4D Structural root architecture modeling from digital twins by X-Ray Computed Tomography

Abstract Background Breakthrough imaging technologies may challenge the plant phenotyping bottleneck regarding marker-assisted breeding and genetic mapping. In this context, X-Ray CT (computed tomography) technology can accurately obtain the digital twin of root system architecture (RSA) but computational methods to quantify RSA traits and analyze their changes over time are limited. RSA traits extremely affect agricultural productivity. We develop a spatial–temporal root architectural modeling method based on 4D data from X-ray CT. This novel approach is optimized for high-throughput phenotyping considering the cost-effective time to process the data and the accuracy and robustness of the results. Significant root architectural traits, including root elongation rate, number, length, growth angle, height, diameter, branching map, and volume of axial and lateral roots are extracted from the model based on the digital twin. Our pipeline is divided into two major steps: (i) first, we compute the curve-skeleton based on a constrained Laplacian smoothing algorithm. This skeletal structure determines the registration of the roots over time; (ii) subsequently, the RSA is robustly modeled by a cylindrical fitting to spatially quantify several traits. The experiment was carried out at the Ag Alumni Seed Phenotyping Facility (AAPF) from Purdue University in West Lafayette (IN, USA). Results Roots from three samples of tomato plants at two different times and three samples of corn plants at three different times were scanned. Regarding the first step, the PCA analysis of the skeleton is able to accurately and robustly register temporal roots. From the second step, several traits were computed. Two of them were accurately validated using the root digital twin as a ground truth against the cylindrical model: number of branches (RRMSE better than 9%) and volume, reaching a coefficient of determination (R2) of 0.84 and a P < 0.001. Conclusions The experimental results support the viability of the developed methodology, being able to provide scalability to a comprehensive analysis in order to perform high throughput root phenotyping.

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4D Structural Root Architecture Modeling From Digital Twins By X-Ray Computed Tomography

10.21203/rs.3.rs-635314/v1 ◽

2021 ◽

Author(s):

Monica Herrero ◽

Valerian Meline ◽

Anjali S. Iyer-Pascuzzi ◽

Augusto M. Souza ◽

Mitchell R. Tuinstra ◽

...

Keyword(s):

Computed Tomography ◽

High Throughput ◽

Lateral Roots ◽

Skeletal Structure ◽

Coefficient Of Determination ◽

Plant Phenotyping ◽

X Ray ◽

Digital Twin ◽

Three Samples ◽

Over Time

Abstract BackgroundBreakthrough imaging technologies are a potential solution to address the plant phenotyping bottleneck regarding marker-assisted breeding and genetic mapping. X-Ray CT (computed tomography) technology is able to acquire the digital twin of root system architecture (RSA) but computational methods to quantify RSA traits and analyze their changes over time are limited. RSA traits extremely affect agricultural productivity. We develop a spatial-temporal root architectural modeling method based on 4D data from X-ray CT. This novel approach is optimized for high-throughput phenotyping considering the cost-effective time to process the data and the accuracy and robustness of the results. Significant root architectural traits, including root elongation rate, number, length, growth angle, height, diameter, branching map, and volume of axial and lateral roots are extracted from the model based on the digital twin. Our pipeline is divided into two major steps: (i) first, we compute the curve-skeleton based on a constrained Laplacian smoothing algorithm. This skeletal structure determines the registration of the roots over time; (ii) subsequently, the RSA is robustly modeled by a cylindrical fitting. The experiment was carried out at the Ag Alumni Seed Phenotyping Facility (AAPF) from Purdue University in West Lafayette (IN, USA). ResultsRoots from three samples of tomato plants at two different times and three samples of corn plants at three different times were scanned. Regarding the first step, the PCA analysis of the skeleton is able to accurately and robustly register temporal roots. From the second step, the volume from the cylindrical model was compared against the root digital twin, reaching a coefficient of determination (R2) of 0.84 and a P < 0.001. ConclusionsThe results confirm the feasibility of the proposed methodology, providing scalability to a comprehensive analysis to high throughput root phenotyping.

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ROOT PHENOTYPING FROM X-RAY COMPUTED TOMOGRAPHY: SKELETON EXTRACTION

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliii-b4-2021-417-2021 ◽

2021 ◽

Vol XLIII-B4-2021 ◽

pp. 417-422

Author(s):

M. Herrero-Huerta ◽

V. Meline ◽

A. S. Iyer-Pascuzzi ◽

A. M. Souza ◽

M. R. Tuinstra ◽

...

