抄録
To evaluate rice plant type precisely at the seedling stage, we established a quantitative evaluation method using an image analysis. P-type Fourier descriptors, which could apply an “open-curve”, were used for the plant type, and the coefficients were summarized as the scores of principal components (PCs) by principal component analysis. At the same time, “conventional plant type traits”, leaf blade length, leaf blade angle and inter-leaf-blade length, were measured by traditional plant type measurement methods. Based on the PC scores, the plant type for each PC was reconstructed by inverse Fourier transformation and the morphological characteristics were evaluated. To examine whether our method could appropriately identify the characteristics of the varieties, we discriminated the varieties using the PC scores by support vector machines. The varieties were also discriminated using the conventional traits of plant type. The results indicated that both traits had equal discrimination efficiency. In addition, the combination of conventional traits and scores had the highest discrimination efficiency. The relationship between the PC scores and conventional traits was examined by multiple regression analysis. The PC scores were not correlated with size-related traits. From these results, our research clarified that a plant type evaluation method using P-type Fourier descriptors could evaluate rice plant type precisely combined with conventional methods.
