One of the most important diseases of sugar beet (Beta vulgaris L.) is Rhizomania or Root madness, which is currently prevalent in all parts of the world. The damage of this disease in susceptible cultivars has been estimated at more than 50% and in some cases up to 100%. Due to the increase in the country's population and the need for sugar, sugar beet crop has a special place among crops. To evaluate genetic parameters, relationships between traits, and grouping of different sugar beet genotypes, 44 sugar beet hybrids in four regions (Hamedan, Kermanshah, Mashhad, and Shiraz) was evaluated in 2019. The experiment was conducted in the form of an incomplete block design (alpha latest) in 6 replications. The results showed that sugar content and root yield with 88.24 and 59.53%, respectively, had the highest and lowest values of
broad-sense heritability. In this study, white sugar yield with root yield, sugar content, sugar yield, sugar extraction coefficient, and white sugar content showed a positive and significant phenotypic and genetic correlation, and with root potassium content and molasses sugar had a negative and significant correlation. Based on stepwise regression analysis root potassium, sugar content, and nitrogen content were explained 52% of the white sugar yield variation and identified as the most effective traits in justifying white sugar yield variation. Cluster analysis classified 44 hybrids and 3 controls of sugar beet cultivar into four clusters in four locations. Cluster number four included hybrids No. 20, 43, 31, 23, 25, 24, and 37 and foreign control cultivars Succara and BTS 213, and had the most suitable quantitative and qualitative characteristics. In factor analysis through principal component analysis, two factors were identified that explained 82.52% of the total variance of the data. In this study, root potassium content and sugar content were identified as the most effective traits, and hybrids located in the cluster of four identified as the most suitable hybrid for future breeding programs.