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2023, Vol. 8, Issue 3, Part B

Proposed new stability indices using AMMI model and GGE BIPLOT approach to assess G×E interaction


Author(s): Aditi, Sarita Rani, Vikas Khandelwal, Devvart and Arti Vaish

Abstract: Breeding for novel genotypes with high yield and stability is a crucial objective in agriculture. Environmental factors play a significant role in determining a genotype's response, which is commonly known as genotype-by-environment interaction. In this study, a multi-environment experiment with three replications of twenty-nine pearl millet genotypes for one year (2019) was conducted at eight locations in India. The Additive main effects and multiplicative interaction (AMMI) and Genotype and Genotype-by-environment (GGE) biplot analyses were used to study the genotype-by-environment (G x E) interaction and identify stable genotypes. A new weighted stability index was proposed, which was based on standardized grain yield indices and AMMI-based stability parameters to determine high-yielding and stable genotypes. In all environments, seven independent principal component axes (IPCAs) were significant. AMMI-based stability parameters and stability indices were used to identify stable genotypes, while yield stability index and weighted index were employed to identify the most stable and highest-yielding genotypes simultaneously. According to the AMMI-based stability parameters, genotypes G27, G13, and G28 were found to be stable, while genotypes G10, G11, and G13 were identified as stable with high grain yield according to yield stability index and weighted index. These findings suggest that the proposed weighted stability index can be used to identify high-yielding and stable pearl millet genotypes.

DOI: 10.22271/maths.2023.v8.i3b.992

Pages: 111-117 | Views: 414 | Downloads: 17

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International Journal of Statistics and Applied Mathematics
How to cite this article:
Aditi, Sarita Rani, Vikas Khandelwal, Devvart, Arti Vaish. Proposed new stability indices using AMMI model and GGE BIPLOT approach to assess G×E interaction. Int J Stat Appl Math 2023;8(3):111-117. DOI: 10.22271/maths.2023.v8.i3b.992

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