标题：Assessment of Genetic Diversity of Bread Wheat Genotypes for Drought Tolerance Using Canopy Reflectance-Based Phenotyping and SSR Marker-Based Genotyping
摘要：This study investigated the genetic diversity of bread-wheat genotypes using canopy reflectance-based vegetation indices (VIs) and simple sequence repeat (SSR) marker-based genotyping for drought tolerance. A total of 56 wheat genotypes were assessed using phenotypic traits (combination of VIs and yield traits) and 30 SSR markers. The data of the phenotypic traits were averaged over two growing seasons under irrigated and drought-stressed conditions. The hierarchical clustering of the wheat genotypes unveiled three drought-tolerant groups. Cluster 1 genotypes showed minimal phenotypic alterations, conferring superior drought tolerance and yield stability than clusters 2 and 3. The polymorphism information content values for the SSR markers ranged from 0.434 to 0.932, averaging 0.83. A total of 458 alleles (18.32 alleles per locus) were detected, with the most polymorphic markers, wmc177 and wms292, having the most alleles (24). A comparative study of SSR diversity among phenotypic clusters indicated that genotypes under cluster 1 had higher genetic diversity (0.879) and unique alleles (47%), suggesting their potential in future breeding programs. The unweighted neighbor-joining tree grouped the wheat genotypes into five major clusters. Wheat genotypes from all phenotypic clusters were distributed throughout all SSR-based clusters, indicating that genetically heterogeneous genotypes were allocated to different drought-tolerant groups. However, SSR-based clusters and model-based populations showed significant co-linearity (86.7%). The findings of the present study suggest that combining reflectance-based indirect phenotyping with SSR-based genotyping might be an effective technique for assessing genetic diversity to improve the drought tolerance of bread-wheat genotypes.
关键词：bread-wheat; drought tolerance; vegetation indices; SSR markers; genetic diversity; unique alleles; cluster analysis; population structure
