Genetic and phenotypic assessment of quantitative and qualitative characteristics of new sugar beet (Beta vulgaris L.) genotypes

This experiment aimed to identify the genetic relationship between sugar beets' quantitative and qualitative traits and their association with sugar yield (WSY). In this study, 13 sugar beet genotypes were grown in a randomised complete block design in Iran's Karaj, Mashhad, Miandoab, Zarghan, and Hamedan stations in the 2022 and 2023 crop seasons. Based on the heat map cluster analysis results in both years, the Genotypes were classified into three groups. Genotypes G5, G6, G7, and G13 exhibited the highest values of sugar yield (SY), sugar content (SC), white sugar content (WSC), WSY, and purity (PUR) compared to other groups. According to the biplot analysis, the first two components accounted for 83.4% and 82.8% of the total data variance. The estimated values of the phenotypic (PCV) and genotypic coefficient of variance (GCV), heritability (h²b), and genetic advance as a percentage of the mean (GAM) for WSY in the first year were 9.37%, 11.97%, 66%, and 16.3%, and in the second year, were 9.39%, 11.68%, 64%, and 15.55%. In both years, there were positive and significant genetic and phenotypic correlations of WSY with SC, α-amino-N (N), PUR, WSC, and WSY, and negative with alkalinity (ALC) and molasses sugar (MS). In addition to SY's positive genetic and phenotypic direct effect on WSY, traits such as RY, SC, N, PUR, and WSC indirectly showed a positive genetic and phenotypic effect on WSY through this trait. Sodium (Na) had the highest PCV, GCV, heritability, and GAM value; this trait's correlations and direct genetic and phenotypic effects on WSY were negative and significant, so selecting genotypes based on low Na is more effective.