Exploring the Genotype-Environment Interaction in Sugar Beet (Beta vulgaris L.) Genotypes for Optimal Selection

Background: Genotype-environment interaction, reflecting how genotypes respond differently across environments, significantly impacts breeding progress.This phenomenon poses challenges for breeders in selecting and evaluating superior genotypes.Understanding the genotypeenvironment interaction enables breeders to meticulously assess and select genotypes that align well with target environment conditions.Moreover, it offers opportunities to identify genotypes that exhibit positive interactions with specific environments or demonstrate robust performance in diverse environments.By cultivating genotypes in varied environments, breeders can observe genotypic responses, facilitating the selection of superior and stable genotypes.A thorough exploration of the genotype-environment interaction necessitates the application of robust statistical methods.In this study, a series of sugar beet hybrids were grown in diverse environments to investigate the impact of the genotype-environment interaction on the quantitative production potential of root yield and white sugar yield, assess their adaptability, and employ different statistical approaches to identify successful hybrids.Methods: This research involved the cultivation of 18 sugar beet genotypes that encompassed 15 hybrids and three control varieties previously developed to enhance resistance against rhizomania, rhizoctonia, and cyst nematode diseases.Phenotypic evaluations were conducted over two consecutive crop years (2022 and 2023) at two agricultural research stations in Karaj, Alborz, Iran, and Kermanshah, Kermanshah, Iran, utilizing a randomized complete block design with four replications.Standard agricultural practices, including weed control, irrigation, fertilizer application, and other farm management activities, were implemented, throughout the cropping season.Statistical analyses were performed on the collected data related to root yield and white sugar yield.Results: The analysis of genotype main effects revealed a significant difference in both root yield and white sugar yield.The interaction effects of year-location and genotype-year-location at the 1% probability level for both root yield and white sugar yield traits and genotype-year at the 5% probability level on white sugar yield made a significant difference.These findings suggest that fluctuations in environmental conditions and genetic factors can impact genotype performance across diverse environments, leading to marked variations in root yield and white sugar yield among genotypes.Using the GGE biplot method, it was found that the first and second principal components of the genotype-environment interaction explained 93.44 and 3.85%, respectively, and a total of 97.29% of variations in the root yield.Regarding the white sugar yield, the first and second principal components of the genotype-environment interaction explained 95.10 and 2.54%, respectively, and a total of 97.64% of variations.Considering that the first and second principal components played an important role in the variance of the data, the respective biplots can well explain the genotype variations and the genotype-environment interaction.The association biplot illustrated positive correlations between experimental environments, with a strong positive correlation observed between Karaj in 2023 and Kermanshah in 2022 for the root yield.Similarly,