Image Analysis for Mapping Immeasurable Phenotypes in Maize [Life Sciences]

Author

Shyu, Chi-Ren ; Green, Jason M. ; Lun, Daniel P K ; Kazic, Toni ; Schaeffer, Mary ; Coe, Ed

Author_Institution

Missouri-Columbia Univ., Columbia, MO

Volume

24

Issue

3

fYear

2007

fDate

5/1/2007 12:00:00 AM

Firstpage

115

Lastpage

118

Abstract

This work will allow bio-informaticians to analyze the ever-increasing gene sequence data, discover valuable knowledge in maize biology and related plant; development, and understand subtle variations among different phenotypes. Furthermore, successful measuring of visual phenotypes will advance plant research by finding the genes and/or environmental factors that cause a given visual phenotype. In what follows, the field of plant genetics is introduced (particularly quantitative trait loci and disease scoring) to the signal processing community, discuss the challenges involved, and present an image analysis system for precisely quantifying and mapping immeasurable phenotypes in maize

Keywords

biology computing; crops; genetics; image sequences; gene sequence data; image analysis; maize biology; mapping immeasurable phenotypes; plant genetics; signal processing; visual phenotype; Bioinformatics; Couplings; Crops; Diseases; Environmental factors; Genetics; Genomics; Image analysis; Image sequence analysis; Ontologies;

fLanguage

English

Journal_Title

Signal Processing Magazine, IEEE

Publisher

ieee

ISSN

1053-5888

Type

jour

DOI

10.1109/MSP.2007.361609

Filename

4205096