Sugar beet (Beta vulgaris L.) is a biennial herbaceous plant belonging to the genus Beta within the family Amaranthaceae. Its root tuber can be used as an effective source for sucrose production. In the pursuit of sustainable development and maximizing the economic value of crops, the full utilization of crop germplasm resources and efficient production is necessary. To better facilitate the collection and utilization of sugar beet germplasm resources, this study used 106 accessions of multigerm sugar beet germplasm provided by the Key Laboratory of Molecular Genetic Breeding for sugar beet as materials. We evaluated the core collections constructed under various strategies using relevant genetic parameters and ultimately established two core collection construction strategies based on morphological and molecular markers. The optimal strategy based on morphological data was “Euclidean distance + Multiple clustering deviation sampling + UPGMA + 25% sampling proportion”, while the optimal strategy based on molecular marker data was “Jaccard distance + Multiple clustering random sampling + UPGMA + 20% sampling proportion”. In addition, representativeness evaluation of the core collection was conducted based on parameters related to both morphology and molecular markers. Principal component analysis (PCA) was utilized for the final determination of the core collection. The results showed that for both the morphological parameters and molecular marker-related parameters, there were no significant differences between the constructed core collection and the original germplasm; the phenotypic distribution frequencies were basically similar. Principal component analysis indicated that the core collection possessed a population structure similar to that of the original germplasm. The constructed core collection had good representativeness. This study, for the first time, proposed a core collection construction approach suitable for sugar beet by integrating morphological and molecular marker methodologies. It aimed to provide a scientific basis for the utilization and development of sugar beet germplasm resources, genetic improvement, and the breeding of new cultivars.

This study utilized SRAP molecular markers to analyze the genetic basis of 106 multigerm sugar beet germplasm accessions. By revealing the genetic diversity, population structure, and differentiation patterns, it aimed to tap into the germplasm potential, guide core germplasm construction and hybrid combination optimization, and ultimately design a molecular breeding route to break through bottlenecks in sugar beet genetic breeding. In total, 24 core primer combinations were screened from 546 initial primer pairs for genomic DNA amplification. The results demonstrated that each primer combination amplified an average of five alleles. Genetic parameter calculations revealed moderate variation potential. Population structure analysis divided the germplasm into four genetic groups (G1–G4), highly consistent with cluster analysis and DAPC analysis results. Its reliability was jointly confirmed by STRUCTURE convergence verification (LnP(K) standard deviation) and cluster goodness-of-fit testing (r = 0.63166, p < 0.0001). Key findings indicated that Group G4 possesses a unique genetic background, and the maximum genetic distance exists between Group G1 and the other three groups, indicating its significant genetic differentiation characteristics. Gene exchange exists between the G3 and G4 populations. Genetic variation primarily originated from within populations (93%, F_ST = 0.1283). Genetic distances spanned from 0.385 (between accessions 66 and 71 within a group) to 0.836 (between accessions 47 and 85 across groups). Concurrently, gene flow analysis (Nm = 3.3977) indicated moderate genetic exchange among populations. This achievement established the first SRAP marker-based genetic architecture for multigerm sugar beet germplasm resources. It provides a quantitative population genetics basis for formulating targeted strategies for germplasm resource conservation and utilization, and lays the foundation for constructing an innovation system for sugar beet germplasm resources.