Stability and Adaptability of Sugar Beet Examined Based on AMMI and BLUP–GGE Biplot Analyses

Abstract

To identify high-yielding, adaptable, and regionally representative sugar beet varieties, this study applied analysis of variance, the additive main effects and multiplicative interaction (AMMI), best linear unbiased prediction (BLUP) analysis, and the genotype main effects plus genotype–environment interaction (GGE) biplot method. We evaluated the sugar content and root yield of 16 sugar beet varieties grown at seven different trial locations in 2021. The results indicated significant differences between the uncorrected data and the BLUP values, with the latter being more accurate and reliable in representing breeding values. Among the tested varieties, KWS 7748–1 (V6) exhibited the highest and most stable yield across all three models, demonstrating strong adaptability and high yield potential in various environments. This suggests that KWS 7748–1 (V6) has high potential for stable yields, even in regions with fluctuating climatic conditions. Therefore, it could become an important resource in breeding programs, particularly for improving yield adaptability and stress resistance. Its reliability in diverse environments makes it an ideal candidate for widespread cultivation, contributing to increased sugar beet production and food security. Furthermore, Jialaid Banner (E7) was identified as the most discriminative and representative trial location. The combined application of analysis of variance, AMMI model, BLUP analysis, and GGE biplot method enhanced the scientific rigor, comprehensiveness, and effectiveness of the regional trials for sugar beet varieties.