Keyword(s):

Computed Tomography ◽

Root System ◽

High Throughput ◽

Skeletal Structure ◽

Plant Phenotyping ◽

Skeleton Extraction ◽

X Ray ◽

Digital Twin ◽

Three Samples ◽

Root Phenotyping

Abstract. Breakthrough imaging technologies are a potential solution to the plant phenotyping bottleneck in marker-assisted breeding and genetic mapping. X-Ray CT (computed tomography) technology is able to acquire the digital twin of root system architecture (RSA), however, advances in computational methods to digitally model spatial disposition of root system networks are urgently required.We extracted the root skeleton of the digital twin based on 3D data from X-ray CT, which is optimized for high-throughput and robust results. Significant root architectural traits such as number, length, growth angle, elongation rate and branching map can be easily extracted from the skeleton. The curve-skeleton extraction is computed based on a constrained Laplacian smoothing algorithm. This skeletal structure drives the registration procedure in temporal series. The experiment was carried out at the Ag Alumni Seed Phenotyping Facility (AAPF) at Purdue University in West Lafayette (IN, USA). Three samples of tomato root at 2 different times and three samples of corn root at 3 different times were scanned. The skeleton is able to accurately match the shape of the RSA based on a visual inspection.The results based on a visual inspection confirm the feasibility of the proposed methodology, providing scalability to a comprehensive analysis to high throughput root phenotyping.

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High throughput phenotyping of morpho-anatomical stem properties using X-ray computed tomography in sorghum

Plant Methods ◽

10.1186/s13007-018-0326-3 ◽

2018 ◽

Vol 14 (1) ◽

Cited By ~ 11

Author(s):

Francisco E. Gomez ◽

Geraldo Carvalho ◽

Fuhao Shi ◽

Anastasia H. Muliana ◽

William L. Rooney

Keyword(s):

Computed Tomography ◽

High Throughput ◽

X Ray ◽

High Throughput Phenotyping ◽

X Ray Computed

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High-Throughput Phenotyping of Morphological Seed and Fruit Characteristics Using X-Ray Computed Tomography

Frontiers in Plant Science ◽

10.3389/fpls.2020.601475 ◽

2020 ◽

Vol 11 ◽

Author(s):

Weizhen Liu ◽

Chang Liu ◽

Jingyi Jin ◽

Dongye Li ◽

Yongping Fu ◽

...

Keyword(s):

Computed Tomography ◽

High Throughput ◽

Fruit Characteristics ◽

X Ray ◽

High Throughput Phenotyping ◽

X Ray Computed

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A high-throughput X-ray micro-computed tomography (μCT) approach for measuring single kernel maize ( Zea mays L.) volumes and densities

Journal of Cereal Science ◽

10.1016/j.jcs.2016.04.009 ◽

2016 ◽

Vol 69 ◽

pp. 321-328 ◽

Cited By ~ 16

Author(s):

Anina Guelpa ◽

Anton du Plessis ◽

Marena Manley

Keyword(s):

Computed Tomography ◽

Zea Mays ◽

High Throughput ◽

Zea Mays L ◽

Micro Computed Tomography ◽

X Ray

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Differential X-ray diagnosis of pseudotuberculous scenario of pulmonary abscess with tuberculous cavities

Український радіологічний та онкологічний журнал ◽

10.46879/ukroj.1.2021.9-20 ◽

2021 ◽

Vol 29 (1) ◽

pp. 9-20

Author(s):

R. Yu. Churylin ◽

I. O. Voronzhev ◽

Yu. A. Kolomiichenko ◽

О. О. Коvalova ◽

V. V. Syrota

Keyword(s):

Computed Tomography ◽

Differential Diagnosis ◽

Thoracic Surgery ◽

Lung Abscess ◽

Accurate Diagnosis ◽

Tuberculosis Patients ◽

X Ray ◽

Pulmonary Abscess ◽

Over Time

Background. Recent decades in Ukraine have been characterized by a significant increase in the number of tuberculosis patients, often with forming cavities of destruction. X-ray diagnosis of lung cavitary lesions is one of the current issues of modern pulmonology and thoracic surgery. Pulmonary abscesses resemble other diseases with destruction and cavities substantiating the need for differential diagnosis with tuberculosis. Purpose – specifying particular scenarios of X-ray presentation of lung abscess and determining the capability of differential diagnosis of pseudotuberculosis with cavities of tuberculosis etiology. Materials and methods. The paper deals with the analysis of X-ray examination of thoracic viscera provided for 252 patients with lung abscess, aged 18 and up to 78. X-ray radiography in two projections, linear and computed tomography (56 patients involved) were performed. All patients underwent a study over time. Results. Almost in most lung abscess cases, there is a need for differential diagnosis with a range of medical entities. The obtained data have made it possible to suggest a classification of X-ray scenarios of lung abscess. The scenarios of X-ray presentation of acute pulmonary abscess are typical and atypical, among those: cystoid, pseudotuberculous, affected 38 patients (15 %), and pulmonary-pleural. The peculiarities of X-ray presentation of pseudotuberculous scenario along with the differences and signs allowing to make an accurate diagnosis have been specified. Conclusions. X-ray study remains an essential in diagnosing purulent-destructive diseases. Being familiar with the scenarios mentioned above and pseudotuberculous one, in particular, will make it possible to significantly improve diagnosis as well as differential diagnosis of pulmonary abscess.

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