Visualization of internal 3D structure of small live seed on germination by laboratory-based X-ray microscopy with phase contrast computed tomography

Toward robust and high-throughput detection of seed defects in X-ray images via deep learning

BACKGROUND

The detection of internal defects in seeds via non-destructive imaging techniques is a topic of high interest to optimize the quality of seed lots. In this context, X-ray imaging is especially suited. Recent studies have shown the feasibility of defect detection via deep learning models in 3D tomography images. We demonstrate the possibility of performing such deep learning-based analysis on 2D X-ray radiography for a faster yet robust method via the X-Robustifier pipeline proposed in this article.

RESULTS

2D X-ray images of both defective and defect-free seeds were acquired. A deep learning model based on state-of-the-art object detection neural networks is proposed. Specific data augmentation techniques are introduced to compensate for the low ratio of defects and increase the robustness to variation of the physical parameters of the X-ray imaging systems. The seed defects were accurately detected (F1-score >90%), surpassing human performance in computation time and error rates. The robustness of these models against the principal distortions commonly found in actual agro-industrial conditions is demonstrated, in particular, the robustness to physical noise, dimensionality reduction and the presence of seed coating.

CONCLUSION

This work provides a full pipeline to automatically detect common defects in seeds via 2D X-ray imaging. The method is illustrated on sugar beet and faba bean and could be efficiently extended to other species via the proposed generic X-ray data processing approach (X-Robustifier). Beyond a simple proof of feasibility, this constitutes important results toward the effective use in the routine of deep learning-based automatic detection of seed defects.

New Growth-Related Features of Wheat Grain Pericarp Revealed by Synchrotron-Based X-ray Micro-Tomography and 3D Reconstruction

Wheat (Triticum aestivum L.) is one of the most important crops as it provides 20% of calories and proteins to the human population. To overcome the increasing demand in wheat grain production, there is a need for a higher grain yield, and this can be achieved in particular through an increase in the grain weight. Moreover, grain shape is an important trait regarding the milling performance. Both the final grain weight and shape would benefit from a comprehensive knowledge of the morphological and anatomical determinism of wheat grain growth. Synchrotron-based phase-contrast X-ray microtomography (X-ray µCT) was used to study the 3D anatomy of the growing wheat grain during the first developmental stages. Coupled with 3D reconstruction, this method revealed changes in the grain shape and new cellular features. The study focused on a particular tissue, the pericarp, which has been hypothesized to be involved in the control of grain development. We showed considerable spatio-temporal diversity in cell shape and orientations, and in tissue porosity associated with stomata detection. These results highlight the growth-related features rarely studied in cereal grains, which may contribute significantly to the final grain weight and shape.

Automated extraction of pod phenotype data from micro-computed tomography

INTRODUCTION

Plant image datasets have the potential to greatly improve our understanding of the phenotypic response of plants to environmental and genetic factors. However, manual data extraction from such datasets are known to be time-consuming and resource intensive. Therefore, the development of efficient and reliable machine learning methods for extracting phenotype data from plant imagery is crucial.

METHODS

In this paper, a current gold standard computed vision method for detecting and segmenting objects in three-dimensional imagery (StartDist-3D) is applied to X-ray micro-computed tomography scans of oilseed rape (Brassica napus) mature pods.

RESULTS

With a relatively minimal training effort, this fine-tuned StarDist-3D model accurately detected (Validation F1-score = 96.3%,Testing F1-score = 99.3%) and predicted the shape (mean matched score = 90%) of seeds.

DISCUSSION

This method then allowed rapid extraction of data on the number, size, shape, seed spacing and seed location in specific valves that can be integrated into models of plant development or crop yield. Additionally, the fine-tuned StarDist-3D provides an efficient way to create a dataset of segmented images of individual seeds that could be used to further explore the factors affecting seed development, abortion and maturation synchrony within the pod. There is also potential for the fine-tuned Stardist-3D method to be applied to imagery of seeds from other plant species, as well as imagery of similarly shaped plant structures such as beans or wheat grains, provided the structures targeted for detection and segmentation can be described as star-convex polygons.

A high-resolution study of PM2.5 accumulation inside leaves in leaf stomata compared with non-stomatal areas using three-dimensional X-ray microscopy

