---
_id: '2822'
abstract:
- lang: eng
  text: Identification of genes that control root system architecture in crop plants
    requires innovations that enable high-throughput and accurate measurements of
    root system architecture through time. We demonstrate the ability of a semiautomated
    3D in vivo imaging and digital phenotyping pipeline to interrogate the quantitative
    genetic basis of root system growth in a rice biparental mapping population, Bala
    x Azucena. We phenotyped >1,400 3D root models and >57,000 2D images for
    a suite of 25 traits that quantified the distribution, shape, extent of exploration,
    and the intrinsic size of root networks at days 12, 14, and 16 of growth in a
    gellan gum medium. From these data we identified 89 quantitative trait loci, some
    of which correspond to those found previously in soil-grown plants, and provide
    evidence for genetic tradeoffs in root growth allocations, such as between the
    extent and thoroughness of exploration. We also developed a multivariate method
    for generating and mapping central root architecture phenotypes and used it to
    identify five major quantitative trait loci (r2 = 24-37%), two of which were not
    identified by our univariate analysis. Our imaging and analytical platform provides
    a means to identify genes with high potential for improving root traits and agronomic
    qualities of crops.
author:
- first_name: Christopher
  full_name: Topp, Christopher
  last_name: Topp
- first_name: Anjali
  full_name: Iyer Pascuzzi, Anjali
  last_name: Iyer Pascuzzi
- first_name: Jill
  full_name: Anderson, Jill
  last_name: Anderson
- first_name: Cheng
  full_name: Lee, Cheng
  last_name: Lee
- first_name: Paul
  full_name: Zurek, Paul
  last_name: Zurek
- first_name: Olga
  full_name: Symonova, Olga
  id: 3C0C7BC6-F248-11E8-B48F-1D18A9856A87
  last_name: Symonova
- first_name: Ying
  full_name: Zheng, Ying
  last_name: Zheng
- first_name: Alexander
  full_name: Bucksch, Alexander
  last_name: Bucksch
- first_name: Yuriy
  full_name: Mileyko, Yuriy
  last_name: Mileyko
- first_name: Taras
  full_name: Galkovskyi, Taras
  last_name: Galkovskyi
- first_name: Brad
  full_name: Moore, Brad
  last_name: Moore
- first_name: John
  full_name: Harer, John
  last_name: Harer
- first_name: Herbert
  full_name: Edelsbrunner, Herbert
  id: 3FB178DA-F248-11E8-B48F-1D18A9856A87
  last_name: Edelsbrunner
  orcid: 0000-0002-9823-6833
- first_name: Thomas
  full_name: Mitchell Olds, Thomas
  last_name: Mitchell Olds
- first_name: Joshua
  full_name: Weitz, Joshua
  last_name: Weitz
- first_name: Philip
  full_name: Benfey, Philip
  last_name: Benfey
citation:
  ama: Topp C, Iyer Pascuzzi A, Anderson J, et al. 3D phenotyping and quantitative
    trait locus mapping identify core regions of the rice genome controlling root
    architecture. <i>PNAS</i>. 2013;110(18):E1695-E1704. doi:<a href="https://doi.org/10.1073/pnas.1304354110">10.1073/pnas.1304354110</a>
  apa: Topp, C., Iyer Pascuzzi, A., Anderson, J., Lee, C., Zurek, P., Symonova, O.,
    … Benfey, P. (2013). 3D phenotyping and quantitative trait locus mapping identify
    core regions of the rice genome controlling root architecture. <i>PNAS</i>. National
    Academy of Sciences. <a href="https://doi.org/10.1073/pnas.1304354110">https://doi.org/10.1073/pnas.1304354110</a>
  chicago: Topp, Christopher, Anjali Iyer Pascuzzi, Jill Anderson, Cheng Lee, Paul
    Zurek, Olga Symonova, Ying Zheng, et al. “3D Phenotyping and Quantitative Trait
    Locus Mapping Identify Core Regions of the Rice Genome Controlling Root Architecture.”
    <i>PNAS</i>. National Academy of Sciences, 2013. <a href="https://doi.org/10.1073/pnas.1304354110">https://doi.org/10.1073/pnas.1304354110</a>.
  ieee: C. Topp <i>et al.</i>, “3D phenotyping and quantitative trait locus mapping
    identify core regions of the rice genome controlling root architecture,” <i>PNAS</i>,
    vol. 110, no. 18. National Academy of Sciences, pp. E1695–E1704, 2013.
  ista: Topp C, Iyer Pascuzzi A, Anderson J, Lee C, Zurek P, Symonova O, Zheng Y,
    Bucksch A, Mileyko Y, Galkovskyi T, Moore B, Harer J, Edelsbrunner H, Mitchell
    Olds T, Weitz J, Benfey P. 2013. 3D phenotyping and quantitative trait locus mapping
    identify core regions of the rice genome controlling root architecture. PNAS.
    110(18), E1695–E1704.
  mla: Topp, Christopher, et al. “3D Phenotyping and Quantitative Trait Locus Mapping
    Identify Core Regions of the Rice Genome Controlling Root Architecture.” <i>PNAS</i>,
    vol. 110, no. 18, National Academy of Sciences, 2013, pp. E1695–704, doi:<a href="https://doi.org/10.1073/pnas.1304354110">10.1073/pnas.1304354110</a>.
  short: C. Topp, A. Iyer Pascuzzi, J. Anderson, C. Lee, P. Zurek, O. Symonova, Y.
