scholarly journals Connecting the dots between root cross-section images and modelling tools to create a high resolution root system hydraulic maps in Zea mays.

2020 ◽  
Author(s):  
Adrien Heymans ◽  
Valentin Couvreur ◽  
Guillaume Lobet
Keyword(s):  
Zea Mays ◽  
High Resolution ◽  
Hydraulic Conductivity ◽  
Root System ◽  
Cross Section ◽  
Hydraulic Properties ◽  
Root Anatomy ◽  
Root Pressure ◽  
Anatomical Features ◽  
Root Types

Root hydraulic properties play a central role in the global water cycle, agricultural systems productivity, and ecosystem survival as they impact the global canopy water supply. However, the available experimental methods to quantify root hydraulic conductivities, such as the root pressure probing, are particularly challenging and their applicability on thin roots and small root segments is limited. There is a gap in methods enabling easy estimations of root hydraulic conductivities across a diversity of root types and at high resolution along root axes. In this case study, we analysed Zea mays (maize) plants of the var. B73 that were grown in pots for 14 days. Root cross-section data were used to extract anatomical measurements. We used the Generator of Root Anatomy in R (GRANAR) model to generate root anatomical networks from anatomical features. Then we used the Model of Explicit Cross-section Hydraulic Anatomy (MECHA) to compute an estimation of the root axial and radial hydraulic conductivities (kx and kr, respectively), based on the generated anatomical networks and cell hydraulic properties from the literature. The root hydraulic conductivity maps obtained from the root cross-sections suggest significant functional variations along and between different root types. Predicted variations of kr along the root axis were strongly dependent on the maturation stage of hydrophobic barriers. The same was also true for the maturation rates of the metaxylem. The different anatomical features, as well as their evolution along the root type add significant variation to the kr estimation in between root type and along the root axe. Under the prism of root types, anatomy, and hydrophobic barriers, our results highlight the diversity of root radial and axial hydraulic conductivities, which may be veiled under low-resolution measurements of the root system hydraulic conductivity. While predictions of our root hydraulic maps match the range and trend of measurements reported in the literature, future studies could focus on the quantitative validation of hydraulic maps. From now on, a novel method, which turns root cross-section images into hydraulic maps will offer an inexpensive and easily applicable investigation tool for root hydraulics, in parallel to root pressure probing experiments.

scholarly journals Root Anatomy based on Root Cross-Section Image Analysis with Deep Learning

2018 ◽  
Author(s):  
Chaoxin Wang ◽  
Xukun Li ◽  
Doina Caragea ◽  
Raju Bheemanahalli ◽  
S.V. Krishna Jagadish
Keyword(s):  
Deep Learning ◽  
Cross Section ◽  
Food Production ◽  
Human Interaction ◽  
Root Anatomy ◽  
Steady Increase ◽  
Anatomical Features ◽  
Bounding Boxes ◽  
Root Stele ◽  
Plant Efficiency

The aboveground plant efficiency has improved significantly in recent years, and the improvement has led to a steady increase in global food production. The improvement of belowground plant efficiency has the potential to further increase food production. However, the belowground plant roots are harder to study, due to inherent challenges presented by root phenotyping. Several tools for identifying root anatomical features in root cross-section images have been proposed. However, the existing tools are not fully automated and require significant human effort to produce accurate results. To address this limitation, we propose a fully automated approach, called Deep Learning for Root Anatomy (DL-RootAnatomy), for identifying anatomical traits in root cross-section images. Using the Faster Region-based Convolutional Neural Network (Faster R-CNN), the DL-RootAnatomy models detect objects such as root, stele and late metaxylem, and predict rectangular bounding boxes around such objects. Subsequently, the bounding boxes are used to estimate the root diameter, stele diameter, and late metaxylem number and average diameter. Experimental evaluation using standard object detection metrics, such as intersection-over-union and mean average precision, has shown that our models can accurately detect the root, stele and late metaxylem objects. Furthermore, the results have shown that the measurements estimated based on predicted bounding boxes have very small root mean square error when compared with the corresponding ground truth values, suggesting that DL-RootAnatomy can be used to accurately detect anatomical features. Finally, a comparison with existing approaches, which involve some degree of human interaction, has shown that the proposed approach is more accurate than existing approaches on a subset of our data. A webserver for performing root anatomy using our deep learning pre-trained models is available at https://rootanatomy.org, together with a link to a GitHub repository that contains code that can be used to re-train or fine-tune our network with other types of root-cross section images. The labeled images used for training and evaluating our models are also available from the GitHub repository.

