skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: 3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

Abstract

Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height, leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquiremore » shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.« less

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]
  1. Texas A & M Univ., College Station, TX (United States). Interdisciplinary Program in Genetics and Biochemistry and Biophysics Department
Publication Date:
Research Org.:
Univ. of Wisconsin, Madison, WI (United States; Texas A & M Univ., College Station, TX (United States)
Sponsoring Org.:
USDOE Advanced Research Projects Agency - Energy (ARPA-E); USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1427723
Grant/Contract Number:  
FC02-07ER64494; AR0000596
Resource Type:
Accepted Manuscript
Journal Name:
Plant Physiology (Bethesda)
Additional Journal Information:
Journal Name: Plant Physiology (Bethesda); Journal Volume: 172; Journal Issue: 2; Journal ID: ISSN 0032-0889
Publisher:
American Society of Plant Biologists
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES

Citation Formats

Mccormick, Ryan F., Truong, Sandra K., and Mullet, John E. 3D sorghum reconstructions from depth images identify QTL regulating shoot architecture. United States: N. p., 2016. Web. doi:10.1104/pp.16.00948.
Mccormick, Ryan F., Truong, Sandra K., & Mullet, John E. 3D sorghum reconstructions from depth images identify QTL regulating shoot architecture. United States. doi:10.1104/pp.16.00948.
Mccormick, Ryan F., Truong, Sandra K., and Mullet, John E. Mon . "3D sorghum reconstructions from depth images identify QTL regulating shoot architecture". United States. doi:10.1104/pp.16.00948. https://www.osti.gov/servlets/purl/1427723.
@article{osti_1427723,
title = {3D sorghum reconstructions from depth images identify QTL regulating shoot architecture},
author = {Mccormick, Ryan F. and Truong, Sandra K. and Mullet, John E.},
abstractNote = {Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height, leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.},
doi = {10.1104/pp.16.00948},
journal = {Plant Physiology (Bethesda)},
number = 2,
volume = 172,
place = {United States},
year = {2016},
month = {8}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 16 works
Citation information provided by
Web of Science

Figures / Tables:

Figure 1 Figure 1: Processing of image data to segmented meshes. A, Point clouds are sampled from multiple perspectives around the plant. B, The point clouds are registered to the same frame and combined. C, The combined cloud is meshed to generate a set of polygons approximating the surface of the plant.more » D, The mesh is segmented into a shoot cylinder, leaves, and an inflorescence (if one exists; Supplemental Fig. S2), and phenotypes are measured automatically.« less

Save / Share:

Works referenced in this record:

Data from: 3D sorghum reconstructions from depth images identify QTL regulating shoot architecture
dataset, September 2016

  • McCormick, Ryan F.; Truong, Sandra K.; Mullet, John E.
  • Dryad Digital Repository-Supplementary information for journal article at DOI: 10.1104/pp.16.00948, 6 files
  • DOI: 10.5061/dryad.9vs26

    Works referencing / citing this record:

    Data from: 3D sorghum reconstructions from depth images identify QTL regulating shoot architecture
    dataset, September 2016

    • McCormick, Ryan F.; Truong, Sandra K.; Mullet, John E.
    • Dryad Digital Repository-Supplementary information for journal article at DOI: 10.1104/pp.16.00948, 6 files
    • DOI: 10.5061/dryad.9vs26

    High-Throughput Phenotyping Enabled Genetic Dissection of Crop Lodging in Wheat
    journal, April 2019


    High-Throughput Phenotyping Enabled Genetic Dissection of Crop Lodging in Wheat
    journal, April 2019


    Data from: 3D sorghum reconstructions from depth images identify QTL regulating shoot architecture
    dataset, September 2016

    • McCormick, Ryan F.; Truong, Sandra K.; Mullet, John E.
    • Dryad Digital Repository-Supplementary information for journal article at DOI: 10.1104/pp.16.00948, 6 files
    • DOI: 10.5061/dryad.9vs26

    Novel Low Cost 3D Surface Model Reconstruction System for Plant Phenotyping
    journal, September 2017

    • Liu, Suxing; Acosta-Gamboa, Lucia; Huang, Xiuzhen
    • Journal of Imaging, Vol. 3, Issue 3
    • DOI: 10.3390/jimaging3030039

    High-Throughput Phenotyping Analysis of Potted Soybean Plants Using Colorized Depth Images Based on A Proximal Platform
    journal, May 2019

    • Ma, Xiaodan; Zhu, Kexin; Guan, Haiou
    • Remote Sensing, Vol. 11, Issue 9
    • DOI: 10.3390/rs11091085

    A Novel LiDAR-Based Instrument for High-Throughput, 3D Measurement of Morphological Traits in Maize and Sorghum
    journal, April 2018

    • Thapa, Suresh; Zhu, Feiyu; Walia, Harkamal
    • Sensors, Vol. 18, Issue 4
    • DOI: 10.3390/s18041187

    3-D Image-Driven Morphological Crop Analysis: A Novel Method for Detection of Sunflower Broomrape Initial Subsoil Parasitism
    journal, April 2019

    • Lati, Ran; Filin, Sagi; Elnashef, Bashar
    • Sensors, Vol. 19, Issue 7
    • DOI: 10.3390/s19071569

      Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.