Genome-wide association for grain morphology in synthetic hexaploid wheats using digital imaging analysis

Abstract

Grain size and shape greatly influence grain weight which ultimately enhances grain yield in wheat. Digital imaging (DI) based phenomic characterization can capture the three dimensional variation in grain size and shape than has hitherto been possible. In this study, we report the results from using digital imaging of grain size and shape to understand the relationship among different components of this trait, their contribution to enhance grain weight, and to identify genomic regions (QTLs) controlling grain morphology using genome wide association mapping with high density diversity array technology (DArT) and allele-specific markers.