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

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background

In bioenergy/forage sorghum, morpho-anatomical stem properties are major components affecting standability and juice yield. However, phenotyping these traits is low-throughput, and has been restricted by the lack of a high-throughput phenotyping platforms that can collect both morphological and anatomical stem properties. X-ray computed tomography (CT) offers a potential solution, but studies using this technology in plants have evaluated limited numbers of genotypes with limited throughput. Here we suggest that using a medical CT might overcome sample size limitations when higher resolution is not needed. Thus, the aim of this study was to develop a practical high-throughput phenotyping and image data processing pipeline that extracts stem morpho-anatomical traits faster, more efficiently and on a larger number of samples.

Results

A medical CT was used to image morpho-anatomical stem properties in sorghum. The platform and image analysis pipeline revealed extensive phenotypic variation for important morpho-anatomical traits in well-characterized sorghum genotypes at suitable repeatability rates. CT estimates were highly predictive of morphological traits and moderately predictive of anatomical traits. The image analysis pipeline also identified genotypes with superior morpho-anatomical traits that were consistent with ground-truth based classification in previous studies. In addition, stem cross section intensity measured by the CT was highly correlated with stem dry-weight density, and can potentially serve as a high-throughput approach to measure stem density in grass stems.

Conclusions

The use of CT on a diverse set of sorghum genotypes with a defined platform and image analysis pipeline was effective at predicting traits such as stem length, diameter, and pithiness ratio at the internode level. High-throughput phenotyping of stem traits using CT appears to be useful and feasible for use in an applied breeding program.

Electronic supplementary material

The online version of this article (10.1186/s13007-018-0326-3) contains supplementary material, which is available to authorized users.

Related collections

Most cited references 38

Record: found
Abstract: found
Article: not found

Dissecting the phenotypic components of crop plant growth and drought responses based on high-throughput image analysis.

Kerstin Neumann, Christian Klukas, Benjamin Kilian … (2014)

Significantly improved crop varieties are urgently needed to feed the rapidly growing human population under changing climates. While genome sequence information and excellent genomic tools are in place for major crop species, the systematic quantification of phenotypic traits or components thereof in a high-throughput fashion remains an enormous challenge. In order to help bridge the genotype to phenotype gap, we developed a comprehensive framework for high-throughput phenotype data analysis in plants, which enables the extraction of an extensive list of phenotypic traits from nondestructive plant imaging over time. As a proof of concept, we investigated the phenotypic components of the drought responses of 18 different barley (Hordeum vulgare) cultivars during vegetative growth. We analyzed dynamic properties of trait expression over growth time based on 54 representative phenotypic features. The data are highly valuable to understand plant development and to further quantify growth and crop performance features. We tested various growth models to predict plant biomass accumulation and identified several relevant parameters that support biological interpretation of plant growth and stress tolerance. These image-based traits and model-derived parameters are promising for subsequent genetic mapping to uncover the genetic basis of complex agronomic traits. Taken together, we anticipate that the analytical framework and analysis results presented here will be useful to advance our views of phenotypic trait components underlying plant development and their responses to environmental cues. © 2014 American Society of Plant Biologists. All rights reserved.

0 comments Cited 137 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Development and evaluation of a field-based high-throughput phenotyping platform

Pedro Andrade‑Sanchez, Michael Gore, John T. Heun … (2014)

Physiological and developmental traits that vary over time are difficult to phenotype under relevant growing conditions. In this light, we developed a novel system for phenotyping dynamic traits in the field. System performance was evaluated on 25 Pima cotton (Gossypium barbadense L.) cultivars grown in 2011 at Maricopa, Arizona. Field-grown plants were irrigated under well watered and water-limited conditions, with measurements taken at different times on 3 days in July and August. The system carried four sets of sensors to measure canopy height, reflectance and temperature simultaneously on four adjacent rows, enabling the collection of phenotypic data at a rate of 0.84ha h-1. Measurements of canopy height, normalised difference vegetation index and temperature all showed large differences among cultivars and expected interactions of cultivars with water regime and time of day. Broad-sense heritabilities (H2)were highest for canopy height (H2=0.86-0.96), followed by the more environmentally sensitive normalised difference vegetation index (H2=0.28-0.90) and temperature (H2=0.01-0.90) traits. We also found a strong agreement (r2=0.35-0.82) between values obtained by the system, and values from aerial imagery and manual phenotyping approaches. Taken together, these results confirmed the ability of the phenotyping system to measure multiple traits rapidly and accurately.

0 comments Cited 112 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

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

Ralf Metzner, Anja Eggert, Dagmar van Dusschoten … (2015)

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. Electronic supplementary material The online version of this article (doi:10.1186/s13007-015-0060-z) contains supplementary material, which is available to authorized users.

0 comments Cited 106 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Francisco E. Gomez: fegomez@ncsu.edu

Geraldo Carvalho Jr.: gacjunior@gmail.com

Fuhao Shi: fuhaoshi@gmail.com

Anastasia H. Muliana: amuliana@tamu.edu

William L. Rooney: wlr@tamu.edu

Journal

Journal ID (nlm-ta): Plant Methods

Journal ID (iso-abbrev): Plant Methods

Title: Plant Methods

Publisher: BioMed Central (London )

ISSN (Electronic): 1746-4811

Publication date (Electronic): 13 July 2018

Publication date PMC-release: 13 July 2018

Publication date Collection: 2018

Volume: 14

Electronic Location Identifier: 59

Affiliations

[1 ]ISNI 0000 0001 2173 6074, GRID grid.40803.3f, Department of Crop and Soil Sciences, , North Carolina State University, ; Raleigh, NC 27695 USA

[2 ]ISNI 0000 0004 4687 2082, GRID grid.264756.4, Department of Soil and Crop Sciences, , Texas A&M University, ; 370 Olsen Blvd, College Station, TX 77843 USA

[3 ]ISNI 0000 0004 4687 2082, GRID grid.264756.4, Department of Computer Science and Engineering, , Texas A&M University, ; 3112 TAMU, 710 Ross St, College Station, TX 77843 USA

[4 ]ISNI 0000 0004 4687 2082, GRID grid.264756.4, Department of Mechanical Engineering, , Texas A& M University, ; 401 Joe Routt Blvd, College Station, TX 77843 USA

Article

Publisher ID: 326

DOI: 10.1186/s13007-018-0326-3

PMC ID: 6043981

SO-VID: f18c29c7-a83d-4e0c-874f-0979cd32dc61

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 2 August 2017

Date accepted : 4 July 2018

Custom metadata

ScienceOpen disciplines: Plant science & Botany

Keywords: x-ray computed tomography,sorghum,high-throughput phenotyping,stem morphology,stem anatomy,stem biomechanics,computer vision

Data availability:

ScienceOpen disciplines: Plant science & Botany

Keywords: x-ray computed tomography, sorghum, high-throughput phenotyping, stem morphology, stem anatomy, stem biomechanics, computer vision

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

Read this article at

Abstract

Background

Results

Conclusions

Electronic supplementary material

Related collections

Plant MYBs

Most cited references 38

Dissecting the phenotypic components of crop plant growth and drought responses based on high-throughput image analysis.

Development and evaluation of a field-based high-throughput phenotyping platform

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

Author and article information

Contributors

Journal

Affiliations

Article

History

Categories

Custom metadata

Comments

Comment on this article

Similar content 202

Cited by 12

Most referenced authors 601