Revealing Adaptability of Sugar Beet (Beta vulgaris) Genotypes Through Environmental Interaction (GEI) connecting Variations in Tuber Yield

Shanmuganathan, M.; Kumaresan, D.; Geetha, S.; Dhasarathan, M.; Jayaramachandran, M.; Sudhagar, R.; Selvakumar, T.; Chitra, L; Mohan, S.; Gurusamy, A.; Iyanar, K.

doi:10.1007/s40003-023-00649-8

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“…Therefore, it is important to consider GEI while developing strategies to improve the yield of sugar beet ( Eltaher et al, 2021 ). In addition to the inherent characteristics of the variety itself, key environmental factors such as soil and climate conditions can also influence the yield and quality of sugar beet ( Shanmuganathan et al, 2023 ; Bartsch et al, 2003 ). Therefore, sugar enterprises and plant breeders prefer to cultivate sugar beet varieties with high quality and stability under different environmental conditions.…”

Section: Discussionmentioning

confidence: 99%

AMMI and GGE biplot analysis for genotype × environment interactions affecting the yield and quality characteristics of sugar beet

Dang,

Hu,

et al. 2024

PeerJ

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Sugar beet, an important sugar crop, contributes significantly to the world’s sugar production. However, genotype–environment interactions (GEI) often affect the quality characteristics of sugar beet. Hence, understanding the effects of GEI on sugar beet quality can aid in identifying high-quality genotypes that can adapt to different environments. Traditional variance analysis can only be used to examine the yield of a variety and not its specific adaptability to specific conditions. Therefore, more comprehensive analytical methods are required to evaluate the characteristics of the variety under specific environments. Additive main effects and multiplicative interaction (AMMI) and genotype main effect and genotype × environment interaction (GGE) biplot models can be employed to comprehensively evaluate different varieties and address the drawbacks associated with a single evaluation method. Moreover, these models also allow us to explore new varieties more objectively and comprehensively. In this study, the adaptability and stability of 16 sugar beet varieties, in terms of yield and sugar content, were evaluated using AMMI and GGE biplot analysis in seven pilot projects undertaken in 2022. In the assessment of a small but significant proportion of the total GEI variance for the two qualitative traits (yield and sugar content), 80.58% of the variance was explained by the cumulative contribution of IPC1, IPC2, and IPC3. AMMI and GGE biplots clearly highlighted that KWS4207 (G3) exhibited high and stable quality. They also demonstrated that the experiments in Jalaid Banner (Inner Mongolia) (E7) were the most representative. Together, the results suggested that the comprehensive application of AMMI and GGE biplot analysis allowed for a more comprehensive, scientific, and effective evaluation of sugar beet varieties across different regions. The findings offer a theoretical basis for sugar beet breeding and could guide the rational design of experiments for testing new varieties of sugar beet.

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Section: Discussionmentioning

confidence: 99%