Morphological and molecular characterization of sugar beet (Beta vulgaris l.) genotypes

In this study, both molecular and morphological analyses were performed on 187 sugar beet genotypes and 5 commercial varieties obtained from the USDA. In the molecular analyses, the polymorphism and genetic diversity of the genotypes were examined using ISSR and SCoT markers. Using eight strong primers, 68 polymorphic bands were obtained, and the polymorphism rate was determined to be 100%. SCoT primers provided a higher genetic diversity index and PIC values compared to ISSR primers and were considered a more powerful tool for determining genetic differences. The UPGMA dendrogram separated the genotypes into two main groups (A and B) and subgroups; although Group A had narrow genetic diversity, it was important as an alternative genetic resource, while the subgroups in Group B revealed wide genetic variation and potential for use in breeding studies. STRUCTURE and PCA analyses confirmed that genotypes showed significant genetic differentiation and that some individuals originated from different gene pools. Among the USDA genotypes, PI 169017, PI 193458 (Ames 15638), and PI 120692 stood out as sources of high genetic diversity, clustering far from commercial varieties. Morphological analyses examined root-stem yield, sugar content, leaf yield, and sugar yield, with principal component analysis (PCA) results revealing wide variation among genotypes. Components PRIN1 to PRIN4 explained the differences in yield and quality parameters among genotypes and provided important information for parent selection in breeding programs. Both molecular and morphological data indicate significant genetic and agronomic diversity among the genotypes studied. The findings provide a solid scientific basis for both the development of new, high-yielding, and high-quality sugar beet varieties and the conservation of existing genetic resources. Molecular and morphological data serve as an important reference for guiding sugar beet breeding programs and effectively evaluating genetic resources.