Positron emission tomography (PET) of radiotracer uptake and distribution in living plants: methodological aspects

Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives

Plant phenomics (PP) has been recognized as a bottleneck in studying the interactions of genomics and environment on plants, limiting the progress of smart breeding and precise cultivation. High-throughput plant phenotyping is challenging owing to the spatio-temporal dynamics of traits. Proximal and remote sensing (PRS) techniques are increasingly used for plant phenotyping because of their advantages in multi-dimensional data acquisition and analysis. Substantial progress of PRS applications in PP has been observed over the last two decades and is analyzed here from an interdisciplinary perspective based on 2972 publications. This progress covers most aspects of PRS application in PP, including patterns of global spatial distribution and temporal dynamics, specific PRS technologies, phenotypic research fields, working environments, species, and traits. Subsequently, we demonstrate how to link PRS to multi-omics studies, including how to achieve multi-dimensional PRS data acquisition and processing, how to systematically integrate all kinds of phenotypic information and derive phenotypic knowledge with biological significance, and how to link PP to multi-omics association analysis. Finally, we identify three future perspectives for PRS-based PP: (1) strengthening the spatial and temporal consistency of PRS data, (2) exploring novel phenotypic traits, and (3) facilitating multi-omics communication.

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.

Past and Future of Plant Stress Detection: An Overview From Remote Sensing to Positron Emission Tomography

Plant stress detection is considered one of the most critical areas for the improvement of crop yield in the compelling worldwide scenario, dictated by both the climate change and the geopolitical consequences of the Covid-19 epidemics. A complicated interconnection of biotic and abiotic stressors affect plant growth, including water, salt, temperature, light exposure, nutrients availability, agrochemicals, air and soil pollutants, pests and diseases. In facing this extended panorama, the technology choice is manifold. On the one hand, quantitative methods, such as metabolomics, provide very sensitive indicators of most of the stressors, with the drawback of a disruptive approach, which prevents follow up and dynamical studies. On the other hand qualitative methods, such as fluorescence, thermography and VIS/NIR reflectance, provide a non-disruptive view of the action of the stressors in plants, even across large fields, with the drawback of a poor accuracy. When looking at the spatial scale, the effect of stress may imply modifications from DNA level (nanometers) up to cell (micrometers), full plant (millimeters to meters), and entire field (kilometers). While quantitative techniques are sensitive to the smallest scales, only qualitative approaches can be used for the larger ones. Emerging technologies from nuclear and medical physics, such as computed tomography, magnetic resonance imaging and positron emission tomography, are expected to bridge the gap of quantitative non-disruptive morphologic and functional measurements at larger scale. In this review we analyze the landscape of the different technologies nowadays available, showing the benefits of each approach in plant stress detection, with a particular focus on the gaps, which will be filled in the nearby future by the emerging nuclear physics approaches to agriculture.

Expanding PET-applications in life sciences with positron-emitters beyond fluorine-18

Positron-emission-tomography (PET) has become an indispensable diagnostic tool in modern nuclear medicine. Its outstanding molecular imaging features allow repetitive studies on one individual and with high sensitivity, though no interference. Rather few positron-emitters with near favourable physical properties, i.e. carbon-11 and fluorine-18, furnished most studies in the beginning, preferably if covalently bound as isotopic label of small molecules. With the advancement of PET-devices the scope of in vivo research in life sciences and especially that of medical applications expanded, and other than "standard" PET-nuclides received increasing significance, like the radiometals copper-64 and gallium-68. Especially during the last decades, positron-emitters of other chemical elements have gotten into the focus of interest, concomitant with the technical advancements in imaging and radionuclide production. With known nuclear imaging properties and main production methods of emerging positron-emitters their usefulness for medical application is promising and even proven for several ones already. Unfortunate decay properties could be corrected for, and β+-emitters, especially with a longer half-life, provided new possibilities for application where slower processes are of importance. Further on, (bio)chemical features of positron-emitters of other elements, among there many metals, not only expanded the field of classical clinical investigations, but also opened up new fields of application. Appropriately labelled peptides, proteins and nanoparticles lend itself as newer probes for PET-imaging, e.g. in theragnostic or PET/MR hybrid imaging. Furthermore, the potential of non-destructive in-vivo imaging with positron-emission-tomography directs the view on further areas of life sciences. Thus, exploiting the excellent methodology for basic research on molecular biochemical functions and processes is increasingly encouraged as well in areas outside of health, such as plant and environmental sciences.

Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms

The study of phenomes or phenomics has been a central part of biology. The field of automatic phenotype acquisition technologies based on images has seen an important advance in the last years. As with other high-throughput technologies, it addresses a common set of problems, including data acquisition and analysis. In this review, we give an overview of the main systems developed to acquire images. We give an in-depth analysis of image processing with its major issues and the algorithms that are being used or emerging as useful to obtain data out of images in an automatic fashion.

Raman Hyperspectral Imaging for Detection of Watermelon Seeds Infected with Acidovorax citrulli

The bacterial infection of seeds is one of the most important quality factors affecting yield. Conventional detection methods for bacteria-infected seeds, such as biological, serological, and molecular tests, are not feasible since they require expensive equipment, and furthermore, the testing processes are also time-consuming. In this study, we use the Raman hyperspectral imaging technique to distinguish bacteria-infected seeds from healthy seeds as a rapid, accurate, and non-destructive detection tool. We utilize Raman hyperspectral imaging data in the spectral range of 400–1800 cm⁻¹ to determine the optimal band-ratio for the discrimination of watermelon seeds infected by the bacteria Acidovorax citrulli using ANOVA. Two bands at 1076.8 cm⁻¹ and 437 cm⁻¹ are selected as the optimal Raman peaks for the detection of bacteria-infected seeds. The results demonstrate that the Raman hyperspectral imaging technique has a good potential for the detection of bacteria-infected watermelon seeds and that it could form a suitable alternative to conventional methods.

Non-destructive evaluation of bacteria-infected watermelon seeds using visible/near-infrared hyperspectral imaging

BACKGROUND

There is a need to minimize economic damage by sorting infected seeds from healthy seeds before seeding. However, current methods of detecting infected seeds, such as seedling grow-out, enzyme-linked immunosorbent assays, the polymerase chain reaction (PCR) and the real-time PCR have a critical drawbacks in that they are time-consuming, labor-intensive and destructive procedures. The present study aimed to evaluate the potential of visible/near-infrared (Vis/NIR) hyperspectral imaging system for detecting bacteria-infected watermelon seeds.

RESULTS

A hyperspectral Vis/NIR reflectance imaging system (spectral region of 400-1000 nm) was constructed to obtain hyperspectral reflectance images for 336 bacteria-infected watermelon seeds, which were then subjected to partial least square discriminant analysis (PLS-DA) and a least-squares support vector machine (LS-SVM) to classify bacteria-infected watermelon seeds from healthy watermelon seeds. The developed system detected bacteria-infected watermelon seeds with an accuracy > 90% (PLS-DA: 91.7%, LS-SVM: 90.5%), suggesting that the Vis/NIR hyperspectral imaging system is effective for quarantining bacteria-infected watermelon seeds.

CONCLUSION

The results of the present study show that it is possible to use the Vis/NIR hyperspectral imaging system for detecting bacteria-infected watermelon seeds. © 2016 Society of Chemical Industry.

Imaging and analysis of thin structures using positron emission tomography: Thin phantoms and in vivo tobacco leaves study

In this work, a novel approach utilizing the designed phantoms imitating the plant tissues was applied for the evaluation of the relationships between the parameters of the prepared phantoms and/or quantitative variables obtained within the PET analysis. The microPET system developed for animal objects and approaches used made it possible to obtain the quantitative data in the form of (18)F radioactivity as well as the glucose (in µg) accumulated in leaf tissues within the dynamic in vivo study.

