3D segmentation of plant root systems using spatial pyramid pooling and locally adaptive field-of-view inference.

Background: The non-invasive 3D-imaging and successive 3D-segmentation of plant root systems has gained interest within fundamental plant research and selectively breeding resilient crops. Currently the state of the art consists of computed tomography (CT) scans and reconstruction followed by an adequate 3D-segmentation process. Challenge: Generating an exact 3D-segmentation of the roots becomes challenging due to inhomogeneous soil composition, as well as high scale variance in the root structures themselves. Approach: (1) We address the challenge by combining deep convolutional neural networks (DCNNs) with a weakly supervised learning paradigm. Furthermore, (2) we apply a spatial pyramid pooling (SPP) layer to cope with the scale variance of roots. (3) We generate a fine-tuned training data set with a specialized sub-labeling technique. (4) Finally, to yield fast and high-quality segmentations, we propose a specialized iterative inference algorithm, which locally adapts the field of view (FoV) for the network. Experiments: We compare our segmentation results against an analytical reference algorithm for root segmentation (RootForce) on a set of roots from Cassava plants and show qualitatively that an increased amount of root voxels and root branches can be segmented. Results: Our findings show that with the proposed DCNN approach combined with the dynamic inference, much more, and especially fine, root structures can be detected than with a classical analytical reference method. Conclusion: We show that the application of the proposed DCNN approach leads to better and more robust root segmentation, especially for very small and thin roots.

"Chamber #8" - a holistic approach of high-throughput non-destructive assessment of plant roots.

Introduction: In the past years, it has been observed that the breeding of plants has become more challenging, as the visible difference in phenotypic data is much smaller than decades ago. With the ongoing climate change, it is necessary to breed crops that can cope with shifting climatic conditions. To select good breeding candidates for the future, phenotypic experiments can be conducted under climate-controlled conditions. Above-ground traits can be assessed with different optical sensors, but for the root growth, access to non-destructively measured traits is much more challenging. Even though MRI or CT imaging techniques have been established in the past years, they rely on an adequate infrastructure for the automatic handling of the pots as well as the controlled climate. Methods: To address both challenges simultaneously, the non-destructive imaging of plant roots combined with a highly automated and standardized mid-throughput approach, we developed a workflow and an integrated scanning facility to study root growth. Our "chamber #8" contains a climate chamber, a material flow control, an irrigation system, an X-ray system, a database for automatic data collection, and post-processing. The goals of this approach are to reduce the human interaction with the various components of the facility to a minimum on one hand, and to automate and standardize the complete process from plant care via measurements to root trait calculation on the other. The user receives standardized phenotypic traits and properties that were collected objectively. Results: The proposed holistic approach allows us to study root growth of plants in a field-like substrate non-destructively over a defined period and to calculate phenotypic traits of root architecture. For different crops, genotypic differences can be observed in response to climatic conditions which have already been applied to a wide variety of root structures, such as potatoes, cassava, or corn. Discussion: It enables breeders and scientists non-destructive access to root traits. Additionally, due to the non-destructive nature of X-ray computed tomography, the analysis of time series for root growing experiments is possible and enables the observation of kinetic traits. Furthermore, using this automation scheme for simultaneously controlled plant breeding and non-destructive testing reduces the involvement of human resources.

X-Ray CT Phenotyping Reveals Bi-Phasic Growth Phases of Potato Tubers Exposed to Combined Abiotic Stress.