scholarly journals GRANAR, a new computational tool to better understand the functional importance of root anatomy

2019 ◽  
Author(s):  
Adrien Heymans ◽  
Valentin Couvreur ◽  
Therese LaRue ◽  
Ana Paez-Garcia ◽  
Guillaume Lobet
Keyword(s):  
Open Source ◽  
Hydraulic Properties ◽  
Root Anatomy ◽  
Limiting Factor ◽  
Computational Tool ◽  
Uptake Capacity ◽  
Root Hydraulic Conductivity ◽  
Anatomical Features ◽  
Water Uptake Capacity ◽  
Anatomical Parameters

AbstractRoot hydraulic conductivity is an important determinant of plant water uptake capacity. In particular, the root radial conductivity is often thought to be a limiting factor along the water pathways between the soil and the leaf. The root radial conductivity is itself defined by cell scale hydraulic properties and anatomical features. However, quantifying the influence of anatomical features on the radial conductivity remains challenging due to complex, and time-consuming, experimental procedures.We present a new computation tool, the Generator of Root ANAtomy in R (GRANAR) that can be used to rapidly generate digital versions of root anatomical networks. GRANAR uses a limited set of root anatomical parameters, easily acquired with existing image analysis tools. The generated anatomical network can then be used in combination with hydraulic models to estimate the corresponding hydraulic properties.We used GRANAR to re-analyse large maize (Zea mays) anatomical datasets from the literature. Our model was successful at creating virtual anatomies for each experimental observation. We also used GRANAR to generate anatomies not observed experimentally, over wider ranges of anatomical parameters. The generated anatomies were then used to estimate the corresponding radial conductivities with the hydraulic model MECHA. This enabled us to quantify the effect of individual anatomical features on the root radial conductivity. In particular, our simulations highlight the large importance of the width of the stele and the cortex.GRANAR is an open-source project available here: http://granar.github.ioOne-Sentence summaryGenerator of Root ANAtomy in R (GRANAR) is a new open-source computational tool that can be used to rapidly generate digital versions of root anatomical networks.

HRTEM simulation of interfacial structure in amorphous multilayers

1989 ◽  
Vol 47 ◽  
pp. 466-467
Author(s):  
Margaret L. Sattler ◽  
Michael A. O'Keefe
Keyword(s):  
Electron Microscopy ◽  
High Resolution ◽  
Cross Section ◽  
High Resolution Electron Microscopy ◽  
Interfacial Structure ◽  
Multilayer Sample ◽  
Resolution Electron ◽  
Multilayered Materials ◽  
Simulated Images

Multilayered materials have been fabricated with such high perfection that individual layers having two atoms deep are possible. Characterization of the interfaces between these multilayers is achieved by high resolution electron microscopy and Figure 1a shows the cross-section of one type of multilayer. The production of such an image with atomically smooth interfaces depends upon certain factors which are not always reliable. For example, diffusion at the interface may produce complex interlayers which are important to the properties of the multilayers but which are difficult to observe. Similarly, anomalous conditions of imaging or of fabrication may occur which produce images having similar traits as the diffusion case above, e.g., imaging on a tilted/bent multilayer sample (Figure 1b) or deposition upon an unaligned substrate (Figure 1c). It is the purpose of this study to simulate the image of the perfect multilayer interface and to compare with simulated images having these anomalies.

Cross Section Analysis of Cu Filled TSVs Based on High Throughput Plasma-FIB Milling

2012 ◽  
Author(s):  
Frank Altmann ◽  
Jens Beyersdorfer ◽  
Jan Schischka ◽  
Michael Krause ◽  
German Franz ◽  
...  
Keyword(s):  
High Resolution ◽  
Cross Section ◽  
High Throughput ◽  
Cross Sections ◽  
Electron Backscatter Diffraction ◽  
Grain Structure ◽  
Electron Backscatter ◽  
Section Surface ◽  
Backscatter Diffraction ◽  
Section Analysis

Abstract In this paper the new Vion™ Plasma-FIB system, developed by FEI, is evaluated for cross sectioning of Cu filled Through Silicon Via (TSV) interconnects. The aim of the study presented in this paper is to evaluate and optimise different Plasma-FIB (P-FIB) milling strategies in terms of performance and cross section surface quality. The sufficient preservation of microstructures within cross sections is crucial for subsequent Electron Backscatter Diffraction (EBSD) grain structure analyses and a high resolution interface characterisation by TEM.

