@Article{phyton.2025.067124,
AUTHOR = {Jiexiong Xu},
TITLE = {Application of Image Processing Techniques in Rice Grain Phenotypic Analysis and Genome-Wide Association Studies},
JOURNAL = {Phyton-International Journal of Experimental Botany},
VOLUME = {94},
YEAR = {2025},
NUMBER = {8},
PAGES = {2365--2383},
URL = {http://www.techscience.com/phyton/v94n8/63682},
ISSN = {1851-5657},
ABSTRACT = { <b>Background:</b> Rice grain morphology—including traits such as awn length, hull color, size, and shape—is of central importance to yield, quality, and domestication, yet comprehensive quantification at scale has remained challenging. A promising solution has been provided by the integration of high-throughput imaging with genomic analysis. <b>Methods:</b> A standardized 2D image-processing pipeline was established to extract four categories of traits—awn length, hull color, projected grain area, and shape descriptors via PCA of normalized contours—from high-resolution photographs of 229 <i>Oryza sativa japonica</i> landraces. Genome-wide association analyses were then performed using a mixed linear model to control for population structure and kinship. <b>Results:</b> Broad phenotypic diversity was evident in awn length, hull coloration, grain dimensions, and morphological shape, with the first principal component explaining the dominant axis of shape variation. Known awn regulators <i>GAD1</i>/<i>OsRAE2</i> (chr 8; ) and <i>An-1</i> (chr 4; ) were identified. The hull color gene <i>Rd</i> (chr 1; ) was detected. A novel locus on chr 12 at 8.75 Mb with <i>Os12g0257600</i> (), and the known grain size gene <i>FLO2</i> (chr 4; ) were associated with projected area. Shape PC1 was mapped to <i>GLW7</i>/<i>OsSPL13</i> (chr 7; ), <i>NAL2</i>/<i>OsWOX3A</i> (chr 11; ), and <i>OsGIF1</i> (chr 11; ). <b>Conclusions:</b> This study demonstrates that image-based phenotyping combined with genome-wide association studies (GWAS) can efficiently reveal both established and novel genetic determinants of rice grain morphology. These findings provide actionable targets for marker-assisted selection and genome editing to tailor grain traits in rice breeding programs.},
DOI = {10.32604/phyton.2025.067124}
}