Genetic Diversity and Relationship of Some Sugar Beet Population by Morpho-physiological Traits

Abstract The present study focuses on presenting the distribution of genetic diversity in some of the breeding populations of Beta vulgaris L. using yield, yield component, and root morpho-physiological traits. For this purpose, 80 genotypes from 8 different sugar beet populations were used under a randomized complete block design with five replicates at the Azad University research field during the 2021–2022 cropping season. Overall results of ANOVA led to the identification of significant statistical differences among the populations that indicate the genetic difference of the studied sugar beet population. According to the mean comparison of analyzed data, P191 displayed better traits in terms of sugar content, nitrogen content, pure sugar content, extraction coefficient, and root dry matter. Similarly, population M224 exhibited better root number, root yield, leaf weight, and sugar yield than other populations. The dendrogram using UPGMA revealed that the population formed three distinct clusters, with the greatest genetic distance between M249 and the 191 populations. This distance is expected to create maximum heterosis through crossbreeding between these two populations. The results indicate that the number of roots significantly affects RY, LY, Na, and WSY, but does not have a significant correlation with other traits. RY is correlated with LY, Na, and WSY, while LY is inversely correlated with WSC, ECS, and DM, and directly correlated with Na. Principal component analysis based on varimax rotation revealed that the three factors explained 87.6% of the total variance with this arrangement: the first factor named WSC explained 54.5%, the second factor, called RY, accounted for 22.8% and the third factor contributed to 10.2% of the total variance. The Biplot from the first two components also groups populations similar to cluster analysis grouping. It is noticeable that the findings of this research could provide valuable insights into the breeding and improvement of sugar beet populations, which could ultimately benefit the sugar industry.