Image analysis for mapping immeasurable phenotypes in Maize

Chi Ren Shyu, Jason M. Green, Pak Kong Lun, Tonic Kazic, Mary Schaeffer, Ed Coe

Research output: Journal article publicationJournal articleAcademic researchpeer-review

13 Citations (Scopus)

Abstract

An overview is given of challenges in mapping immeasurable phenotypes in maize and the potential of image analysis in a phenotype mapping system. It is argued that the use of image analysis may improve phenotypic quantification by increasing the objectivity and granularity of quantification, which in turn may result in an increase in the rate at which the genes controlling phenotypic traits are isolated. With the provision of sufficient markers and finer characterization of phenotypes, QTL mapping may become more accurate and result in smaller sections of deoxyribonucleic acid (DNA) to sort through for isolation of genes contributing to a given phenotypic trait.
Original languageEnglish
Pages (from-to)116-119
Number of pages4
JournalIEEE Signal Processing Magazine
Volume24
Issue number3
DOIs
Publication statusPublished - 1 Jan 2007

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

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