Simultaneous Quantification of Multiple Quality Traits Hidden in Living White/Pigmented Rice Seeds Both at 2D and 3D Level

Rice quality mainly includes milling, appearance, nutrition, eating, cooking and physicochemical qualities. Rice quality/grade assessment depends on multiple indicators (traits) testing based on the recommended methods in the executing rice standards. Regretfully, the quality/grade assessments for white and pigmented rice do not follow a unified standard. The utilization of a series of independent methods means complex operations, higher time requirements and cost because of the hidden, subtle, and irregular characteristics of quality traits. Destructive husking and polishing are usually the prerequisite steps before quality assessment, leading to a loss of seed activity. Additionally, these methods fail to provide spatial information of the quality traits within intact seeds. In this study, microCT was employed to capture the cross-section images of living rice seeds. We performed contrast and segmentation processes by using image segmentation software. Multiple quality traits were simultaneously determined using one group of cross-section images from one microCT scan both in living white and pigmented rice seeds. This research also expanded the scope of quality-related traits and displayed their 2D and (or) 3D information (e.g., linearity, area, surface area and volume). Our achievements can guide the establishment of a new unified standard for white and pigmented rice at the 3D level, and it also shows great potential for application in phenotyping and breeding.