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Research ArticleBREAKTHROUGH TECHNOLOGIES
Open Access

High-Resolution Inflorescence Phenotyping Using a Novel Image-Analysis Pipeline, PANorama

Samuel Crowell, Alexandre X. Falcão, Ankur Shah, Zachary Wilson, Anthony J. Greenberg, Susan R. McCouch
Samuel Crowell
Department of Plant Biology (S.C., S.R.M.) and Department of Plant Breeding and Genetics (A.X.F., A.S., Z.W., A.J.G., S.R.M.), Cornell University, Ithaca, New York 14853; and
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Alexandre X. Falcão
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Ankur Shah
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Zachary Wilson
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Anthony J. Greenberg
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Susan R. McCouch
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  • For correspondence: srm4@cornell.edu

Published June 2014. DOI: https://doi.org/10.1104/pp.114.238626

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  • © 2014 American Society of Plant Biologists. All Rights Reserved.

Abstract

Variation in inflorescence development is an important target of selection for numerous crop species, including many members of the Poaceae (grasses). In Asian rice (Oryza sativa), inflorescence (panicle) architecture is correlated with yield and grain-quality traits. However, many rice breeders continue to use composite phenotypes in selection pipelines, because measuring complex, branched panicles requires a significant investment of resources. We developed an open-source phenotyping platform, PANorama, which measures multiple architectural and branching phenotypes from images simultaneously. PANorama automatically extracts skeletons from images, allows users to subdivide axes into individual internodes, and thresholds away structures, such as awns, that normally interfere with accurate panicle phenotyping. PANorama represents an improvement in both efficiency and accuracy over existing panicle imaging platforms, and flexible implementation makes PANorama capable of measuring a range of organs from other plant species. Using high-resolution phenotypes, a mapping population of recombinant inbred lines, and a dense single-nucleotide polymorphism data set, we identify, to our knowledge, the largest number of quantitative trait loci (QTLs) for panicle traits ever reported in a single study. Several areas of the genome show pleiotropic clusters of panicle QTLs, including a region near the rice Green Revolution gene SEMIDWARF1. We also confirm that multiple panicle phenotypes are distinctly different among a small collection of diverse rice varieties. Taken together, these results suggest that clusters of small-effect QTLs may be responsible for varietal or subpopulation-specific panicle traits, representing a significant opportunity for rice breeders selecting for yield performance across different genetic backgrounds.

  • Glossary

    PI
    panicle initiation
    IM
    inflorescence meristem
    PBM
    primary branch meristem
    QTL
    quantitative trait locus
    RIL
    recombinant inbred line
    PL
    panicle length
    GUI
    graphical user interface
    EP
    extrusion point
    IMAP
    initial main axis point
    FMAP
    final main axis point
    MAPD
    mean absolute percentage deviation
    MPE
    mean percentage error
    PBL
    primary branch length
    NN
    internode number
    DTH
    days to heading
    PN
    panicle number
    EL
    exsertion length
    LOD
    log10 of the odds
    cM
    centimorgan
    NL
    internode length
    GWAS
    genome-wide association studies
    PVE
    percentage variance explained
    RL
    rachis length
    BpN
    average number of branches per node
    PBN
    primary branch number
    • Received February 25, 2014.
    • Accepted April 1, 2014.
    • Published April 2, 2014.

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    High-Resolution Inflorescence Phenotyping Using a Novel Image-Analysis Pipeline, PANorama
    Samuel Crowell, Alexandre X. Falcão, Ankur Shah, Zachary Wilson, Anthony J. Greenberg, Susan R. McCouch
    Plant Physiology Jun 2014, 165 (2) 479-495; DOI: 10.1104/pp.114.238626

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    High-Resolution Inflorescence Phenotyping Using a Novel Image-Analysis Pipeline, PANorama
    Samuel Crowell, Alexandre X. Falcão, Ankur Shah, Zachary Wilson, Anthony J. Greenberg, Susan R. McCouch
    Plant Physiology Jun 2014, 165 (2) 479-495; DOI: 10.1104/pp.114.238626
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    Plant Physiology: 165 (2)
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