Assessing Genetic Diversity of Soybean Based on Smartphone Image-Derived Canopy Parameter

Convenient and accurate characterization of field-grown crops is essential for effective use of germplasm resources and breeding programs. In this study, we evaluated genetic relationships among ۱۸ soybean accessions at the early growth stage using a smartphone image-derived canopy parameter, the Canopy Cover Rate (CCR). Field experiments were conducted over two consecutive years (۲۰۲۱ and ۲۰۲۲). CCR was estimated from top-view images using image analysis software, providing a non-destructive and efficient indicator of plant morphology. CCR showed significant variation among accessions and was strongly correlated with traditional morphological/biomass traits (Correlation coefficients> ۰.۸). Multivariate analyses, including Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and Discriminant Analysis (DA), revealed that CCR could effectively classify accessions, with DA achieving an average correct classification rate of ۸۸.۹%. The results suggest that CCR is a reliable index for assessing genetic diversity in field-grown soybean genotypes. This study introduces an innovative, simple, and accurate method for evaluating soybean genetic resources using image-derived parameter.

کلیدواژه ها:

Canopy Cover Rate ، ، ">Glycine max L. ، Image analysis software ، Phenotyping ، Soybean genetic resources