As a consequence of climate change, heat waves in combination with extended drought periods will be an increasing threat to crop yield. Therefore, breeding stress tolerant crop plants is an urgent need. Breeding for stress tolerance has benefited from large scale phenotyping, enabling non-invasive, continuous monitoring of plant growth. In case of potato, this is compromised by the fact that tubers grow belowground, making phenotyping of tuber development a challenging task. To determine the growth dynamics of tubers before, during and after stress treatment is nearly impossible with traditional destructive harvesting approaches. In contrast, X-ray Computed Tomography (CT) offers the opportunity to access belowground growth processes. In this study, potato tuber development from initiation until harvest was monitored by CT analysis for five different genotypes under stress conditions. Tuber growth was monitored three times per week via CT analysis. Stress treatment was started when all plants exhibited detectable tubers. Combined heat and drought stress was applied by increasing growth temperature for 2 weeks and simultaneously decreasing daily water supply. CT analysis revealed that tuber growth is inhibited under stress within a week and can resume after the stress has been terminated. After cessation of stress, tubers started growing again and were only slightly and insignificantly smaller than control tubers at the end of the experimental period. These growth characteristics were accompanied by corresponding changes in gene expression and activity of enzymes relevant for starch metabolism which is the driving force for tuber growth. Gene expression and activity of Sucrose Synthase (SuSy) reaffirmed the detrimental impact of the stress on starch biosynthesis. Perception of the stress treatment by the tubers was confirmed by gene expression analysis of potential stress marker genes whose applicability for potato tubers is further discussed. We established a semi-automatic imaging pipeline to analyze potato tuber delevopment in a medium thoughput (5 min per pot). The imaging pipeline presented here can be scaled up to be used in high-throughput phenotyping systems. However, the combination with automated data processing is the key to generate objective data accelerating breeding efforts to improve abiotic stress tolerance of potato genotypes.

Semiautomated 3D Root Segmentation and Evaluation Based on X-Ray CT Imagery.

BACKGROUND: Computed X-ray tomography (CTX) is a high-end nondestructive approach for the visual assessment of root architecture in soil. Nevertheless, in order to evaluate high-resolution CTX data of root architectures, manual segmentation of the depicted root systems from large-scale volume data is currently necessary, which is both time consuming and error prone. The duration of such a segmentation is of importance, especially for time-resolved growth analysis, where several instances of a plant need to be segmented and evaluated. Specifically, in our application, the contrast between soil and root data varies due to different growth stages and watering situations at the time of scanning. Additionally, the root system itself is expanding in length and in the diameter of individual roots. OBJECTIVE: For semiautomated and robust root system segmentation from CTX data, we propose the RootForce approach, which is an extension of Frangi's "multi-scale vesselness" method and integrates a 3D local variance. It allows a precise delineation of roots with diameters down to several µm in pots with varying diameters. Additionally, RootForce is not limited to the segmentation of small below-ground organs, but is also able to handle storage roots with a diameter larger than 40 voxels. RESULTS: Using CTX volume data of full-grown bean plants as well as time-resolved (3D + time) growth studies of cassava plants, RootForce produces similar (and much faster) results compared to manual segmentation of the regarded root architectures. Furthermore, RootForce enables the user to obtain traits not possible to be calculated before, such as total root volume (V root), total root length (L root), root volume over depth, root growth angles (θ min, θ mean, and θ max), root surrounding soil density D soil, or form fraction F. Discussion. The proposed RootForce tool can provide a higher efficiency for the semiautomatic high-throughput assessment of the root architectures of different types of plants from large-scale CTX. Furthermore, for all datasets within a growth experiment, only a single set of parameters is needed. Thus, the proposed tool can be used for a wide range of growth experiments in the field of plant phenotyping.

Migrating Shear Bands in Shaken Granular Matter.

When dense granular matter is sheared, the strain is often localized in shear bands. After some initial transient these shear bands become stationary. Here, we introduce a setup that periodically creates horizontally aligned shear bands which then migrate upward through the sample. Using x-ray radiography we demonstrate that this effect is caused by dilatancy, the reduction in volume fraction occurring in sheared dense granular media. Further on, we argue that these migrating shear bands are responsible for the previously reported periodic inflating and collapsing of the material.

Comparison of Achievable Contrast Features in Computed Tomography Observing the Growth of a 4H-SiC Bulk Crystal.

