Evaluation of upland cotton genotypes for stability over different locations using AMMI and GGE biplot analysis

Abro, Saifullah; Rizwan, Muhammad; Rajput, Muhammad Tahir; Sial, Mahboob Ali; Deho, Z. A.

doi:10.30848/pjb2022-5(1)

Cited by 8 publications

(5 citation statements)

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“…4 b). Several researchers have also succeeded in selecting stable genotypes with GGE biplot on sweet potato [ 47 ], upland cotton [ 57 ], maize hybrid [ 51 ], rice [ 58 ], and barley [ 20 ].…”

Section: Discussionmentioning

confidence: 99%

Genotype-by-environment interactions (GEIs) and evaluate superior sweet potato (Ipomoea batatas [L.] Lam) using combined analysis and GGE biplot

Maulana,

Solihin,

Trimo

et al. 2023

Heliyon

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Section: Discussionmentioning

confidence: 99%

Genotype-by-environment interactions (GEIs) and evaluate superior sweet potato (Ipomoea batatas [L.] Lam) using combined analysis and GGE biplot

Maulana,

Solihin,

Trimo

et al. 2023

Heliyon

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“…GGE biplot was divided into four, seven, ve, ve and four sections for BN, BW, SCY, LY and GP, respectively. Similarly, the GGE biplot was divided into eight, seven, six and four sections according to previous researches ndings by [Regmi et al, 2021, Abro et al, 2022, Daemo et al, 2023, and Yasar et al, 2023. The grouping of all the environmental indicators in one section of the biplot revealed that a particular genotype performed well in all the tested environments.…”

Section: Gge Biplotmentioning

confidence: 99%

Determination of the effect of Genotype × Environment interaction on the trait seed cotton yield in upland cotton (G. hirsutum) genotypes using AMMI and GGE biplot methods

VISHNUVARDHAN,

Reddy,

Sudeepthi

et al. 2024

Preprint

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Background Cotton is an important natural fiber crop worldwide that demands the attention of the textile industry worldwide. Seed cotton yield is a complex polygenic trait that is influenced by many genetic and environmental factors across locations and years. Results The present investigation was conducted in three consecutive environments to delineate the genotype × environment interaction and to assess the stability of seven cotton genotypes at the Regional Agricultural Research Station, Nandyal, during 2018-19, 2019-20 and 2020-21. Multivariate stability tests such as additive main effect and multiplicative interaction (AMMI) and genotype and genotype-by-environment interaction (GGE) models were employed to investigate the stability among cotton genotypes. The AMMI results revealed that the majority of the variation was explained by the sum of the squares of the environmental variables, followed by the sum of the squares of the genotypic variables and the sum of the GEIs for the majority of the traits studied. The first two interaction principal components explained the majority of the GEI in all traits under study. A two-dimensional GGE biplot generated using the first two principal components revealed that the GGE biplot explained 97.14% of the total variation, which was distributed as 83.73% and 13.41% of the sum of squares between principal components PC1 and PC2, respectively, for biometric trait seed cotton yield. Conclusions Based on which-won-where polygon, ideal genotype ranking of AMMI and GGE biplot analysis, genotype, G3 (NDLH 2035-5) was identified as having the highest yield and was most stable in all the test environments studied. However, low yielding but stable genotypes such as G4 (BGDS 1033) and G7 (Sivanandi) were also identified. Among the three environments studied, environment E1 (2018-19) was identified as the most discriminating and representative.

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“…Researchers are indeed investigating how plants may be handled in high-temperature environments. Pharmacological, metabolic, and genomic adaptations to highly stressful conditions have been explored to screen recently developed cotton cultivars [ 72 ]. Discovery and development of prospective genotypes with higher resistance to heat stress might result in improved yield and quality in heat-prone locations.…”

Section: Molecular Mechanisms and Breeding Approaches Against Heat St...mentioning

confidence: 99%

Morphological and physio-biochemical responses under heat stress in cotton: Overview

Abro,

Anwar,

Javwad

et al. 2023

Biotechnology Reports

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Evaluation of upland cotton genotypes for stability over different locations using AMMI and GGE biplot analysis

Cited by 8 publications

References 0 publications

Genotype-by-environment interactions (GEIs) and evaluate superior sweet potato (Ipomoea batatas [L.] Lam) using combined analysis and GGE biplot

Genotype-by-environment interactions (GEIs) and evaluate superior sweet potato (Ipomoea batatas [L.] Lam) using combined analysis and GGE biplot

Determination of the effect of Genotype × Environment interaction on the trait seed cotton yield in upland cotton (G. hirsutum) genotypes using AMMI and GGE biplot methods

Morphological and physio-biochemical responses under heat stress in cotton: Overview

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