Lingaiah, N. and Sudharshanam, A. and Rao, V. Thirumala and Prashant, Y. and Kumar, M. Vijay and Reddy, P. Indhudar and Prasad, B. Ram and Reddy, P. Raghu Rami and Rao, P. Jagan Mohan (2020) AMMI Biplot Analysis in Cotton (Gossypium hirsutum L.) Genotypes for Genotype X Environment Interaction at Four Agro-ecologies in Telangana State. Current Journal of Applied Science and Technology, 39 (15). pp. 98-103. ISSN 2457-1024
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Abstract
The objective of this study was to determine the genotype × environment interaction (GEI) and stability performance of eight promising cotton genotypes at four agro-ecologies in Telangana State. The experimental material consisting of eight genotypes were planted in randomized block design replicating thrice in four diverse environments of Telangana state during 2017, Kharif season. The present investigation was carried out in four diverse environments of Telangana state viz. RARS, Warangal, ARS, Adilabad, ARS, Modhole and RARS, Palem (Professor Jayashankar Telangana State Agricultural University) during 2017, Kharif season. The study was conducted at four diversified agro-ecologies of Telangana State. The experimental material comprised of eight genotypes viz., WGCV-109, ADB-638, WGCV-122, Narasimha, WGCV-119, WGCV-119, Srirama, WGCV-48 and ADB 645. First pooled analysis of variance was carried out to know the significance variation in genotype x environment interaction followed by AMMI analysis for genotype x environment interaction studies. Analysis of variance was significant for environments and (G x E) components indicating the use fullness of AMMI analysis in identifying the stable genotypes. Among the eight cotton genotypes, WGCV-109, Narasimha and ADB-645 were found to be best yielders over environments whereas the genotypes G7 (WGCV-48) and G4 (Narasimha) found to be stable. Most of the genotypes showed environment specificity. As a result, almost all of the evaluated genotypes were affected by the genotype x environment interaction effects, hence no genotype had superior performance in all environments.
Item Type: | Article |
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Subjects: | Academics Guard > Multidisciplinary |
Depositing User: | Unnamed user with email support@academicsguard.com |
Date Deposited: | 24 Feb 2023 09:45 |
Last Modified: | 05 Jul 2024 06:57 |
URI: | http://science.oadigitallibraries.com/id/eprint/292 |