartments with individual transport velocities and numerous lateral exchange connections. A large number of model instances with adjustable complexity can be derived from this model class by permitting only certain model parameters such as flux velocities or exchange rates between compartments to be non-zero. Since some of these models are either inconsistent or redundant we designed a model filter using combinatory rules in order to keep only valid and unique models. A numerical solver for the PDEs was implemented using finite volumes and a weighted essentially non-oscillatory (WENO) scheme. Several candidate models were fitted to experimental data using a Monte Carlo multi-start strategy to approximate the global optimum within a certain parameter space. Analysis of exemplary tracer transport experiments on sugar beet, radish and maize root resulted in different best models depending on the respective data and the required fit quality.

(11)C-PET imaging reveals transport dynamics and sectorial plasticity of oak phloem after girdling.

Carbon transport processes in plants can be followed non-invasively by repeated application of the short-lived positron-emitting radioisotope (11)C, a technique which has rarely been used with trees. Recently, positron emission tomography (PET) allowing 3D visualization has been adapted for use with plants. To investigate the effects of stem girdling on the flow of assimilates, leaves on first order branches of two-year-old oak (Quercus robur L.) trees were labeled with (11)C by supplying (11)CO2-gas to a leaf cuvette. Magnetic resonance imaging gave an indication of the plant structure, while PET registered the tracer flow in a stem region downstream from the labeled branches. After repeated pulse labeling, phloem translocation was shown to be sectorial in the stem: leaf orthostichy determined the position of the phloem sieve tubes containing labeled (11)C. The observed pathway remained unchanged for days. Tracer time-series derived from each pulse and analysed with a mechanistic model showed for two adjacent heights in the stem a similar velocity but different loss of recent assimilates. With either complete or partial girdling of bark within the monitored region, transport immediately stopped and then resumed in a new location in the stem cross-section, demonstrating the plasticity of sectoriality. One day after partial girdling, the loss of tracer along the interrupted transport pathway increased, while the velocity was enhanced in a non-girdled sector for several days. These findings suggest that lateral sugar transport was enhanced after wounding by a change in the lateral sugar transport path and the axial transport resumed with the development of new conductive tissue.

Analytical model for long-distance tracer-transport in plants.

Recent investigations of long-distance transport in plants using non-invasive tracer techniques such as (11)C radiolabeling monitored by positron emission tomography (PET) combined with magnetic resonance imaging (MRI) revealed the need of dedicated methods to allow a quantitative data analysis and comparison of such experiments. A mechanistic compartmental tracer transport model is presented, defined by a linear system of partial differential equations (PDEs). This model simplifies the complexity of axial transport and lateral exchanges in the transport pathways of plants (e.g. the phloem) by simulating transport and reversible exchange within three compartments using just a few parameters which are considered to be constant in space and time. For this system of PDEs an analytical solution in Fourier-space was found allowing a fast and numerically precise evaluation. From the steady-state behavior of the model, the system loss (steadily fixed tracer along the transport conduits) was derived as an additional parameter that can be readily interpreted in a physiological way. The presented framework allows the model to be fitted to spatio-temporal tracer profiles including error and sensitivity analysis of the estimated parameters. This is demonstrated for PET data sets obtained from radish, sugar beet and maize plants.

Combined MRI-PET dissects dynamic changes in plant structures and functions.

Unravelling the factors determining the allocation of carbon to various plant organs is one of the great challenges of modern plant biology. Studying allocation under close to natural conditions requires non-invasive methods, which are now becoming available for measuring plants on a par with those developed for humans. By combining magnetic resonance imaging (MRI) and positron emission tomography (PET), we investigated three contrasting root/shoot systems growing in sand or soil, with respect to their structures, transport routes and the translocation dynamics of recently fixed photoassimilates labelled with the short-lived radioactive carbon isotope (11)C. Storage organs of sugar beet (Beta vulgaris) and radish plants (Raphanus sativus) were assessed using MRI, providing images of the internal structures of the organs with high spatial resolution, and while species-specific transport sectoralities, properties of assimilate allocation and unloading characteristics were measured using PET. Growth and carbon allocation within complex root systems were monitored in maize plants (Zea mays), and the results may be used to identify factors affecting root growth in natural substrates or in competition with roots of other plants. MRI-PET co-registration opens the door for non-invasive analysis of plant structures and transport processes that may change in response to genomic, developmental or environmental challenges. It is our aim to make the methods applicable for quantitative analyses of plant traits in phenotyping as well as in understanding the dynamics of key processes that are essential to plant performance.

Non-invasive determination of plant biomass with microwave resonators.

Non-invasive and rapid determination of plant biomass would be beneficial for a number of research aims. Here, we present a novel device to non-invasively determine plant water content as a proxy for plant biomass. It is based on changes of dielectric properties inside a microwave cavity resonator induced by inserted plant material. The water content of inserted shoots leads to a discrete shift in the centre frequency of the resonator. Calibration measurements with pure water showed good spatial homogeneity in the detection volume of the microwave resonators and clear correlations between water content and centre frequency shift. For cut tomato and tobacco shoots, linear correlations between fresh weight and centre frequency shift were established. These correlations were used to continuously monitor diel growth patterns of intact plants and to determine biomass increase over several days. Interferences from soil and root water were excluded by shielding pots with copper. The presented proof of principle shows that microwave resonators are promising tools to quantitatively detect the water content of plants and to determine plant biomass. As the method is non-invasive, integrative and fast, it provides the opportunity for detailed, dynamic analyses of plant growth, water status and phenotype.