Today the physical vapor transport process is regularly applied for the growth of bulk SiC crystals. Due to the required high temperature of up to 2400 °C, and low gas pressure of several Mbar inside the crucible, the systems are encapsulated by several layers for heating, cooling and isolation inhibiting the operator from observing the growth. Also, the crucible itself is fully encapsulated to avoid impurities from being inserted into the crystal or disturbing the temperature field distribution. Thus, once the crucible has been set up with SiC powder and the seed crystal, the visible access to the progress of growth is limited. In the past, X-ray radiography has allowed this limitation to be overcome by placing the crucible in between an X-ray source and a radiographic film. Recently these two-dimensional attenuation signals have been extended to three-dimensional density distribution by the technique of computed tomography (CT). Beside the classic X-ray attenuation signal dominated by photoelectric effect, Compton effect and Rayleigh scattering, X-ray diffraction resulting in the crystalline structure of the 4H-SiC superimposes the reconstructed result. In this contribution, the achievable material contrast related to the level of X-ray energy and the absorption effects is analyzed using different CT systems with energies from 125 kV to 9 MeV. Furthermore the X-ray diffraction influence is shown by the comparison between the advanced helical-CT method and the classical 3D-CT.

Influence of Morphological Changes in a Source Material on the Growth Interface of 4h-Sic Single Crystals.

In this study, the change of mass distribution in a source material is tracked using an in situ computer tomography (CT) setup during the bulk growth of 4H- silicon carbide (SiC) via physical vapor depostion (PVT). The changing properties of the source material due to recrystallization and densification are evaluated. Laser flash measurement showed that the thermal properties of different regions of the source material change significantly before and after the growth run. The Si-depleted area at the bottom of the crucible is thermally insulating, while the residual SiC source showed increased thermal conductivity compared to the initially charged powder. Ex situ CT measurements revealed a needle-like structure with elongated pores causing anisotropic behavior for the heat conductivity. Models to assess the thermal conductivity are applied in order to calculate the changes in the temperature field in the crucible and the changes in growth kinetics are discussed.

Correction of beam hardening in X-ray radiograms.

The intensity of a monochromatic X-ray beam decreases exponentially with the distance it has traveled inside a material; this behavior is commonly referred to as Beer-Lambert's law. Knowledge of the material-specific attenuation coefficient µ allows us to determine the thickness of a sample from the intensity decrease the beam has experienced. However, classical X-ray tubes emit a polychromatic bremsstrahlung-spectrum. And the attenuation coefficients of all materials depend on the photon energy: photons with high energy are attenuated less than photons with low energy. In consequence, the X-ray spectrum changes while traveling through the medium; due to the relative increase in high energy photons, this effect is called beam hardening. For this varying spectrum, the Beer-Lambert law only remains valid if µ is replaced by an effective attenuation coefficient µeff which depends not only on the material but also on its thickness x and the details of the X-ray setup used. We present here a way to deduce µeff(x) from a small number of auxiliary measurements using a phenomenological model. This model can then be used to determine an unknown material thickness or in the case of a granular media its volume fraction.

Direct comparison of MRI and X-ray CT technologies for 3D imaging of root systems in soil: potential and challenges for root trait quantification.

BACKGROUND: Roots are vital to plants for soil exploration and uptake of water and nutrients. Root performance is critical for growth and yield of plants, in particular when resources are limited. Since roots develop in strong interaction with the soil matrix, tools are required that can visualize and quantify root growth in opaque soil at best in 3D. Two modalities that are suited for such investigations are X-ray Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Due to the different physical principles they are based on, these modalities have their specific potentials and challenges for root phenotyping. We compared the two methods by imaging the same root systems grown in 3 different pot sizes with inner diameters of 34 mm, 56 mm or 81 mm. RESULTS: Both methods successfully visualized roots of two weeks old bean plants in all three pot sizes. Similar root images and almost the same root length were obtained for roots grown in the small pot, while more root details showed up in the CT images compared to MRI. For the medium sized pot, MRI showed more roots and higher root lengths whereas at some spots thin roots were only found by CT and the high water content apparently affected CT more than MRI. For the large pot, MRI detected much more roots including some laterals than CT. CONCLUSIONS: Both techniques performed equally well for pots with small diameters which are best suited to monitor root development of seedlings. To investigate specific root details or finely graduated root diameters of thin roots, CT was advantageous as it provided the higher spatial resolution. For larger pot diameters, MRI delivered higher fractions of the root systems than CT, most likely because of the strong root-to-soil contrast achievable by MRI. Since complementary information can be gathered with CT and MRI, a combination of the two modalities could open a whole range of additional possibilities like analysis of root system traits in different soil structures or under varying soil moisture.