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Abstract. The fast development of plant genomics due to the next generation sequencing (NGS) technology has caused the progress of plant phenomics. In this study, three categories of phenotypic traits were acquired including 26 agronomic traits, 4 biochemical traits and 7 optical traits with 4 HSI traits extracted from HSI images that showed high correlation with rice quality traits that are difficult to measure, such as protein content R²=0.7193. A GWAS analysis of all the traits was applied to identify SNP markers related to rice quality. Results showed optical traits could identify more SNP markers and locate more related bioprocess pathways, which could provide a more comprehensive insight to the bioprocess that is associated with the rice quality. This study combined hyperspectral imaging and GWAS analysis to dissect complex traits of rice seeds, which could accurately quantify and qualify rice seeds and provide a new means to bridge the gap between genotyping and phenotyping.