Plant leaves retain atmospheric particulate matter (PM) on their surfaces, helping PM removal and risk reduction of respiratory tract infection. Several processes (deposition, resuspension, rainfall removal) can influence the PM accumulation on leaves and different leaf microstructures (e.g., trichomes, epicuticular waxes) can also be involved in retaining PM. However, the accumulation and distribution of PM on leaves, particularly at the stomata, are unclear, and the lack of characterization methods limits our understanding of this process. Thus, in this study, we aimed to explore the pathway through which PM_2.5 (aerodynamic diameter ≤ 2.5 μm) enters plant leaves, and the penetration depth of PM_2.5 along the entry route. Here, an indoor experiment using diamond powder as a tracer to simulate PM_2.5 deposition on leaves was carried out. Then, the treated and non-treated leaves were scanned by using three-dimensional (3D) X-ray microscopy. Next, the grayscale value of the scanned images was used to compare PM_2.5 accumulation in stomatal and non-stomatal areas of the treated and non-treated leaves, respectively. Finally, a total PM_2.5 volume from the abaxial epidermis was calculated. The results showed that, first, a large amount of PM_2.5 accumulates within leaf stomata, whereas PM_2.5 does not accumulate at non-stomatal areas. Then, the penetration depth of PM_2.5 in stomata of most tree species was 5-14 μm from the abaxial epidermis. For the first time, 3D X-ray microscope scanning was used to confirm that a pathway by which PM_2.5 enters the leaves is through the stomata, which is fundamental for further research on how PM_2.5 translocates and interacts with tissues and cells in leaves.

Compact laboratory-based X-ray microscope enabling nondestructive 3D structure acquisition of mouse nephron with high speed and better user accessibility

X-ray microscopes adopting computed tomography enable nondestructive 3D visualization of biological specimens at micron-level resolution without conventional 2D serial sectioning that is a destructive/laborious method and is routinely used for analyzing renal biopsy in clinical diagnosis of kidney diseases. Here we applied a compact commercial system of laboratory-based X-ray microscope to observe a resin-embedded osmium-stained 1-mm strip of a mouse kidney piece as a model of renal biopsy, toward a more efficient diagnosis of kidney diseases. A reconstructed computed tomography image from several hours of data collection using CCD detector allowed us to unambiguously segment a single nephron connected to a renal corpuscle, which was consistent with previous reports using serial sectioning. Histogram analysis on the segmented nephron confirmed that the proximal and distal tubules were distinguishable on the basis of their X-ray opacities. A 3D rendering model of the segmented nephron visualized a convoluted structure of renal tubules neighboring the renal corpuscle and a branched structure of efferent arterioles. Furthermore, another data collection using scientific complementary metal-oxide semiconductor detector with a much shorter data acquisition time of 15 min provided similar results from the same samples. These results suggest a potential application of the compact laboratory-based X-ray microscope to analyze mouse renal biopsy.

Nondestructive cellular-level 3D observation of mouse kidney using laboratory-based X-ray microscopy with paraffin-mediated contrast enhancement

For three-dimensional observation of unstained bio-specimens using X-ray microscopy with computed tomography (CT), one main problem has been low contrast in X-ray absorption. Here we introduce paraffin-mediated contrast enhancement to visualize biopsy samples of mouse kidney using a laboratory-based X-tray microscope. Unlike conventional heavy-atom staining, paraffin-mediated contrast enhancement uses solid paraffin as a negative contrast medium to replace water in the sample. The medium replacement from water to paraffin effectively lowers the absorption of low-energy X-rays by the medium, which eventually enhances the absorption contrast between the medium and tissue. In this work, paraffin-mediated contrast enhancement with 8 keV laboratory X-rays was used to visualize cylindrical renal biopsies with diameters of about 0.5 mm. As a result, reconstructed CT images from 19.4 h of data collection achieved cellular-level resolutions in all directions, which provided 3D structures of renal corpuscles from a normal mouse and from a disease model mouse. These two structures with and without disease allowed a volumetric analysis showing substantial volume differences in glomerular subregions. Notably, this nondestructive method presents CT opacities reflecting elemental composition and density of unstained tissues, thereby allowing more unbiased interpretation on their biological structures.

Non-destructive analysis of hollow-shaped single fibers using X-ray computed tomography

A commercial high-resolution X-ray computed tomography (CT) was utilized for non-destructive analysis of single fibers. The micro-CT apparatus was employed because it is applicable to both colored and colorless fibers. A sample preparation using adhesive sheets was demonstrated, and the method is similar to typical tape-lift sample collection method in crime cases. Different cross-sectional shapes of nylon and polyester single fibers were non-destructively distinguished, and the method is applicable to all types of fibers. Cross-sectional areas, aperture ratios, and volumes of individual fibers were directly and automatically measured using the open-source software. The observed parameters were within a coefficient of variation of 3%. In addition, a mass of a single fragment of a fiber can be estimated when the local density is given.

Synchrotron Based X-ray Microtomography Reveals Cellular Morphological Features of Developing Wheat Grain

Wheat is one of the most important crops in the world, mainly used for human consumption and animal feed. To overcome the increasing demand in wheat production, it is necessary to better understand the mechanisms involved in the growth of the wheat grain. X-ray computed tomography is an efficient method for the non-destructive investigation of the 3D architecture of biological specimens, which does not require staining, sectioning, or inclusion. In particular, phase-contrast tomography results in images with better contrast and an increased resolution compared to that obtained with laboratory tomography devices. The aim of this study was to investigate the potential of phase-contrast tomography for the study of the anatomy of the wheat grain at early stages of development. We provided 3D images of entire grains at various development stages. The image analysis allowed identifying a large number of tissues, and to visualize individual cells. Using a high-resolution setup, finer details were obtained, making it possible to identify additional tissues. Three-dimensional rendering of the grain also revealed the pattern resulting from the epidermis cells. X-ray phase-contrast tomography appears as a promising imaging method for the study of the 3D anatomy of plant organs and tissues.

