Studying in vivo dynamics of xylem-transported 11CO2 using positron emission tomography

Kinetically Consistent Data Assimilation for Plant PET Sparse Time Activity Curve Signals

Time activity curve (TAC) signal processing in plant positron emission tomography (PET) is a frontier nuclear science technique to bring out the quantitative fluid dynamic (FD) flow parameters of the plant vascular system and generate knowledge on crops and their sustainable management, facing the accelerating global climate change. The sparse space-time sampling of the TAC signal impairs the extraction of the FD variables, which can be determined only as averaged values with existing techniques. A data-driven approach based on a reliable FD model has never been formulated. A novel sparse data assimilation digital signal processing method is proposed, with the unique capability of a direct computation of the dynamic evolution of noise correlations between estimated and measured variables, by taking into explicit account the numerical diffusion due to the sparse sampling. The sequential time-stepping procedure estimates the spatial profile of the velocity, the diffusion coefficient and the compartmental exchange rates along the plant stem from the TAC signals. To illustrate the performance of the method, we report an example of the measurement of transport mechanisms in zucchini sprouts.

Design Study of a Novel Positron Emission Tomography System for Plant Imaging

Positron Emission Tomography is a non-disruptive and high-sensitive digital imaging technique which allows to measure in-vivo and non invasively the changes of metabolic and transport mechanisms in plants. When it comes to the early assessment of stress-induced alterations of plant functions, plant PET has the potential of a major breakthrough. The development of dedicated plant PET systems faces a series of technological and experimental difficulties, which make conventional clinical and preclinical PET systems not fully suitable to agronomy. First, the functional and metabolic mechanisms of plants depend on environmental conditions, which can be controlled during the experiment if the scanner is transported into the growing chamber. Second, plants need to be imaged vertically, thus requiring a proper Field Of View. Third, the transverse Field of View needs to adapt to the different plant shapes, according to the species and the experimental protocols. In this paper, we perform a simulation study, proposing a novel design of dedicated plant PET scanners specifically conceived to address these agronomic issues. We estimate their expected sensitivity, count rate performance and spatial resolution, and we identify these specific features, which need to be investigated when realizing a plant PET scanner. Finally, we propose a novel approach to the measurement and verification of the performance of plant PET systems, including the design of dedicated plant phantoms, in order to provide a standard evaluation procedure for this emerging digital imaging agronomic technology.

Efflux and assimilation of xylem-transported CO2 in stems and leaves of tree species with different wood anatomy

Determining the fate of CO₂ respired in woody tissues is necessary to understand plant respiratory physiology and to evaluate CO₂ recycling mechanisms. An aqueous ¹³ C-enriched CO₂ solution was infused into the stem of 3-4 m tall trees to estimate efflux and assimilation of xylem-transported CO₂ via cavity ring-down laser spectroscopy and isotope ratio mass spectrometry, respectively. Different tree locations (lower stem, upper stem and leafy shoots) and tissues (xylem, bark and leaves) were monitored in species with tracheid, diffuse- and ring-porous wood anatomy (cedar, maple and oak, respectively). Radial xylem CO₂ diffusivity and xylem [CO₂ ] were lower in cedar relative to maple and oak trees, thereby limiting label diffusion. Part of the labeled ¹³ CO₂ was assimilated in cedar (8.7%) and oak (20.6%) trees, mostly in xylem and bark tissues of the stem, while limited solution uptake in maple trees hindered the detection of label assimilation. Little label reached foliar tissues, suggesting substantial label loss along the stem-branch transition following reductions in the radial diffusive pathway. Differences in respiration rates and radial xylem CO₂ diffusivity (lower in conifer relative to angiosperm species) might reconcile discrepancies in efflux and assimilation of xylem-transported CO₂ so far observed between taxonomic clades.

Non-invasive 11C-Imaging Revealed the Spatiotemporal Variability in the Translocation of Photosynthates Into Strawberry Fruits in Response to Increasing Daylight Integrals at Leaf Surface

The efficiency of photosynthate translocation from leaves to fruits directly affects dry matter partitioning. Therefore, controlling photosynthate translocation dynamics is critical for high-yield and high-quality fruit production. Accordingly, photosynthate translocation changes must be characterized using data obtained at a higher spatiotemporal resolution than those provided by conventional methods. In this study, ¹¹C-photosynthate translocation into strawberry (Fragaria × ananassa Duch.) fruits in individual plants was visualized non-invasively and repeatedly using a positron emission tracer imaging system (PETIS) to assess the spatiotemporal variability in the translocation dynamics in response to increasing daylight integrals (i.e., 0.5-, 4.5-, and 9-h exposures to 400 μmol m^-2 s^-1 at the leaf surface). Serial images of photosynthate translocation into strawberry fruits obtained from the PETIS confirmed that ¹¹C-photosynthates were translocated heterogeneously into each fruit on the same inflorescence. The amount of translocated ¹¹C-photosynthates and the translocation rate into each fruit significantly increased as the integrated light intensity at the leaf surface increased. An analysis of the pedicel of each fruit also confirmed that the photosynthate translocation rate increased. The cumulated photosynthesis in leaves increased almost linearly during the light period, suggesting that an increase in the amount of photosynthates in leaves promotes the translocation of photosynthates from leaves, resulting in an increase in the photosynthate translocation rate in pedicels and enhanced photosynthate accumulation in fruits. Additionally, the distribution pattern of photosynthate translocated to fruits did not change during the light period, nor did the order of the sink activity (¹¹C radioactivity/fruit dry weight), which is the driving force for the prioritization of the ¹¹C-partitioning between competing organs, among fruits. Thus, this is the first study to use ¹¹C-radioisotopes to clarify the spatiotemporal variability in photosynthate translocation from source leaves to individual sink fruits in vivo in response to increasing daylight integrals at a high spatiotemporal resolution.

Guide to Plant-PET Imaging Using 11CO2

Due to its high sensitivity and specificity for tumor detection, positron emission tomography (PET) has become a standard and widely used molecular imaging technique. Given the popularity of PET, both clinically and preclinically, its use has been extended to study plants. However, only a limited number of research groups worldwide report PET-based studies, while we believe that this technique has much more potential and could contribute extensively to plant science. The limited application of PET may be related to the complexity of putting together methodological developments from multiple disciplines, such as radio-pharmacology, physics, mathematics and engineering, which may form an obstacle for some research groups. By means of this manuscript, we want to encourage researchers to study plants using PET. The main goal is to provide a clear description on how to design and execute PET scans, process the resulting data and fully explore its potential by quantification via compartmental modeling. The different steps that need to be taken will be discussed as well as the related challenges. Hereby, the main focus will be on, although not limited to, tracing 11CO2 to study plant carbon dynamics.