Abstract
The traits of rice panicles play important roles in yield assessment, variety classification, rice breeding, and cultivation management. Most traditional grain phenotyping methods require threshing and thus are time-consuming and labor-intensive; moreover, these methods cannot obtain 3D grain traits. In this work, based on X-ray computed tomography, we proposed an image analysis method to extract twenty-two 3D grain traits. After 104 samples were tested, the R2 values between the extracted and manual measurements of the grain number and grain length were 0.980 and 0.960, respectively. We also found a high correlation between the total grain volume and weight. In addition, the extracted 3D grain traits were used to classify the rice varieties, and the support vector machine classifier had a higher recognition accuracy than the stepwise discriminant analysis and random forest classifiers. In conclusion, we developed a 3D image analysis pipeline to extract rice grain traits using X-ray computed tomography that can provide more 3D grain information and could benefit future research on rice functional genomics and rice breeding.
Highlights
Rice is one of the most important food crops worldwide, especially in China [1,2,3]
Using two discriminant functions generated by the Stepwise discriminant analysis (SDA) algorithm, the grain variety classification results are visualized in Figure 7, which shows that most varieties were well classified
To ensure that all the rice panicles were in the CT field of view, the panicles were wrapped by using a thin roll of paper when scanning
Summary
Rice is one of the most important food crops worldwide, especially in China [1,2,3]. Phenotypes have been shown to greatly accelerate the process of rice genetics and breeding [7, 8]. The rice panicle, an important agronomic component [9], is closely associated with yield. The number of grains per panicle directly determines rice yield [10]. Accurately quantifying the grain number and grain size per panicle is a key step in rice phenotyping [11]. The phenotyping of grain traits is manually performed after threshing; this is an incredibly time-consuming and laborintensive process [12]
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