X-ray computed tomography for 3D plant imaging

X-ray computed tomography (CT) is a valuable tool for 3D imaging of plant tissues and organs. Applications include the study of plant development and organ morphogenesis, as well as modeling of transport processes in plants. Some challenges remain, however, including attaining higher contrast for easier quantification, increasing the resolution for imaging subcellular features, and decreasing image acquisition and processing time for high-throughput phenotyping. In addition, phase contrast, multispectral, dark-field, soft X-ray, and time-resolved imaging are emerging. At the same time, a large amount of 3D image data are becoming available, posing challenges for data management. We review recent advances in the area of X-ray CT for plant imaging, and describe opportunities for using such images for studying transport processes in plants.

Microstructure investigation of plant architecture with X-ray microscopy

In recent years, the plant morphology has been well studied by multiple approaches at cellular and subcellular levels. Two-dimensional (2D) microscopy techniques offer imaging of plant structures on a wide range of magnifications for researchers. However, subcellular imaging is still challenging in plant tissues like roots and seeds. Here we use a three-dimensional (3D) imaging technology based on the X-ray microscope (XRM) and analyze several plant tissues from different plant species. The XRM provides new insights into plant structures using non-destructive imaging at high-resolution and high contrast. We also utilized a workflow aiming to acquire accurate and high-quality images in the context of the whole specimen. Multiple plant samples including rice, tobacco, Arabidopsis and maize were used to display the differences of phenotypes. Our work indicates that the XRM is a powerful tool to investigate plant microstructure in high-resolution scale. Our work also provides evidence that evaluate and quantify tissue specific differences for a range of plant species. We also characterize novel plant tissue phenotypes by the XRM, such as seeds in Arabidopsis, and utilize them for novel observation measurement. Our work represents an evaluated spatial and temporal resolution solution on seed observation and screening.

Magnetopriming effects on arsenic stress-induced morphological and physiological variations in soybean involving synchrotron imaging

This study investigates the effect of static magnetic field (SMF) pre-treatment in ameliorating arsenic (As) toxicity in soybean plants in relation to growth, photosynthesis and water transport through leaf venation. Soybean (Glycine max variety JS-9560) seeds pre-treated with SMF (200 mT for 1 h) were grown in four levels of arsenate-polluted soil (As(V); 0, 5, 10 and 50 mg kg-1 ) in order to find out the impact of magnetopriming on plant tolerance against As toxicity. Quantitative image analysis of soybean leaf venation showed a narrowing in the width of midrib with increasing As(V) contamination in non-primed seeds. The morphological variations are also supported by the physiological parameters such as reduction in efficiency of photosystem II, plant performance index, stomatal conductance and photosynthetic rate in the presence of As(V) for non-primed seeds. However, remarkable increase was observed in all the measured parameters by SMF pre-treatment at all the concentrations of As(V) used. Even for the highest concentration of As(V) (50 mg kg-1 soil), SMF pre-treatment caused significant enhancement in plant height (40%), area of third trifoliate leaves (40%), along with increase in width of the midrib (17%) and minor vein (13%), contributing to increase in the water uptake, that resulted in higher primary photochemistry of PSII (12%), performance index (50%), stomatal conductance (57%) and photosynthetic rate (33%) as compared to non-primed ones. Consequently, magnetopriming of dry seeds can be effectively used as pretreatment for reduction of As toxicity in soybean plants.

Preparation, Scanning and Analysis of Duckweed Using X-Ray Computed Microtomography

Quantification of anatomical and compositional features underpins both fundamental and applied studies of plant structure and function. Relatively few non-invasive techniques are available for aquatic plants. Traditional methods such as sectioning are low-throughput and provide 2-dimensional information. X-ray Computed Microtomography (μCT) offers a non-destructive method of three dimensional (3D) imaging in planta, but has not been widely used for aquatic species, due to the difficulties in sample preparation and handling. We present a novel sample handling protocol for aquatic plant material developed for μCT imaging, using duckweed plants and turions as exemplars, and compare the method against existing approaches. This technique allows for previously unseen 3D volume analysis of gaseous filled spaces, cell material, and sub-cellular features. The described embedding method, utilizing petrolatum gel for sample mounting, was shown to preserve sample quality during scanning, and to display sufficiently different X-ray attenuation to the plant material to be easily differentiated by image analysis pipelines. We present this technique as an improved method for anatomical structural analysis that provides novel cellular and developmental information.