    Zheng, A. Bucksch, Y. Mileyko, T. Galkovskyi, B. Moore, J. Harer, H. Edelsbrunner,
    T. Mitchell Olds, J. Weitz, P. Benfey, PNAS 110 (2013) E1695–E1704.
date_created: 2018-12-11T11:59:47Z
date_published: 2013-04-30T00:00:00Z
date_updated: 2021-01-12T06:59:58Z
day: '30'
department:
- _id: MaJö
- _id: HeEd
doi: 10.1073/pnas.1304354110
external_id:
  pmid:
  - '25673779'
intvolume: '       110'
issue: '18'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4378147/
month: '04'
oa: 1
oa_version: Submitted Version
page: E1695 - E1704
pmid: 1
publication: PNAS
publication_status: published
publisher: National Academy of Sciences
publist_id: '3979'
quality_controlled: '1'
scopus_import: 1
status: public
title: 3D phenotyping and quantitative trait locus mapping identify core regions of
  the rice genome controlling root architecture
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 110
year: '2013'
...
---
_id: '2903'
abstract:
- lang: eng
  text: In order to enjoy a digital version of the Jordan Curve Theorem, it is common
    to use the closed topology for the foreground and the open topology for the background
    of a 2-dimensional binary image. In this paper, we introduce a single topology
    that enjoys this theorem for all thresholds decomposing a real-valued image into
    foreground and background. This topology is easy to construct and it generalizes
    to n-dimensional images.
author:
- first_name: Herbert
  full_name: Edelsbrunner, Herbert
  id: 3FB178DA-F248-11E8-B48F-1D18A9856A87
  last_name: Edelsbrunner
  orcid: 0000-0002-9823-6833
- first_name: Olga
  full_name: Symonova, Olga
  id: 3C0C7BC6-F248-11E8-B48F-1D18A9856A87
  last_name: Symonova
citation:
  ama: 'Edelsbrunner H, Symonova O. The adaptive topology of a digital image. In:
    IEEE; 2012:41-48. doi:<a href="https://doi.org/10.1109/ISVD.2012.11">10.1109/ISVD.2012.11</a>'
  apa: 'Edelsbrunner, H., &#38; Symonova, O. (2012). The adaptive topology of a digital
    image (pp. 41–48). Presented at the ISVD: International Symposium on Voronoi Diagrams
    in Science and Engineering, New Brunswick, NJ, USA : IEEE. <a href="https://doi.org/10.1109/ISVD.2012.11">https://doi.org/10.1109/ISVD.2012.11</a>'
  chicago: Edelsbrunner, Herbert, and Olga Symonova. “The Adaptive Topology of a Digital
    Image,” 41–48. IEEE, 2012. <a href="https://doi.org/10.1109/ISVD.2012.11">https://doi.org/10.1109/ISVD.2012.11</a>.
  ieee: 'H. Edelsbrunner and O. Symonova, “The adaptive topology of a digital image,”
    presented at the ISVD: International Symposium on Voronoi Diagrams in Science
    and Engineering, New Brunswick, NJ, USA , 2012, pp. 41–48.'
  ista: 'Edelsbrunner H, Symonova O. 2012. The adaptive topology of a digital image.
    ISVD: International Symposium on Voronoi Diagrams in Science and Engineering,
    41–48.'
  mla: Edelsbrunner, Herbert, and Olga Symonova. <i>The Adaptive Topology of a Digital
    Image</i>. IEEE, 2012, pp. 41–48, doi:<a href="https://doi.org/10.1109/ISVD.2012.11">10.1109/ISVD.2012.11</a>.
  short: H. Edelsbrunner, O. Symonova, in:, IEEE, 2012, pp. 41–48.
conference:
  end_date: 2012-06-29
  location: 'New Brunswick, NJ, USA '
  name: 'ISVD: International Symposium on Voronoi Diagrams in Science and Engineering'
  start_date: 2012-06-27
date_created: 2018-12-11T12:00:15Z
date_published: 2012-08-06T00:00:00Z
date_updated: 2021-01-12T07:00:35Z
day: '06'
ddc:
- '000'
department:
- _id: HeEd
- _id: MaJö
doi: 10.1109/ISVD.2012.11
file:
- access_level: open_access
  checksum: 444869a4e8abf07834f88b6e5cb5e9c3
  content_type: application/pdf
  creator: system
  date_created: 2018-12-12T10:09:41Z
  date_updated: 2020-07-14T12:45:52Z
  file_id: '4765'
  file_name: IST-2016-545-v1+1_2012-P-10-AdaptiveTopology.pdf
  file_size: 760548
  relation: main_file
file_date_updated: 2020-07-14T12:45:52Z
has_accepted_license: '1'
language:
- iso: eng
month: '08'
oa: 1
oa_version: Submitted Version
page: 41 - 48
publication_status: published
publisher: IEEE
publist_id: '3844'
pubrep_id: '545'
quality_controlled: '1'
scopus_import: 1
status: public
title: The adaptive topology of a digital image
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
year: '2012'
...