Applications of 2-deoxy-2-fluoro-D-glucose (FDG) in Plant Imaging: Past, Present, and Future

The aim of this review article is to explore and establish the current status of 2-deoxy-2-fluoro-D-glucose (FDG) applications in plant imaging. In the present article, we review the previous literature on its experimental merits to formulate a consistent and inclusive picture of FDG applications in plant-imaging research. 2-deoxy-2-fluoro-D-glucose is a [(18)F]fluorine-labeled glucose analog in which C-2 hydroxyl group has been replaced by a positron-emitting [(18)F] radioisotope. As FDG is a positron-emitting radiotracer, it could be used in in vivo imaging studies. FDG mimics glucose chemically and structurally. Its uptake and distribution are found to be similar to those of glucose in animal models. FDG is commonly used as a radiotracer for glucose in medical diagnostics and in vivo animal imaging studies but rarely in plant imaging. Tsuji et al. (2002) first reported FDG uptake and distribution in tomato plants. Later, Hattori et al. (2008) described FDG translocation in intact sorghum plants and suggested that it could be used as a tracer for photoassimilate translocation in plants. These findings raised interest among other plant scientists, which has resulted in a recent surge of articles involving the use of FDG as a tracer in plants. There have been seven studies describing FDG-imaging applications in plants. These studies describe FDG applications ranging from monitoring radiotracer translocation to analyzing solute transport, root uptake, photoassimilate tracing, carbon allocation, and glycoside biosynthesis. Fatangare et al. (2015) recently characterized FDG metabolism in plants; such knowledge is crucial to understanding and validating the application of FDG in plant imaging research. Recent FDG studies significantly advance our understanding of FDG translocation and metabolism in plants but also raise new questions. Here, we take a look at all the previous results to form a comprehensive picture of FDG translocation, metabolism, and applications in plants. In conclusion, we summarize current knowledge, discuss possible implications and limitations of previous studies, point to open questions in the field, and comment on the outlook for FDG applications in plant imaging.

Mathematical modeling of positron emission tomography (PET) data to assess radiofluoride transport in living plants following petiolar administration

BACKGROUND

Ion transport is a fundamental physiological process that can be studied non-invasively in living plants with radiotracer imaging methods. Fluoride is a known phytotoxic pollutant and understanding its transport in plants after leaf absorption is of interest to those in agricultural areas near industrial sources of airborne fluoride. Here we report the novel use of a commercial, high-resolution, animal positron emission tomography (PET) scanner to trace a bolus of [(18)F]fluoride administered via bisected petioles of Brassica oleracea, an established model species, to simulate whole plant uptake of atmospheric fluoride. This methodology allows for the first time mathematical compartmental modeling of fluoride transport in the living plant. Radiotracer kinetics in the stem were described with a single-parameter free- and trapped-compartment model and mean arrival times at different stem positions were calculated from the free-compartment time-activity curves.

RESULTS

After initiation of administration at the bisected leaf stalk, [(18)F] radioactivity climbed for approximately 10 minutes followed by rapid washout from the stem and equilibration within leaves. Kinetic modeling of transport in the stem yielded a trapping rate of 1.5 +/- 0.3%/min (mean +/- s.d., n = 3), velocity of 2.2 +/- 1.1 cm/min, and trapping fraction of 0.8 +/- 0.5%/cm.

CONCLUSION

Quantitative assessment of physiologically meaningful transport parameters of fluoride in living plants is possible using standard positron emission tomography in combination with petiolar radiotracer administration. Movement of free fluoride was observed to be consistent with bulk flow in xylem, namely a rapid and linear change in position with respect to time. Trapping, likely in the apoplast, was observed. Future applications of the methods described here include studies of transport of other ions and molecules of interest in plant physiology.