Image-based phenotyping for identification of QTL determining fruit shape and size in American cranberry (Vaccinium macrocarpon L.)

Publication Overview
TitleImage-based phenotyping for identification of QTL determining fruit shape and size in American cranberry (Vaccinium macrocarpon L.)
AuthorsDiaz-Garcia L, Covarrubias-Pazaran G, Schlautman B, Grygleski E, Zalapa J
TypeJournal Article
Journal NamePeerJ
Volume6
Year2018
Page(s)e5461
CitationDiaz-Garcia L, Covarrubias-Pazaran G, Schlautman B, Grygleski E, Zalapa J. Image-based phenotyping for identification of QTL determining fruit shape and size in American cranberry (Vaccinium macrocarpon L.). PeerJ. 2018; 6:e5461.

Abstract

Image-based phenotyping methodologies are powerful tools to determine quality parameters for fruit breeders and processors. The fruit size and shape of American cranberry (Vaccinium macrocarpon L.) are particularly important characteristics that determine the harvests' processing value and potential end-use products (e.g., juice vs. sweetened dried cranberries). However, cranberry fruit size and shape attributes can be difficult and time consuming for breeders and processors to measure, especially when relying on manual measurements and visual ratings. Therefore, in this study, we implemented image-based phenotyping techniques for gathering data regarding basic cranberry fruit parameters such as length, width, length-to-width ratio, and eccentricity. Additionally, we applied a persistent homology algorithm to better characterize complex shape parameters. Using this high-throughput artificial vision approach, we characterized fruit from 351 progeny from a full-sib cranberry population over three field seasons. Using a covariate analysis to maximize the identification of well-supported quantitative trait loci (QTL), we found 252 single QTL in a 3-year period for cranberry fruit size and shape descriptors from which 20% were consistently found in all years. The present study highlights the potential for the identified QTL and the image-based methods to serve as a basis for future explorations of the genetic architecture of fruit size and shape in cranberry and other fruit crops.
Features
This publication contains information about 206 features:
Feature NameUniquenameType
Fruit projected areaqFPA.GRYG.LG01.14QTL
Fruit projected areaqFPA.GRYG.LG01.15QTL
Fruit projected areaqFPA.GRYG.LG01.16QTL
Fruit projected areaqFPA.GRYG.LG01.combinedQTL
Fruit eccentricityqFECC.GRYG.LG01.14QTL
Fruit eccentricityqFECC.GRYG.LG01.15QTL
Fruit eccentricityqFECC.GRYG.LG01.16QTL
Fruit eccentricityqFECC.GRYG.LG01.combinedQTL
Fruit lengthqFLEN.GRYG.LG01.16QTL
Fruit lengthqFLEN.GRYG.LG01.combinedQTL
Fruit length:width ratioqFWLR.GRYG.LG01.14QTL
Fruit length:width ratioqFWLR.GRYG.LG01.16QTL
Fruit length:width ratioqFWLR.GRYG.LG01.15QTL
Fruit length:width ratioqFWLR.GRYG.LG01.combinedQTL
Fruit shape: persistent homologyqFSPH.GRYG.LG01.14QTL
Fruit shape: persistent homologyqFSPH.GRYG.LG01.16QTL
Fruit shape: persistent homologyqFSPH.GRYG.LG01.15QTL
Fruit widthqFWID.GRYG.LG01.14QTL
Fruit widthqFWID.GRYG.LG01.16QTL
Fruit widthqFWID.GRYG.LG01.15QTL
Fruit widthqFWID.GRYG.LG01.combinedQTL
Fruit projected areaqFPA.GRYG.LG02.14QTL
Fruit projected areaqFPA.GRYG.LG02.16QTL
Fruit projected areaqFPA.GRYG.LG02.15QTL
Fruit projected areaqFPA.GRYG.LG02.combinedQTL

Pages

Projects
This publication contains information about 1 projects:
Project NameDescription
Cranberry-Fruit_shape-Zalapa-2018
Properties
Additional details for this publication include:
Property NameValue
DOI10.7717/peerj.5461
Elocation10.7717/peerj.5461
ISSN2167-8359
Journal AbbreviationPeerJ
Journal CountryUnited States
LanguageEnglish
Language Abbreng
pISSN2167-8359
Publication Date2018
Publication ModelElectronic-eCollection
Publication TypeJournal Article
Published Locatione5461
Published Locatione5461
Cross References
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DatabaseAccession
PMID: PubMedPMID:30128209