scholarly journals Experimental investigation to characterize simple versus multi scaling analysis of hydraulic conductivity at a mesoscale

2021 ◽  
Author(s):  
Guglielmo Federico Antonio Brunetti ◽  
Samuele De Bartolo ◽  
Carmine Fallico ◽  
Ferdinando Frega ◽  
Maria Fernanda Rivera Velásquez ◽  
...  
Keyword(s):  
Hydraulic Conductivity ◽  
Spatial Variability ◽  
Hydraulic Properties ◽  
Scaling Laws ◽  
Scaling Analysis ◽  
Field Scale ◽  
Porous Formation ◽  
Proper Design ◽  
First Time

AbstractThe spatial variability of the aquifers' hydraulic properties can be satisfactorily described by means of scaling laws. The latter enable one to relate the small (typically laboratory) scale to the larger (typically formation/regional) ones, therefore leading de facto to an upscaling procedure. In the present study, we are concerned with the spatial variability of the hydraulic conductivity K into a strongly heterogeneous porous formation. A strategy, allowing one to identify correctly the single/multiple scaling of K, is applied for the first time to a large caisson, where the medium was packed. In particular, we show how to identify the various scaling ranges with special emphasis on the determination of the related cut-off limits. Finally, we illustrate how the heterogeneity enhances with the increasing scale of observation, by identifying the proper law accounting for the transition from the laboratory to the field scale. Results of the present study are of paramount utility for the proper design of pumping tests in formations where the degree of spatial variability of the hydraulic conductivity does not allow regarding them as “weakly heterogeneous”, as well as for the study of dispersion mechanisms.

scholarly journals Photoionization Cross-Sections of Carbon-Like N+ Near the K-Edge (390–440 eV)

Atoms ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 27
Author(s):  
Jean-Paul Mosnier ◽  
Eugene T. Kennedy ◽  
Jean-Marc Bizau ◽  
Denis Cubaynes ◽  
Ségolène Guilbaud ◽  
...  
Keyword(s):  
High Resolution ◽  
Cross Section ◽  
Cross Sections ◽  
Experimental Studies ◽  
Photoionization Cross Section ◽  
Theoretical Work ◽  
Rydberg Series ◽  
R Matrix ◽  
Resonance Strengths ◽  
Nitrogen Ion

High-resolution K-shell photoionization cross-sections for the C-like atomic nitrogen ion (N+) are reported in the 398 eV (31.15 Å) to 450 eV (27.55 Å) energy (wavelength) range. The results were obtained from absolute ion-yield measurements using the SOLEIL synchrotron radiation facility for spectral bandpasses of 65 meV or 250 meV. In the photon energy region 398–403 eV, 1s⟶2p autoionizing resonance states dominated the cross section spectrum. Analyses of the experimental profiles yielded resonance strengths and Auger widths. In the 415–440 eV photon region 1s⟶(1s2s22p2 4P)np and 1s⟶(1s2s22p2 2P)np resonances forming well-developed Rydberg series up n=7 and n=8 , respectively, were identified in both the single and double ionization spectra. Theoretical photoionization cross-section calculations, performed using the R-matrix plus pseudo-states (RMPS) method and the multiconfiguration Dirac-Fock (MCDF) approach were bench marked against these high-resolution experimental results. Comparison of the state-of-the-art theoretical work with the experimental studies allowed the identification of new resonance features. Resonance strengths, energies and Auger widths (where available) are compared quantitatively with the theoretical values. Contributions from excited metastable states of the N+ ions were carefully considered throughout.

A 3D-printed, Arabidopsis Thaliana Root Imaging Platform

Lab on a Chip ◽  
2021 ◽  
Author(s):  
Michel Moussus ◽  
Matthias Meier
Keyword(s):  
Molecular Dynamics ◽  
Arabidopsis Thaliana ◽  
High Resolution ◽  
Root System ◽  
Plant Root ◽  
Microfluidic Platforms ◽  
External Cues ◽  
3D Printed ◽  
Plant Root System ◽  
Analytical Tools

High resolution live imaging promises new insights into the cellular and molecular dynamics of the plant root system in response to external cues. Microfluidic platforms are valuable analytical tools that...

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