AMMI analysis of rainfed lowland rice (Oryza sativa) trials in Nigeria

The additive main effects and multiplicative interaction (AMMI) model is used to analyse the grain yield data of 13 rice genotypes grown in 12 rainfed lowland rice environments. The trials were organized by the International Network for Genetic Evaluation of Rice in Africa (INGER‐Africa) and conduct...

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Main Authors: Abamu, F.J., Alluri, K.
Format: Journal Article
Language:Inglés
Published: Wiley 1998
Subjects:
Online Access:https://hdl.handle.net/10568/96000
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author Abamu, F.J.
Alluri, K.
author_browse Abamu, F.J.
Alluri, K.
author_facet Abamu, F.J.
Alluri, K.
author_sort Abamu, F.J.
collection Repository of Agricultural Research Outputs (CGSpace)
description The additive main effects and multiplicative interaction (AMMI) model is used to analyse the grain yield data of 13 rice genotypes grown in 12 rainfed lowland rice environments. The trials were organized by the International Network for Genetic Evaluation of Rice in Africa (INGER‐Africa) and conducted in Nigeria. Main effects due to environments (E), genotypes (G) and G × E interaction were found to be significant (P = 0.001). Cross validation analysis suggested that an AMMI model with one interaction principal component axis (IPCA) was most useful predictively, whereas Gollobs' test declared two components, IPCA1 and IPCA2, statistically significant (P = 0.01). The IPCAl, however, accounted for most (47.8%) of the G × E sum of squares. Correlation and regression analysis, and relative scatter of genotype and environment points on the AMMI biplot suggest that the interaction partitioned in IPCA1 resulted from differences in the days to flowering among the genotypes. The paper discusses these in relation to the occurrence of Fe toxicity at the test sites and varietal tolerance to the stress.
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spelling CGSpace960002024-08-27T10:35:46Z AMMI analysis of rainfed lowland rice (Oryza sativa) trials in Nigeria Abamu, F.J. Alluri, K. oryza sativa g × e interaction varietal testing The additive main effects and multiplicative interaction (AMMI) model is used to analyse the grain yield data of 13 rice genotypes grown in 12 rainfed lowland rice environments. The trials were organized by the International Network for Genetic Evaluation of Rice in Africa (INGER‐Africa) and conducted in Nigeria. Main effects due to environments (E), genotypes (G) and G × E interaction were found to be significant (P = 0.001). Cross validation analysis suggested that an AMMI model with one interaction principal component axis (IPCA) was most useful predictively, whereas Gollobs' test declared two components, IPCA1 and IPCA2, statistically significant (P = 0.01). The IPCAl, however, accounted for most (47.8%) of the G × E sum of squares. Correlation and regression analysis, and relative scatter of genotype and environment points on the AMMI biplot suggest that the interaction partitioned in IPCA1 resulted from differences in the days to flowering among the genotypes. The paper discusses these in relation to the occurrence of Fe toxicity at the test sites and varietal tolerance to the stress. 1998-09 2018-07-05T06:30:25Z 2018-07-05T06:30:25Z Journal Article https://hdl.handle.net/10568/96000 en Limited Access Wiley Abamu, F. & Alluri, K. (1998). AMMI analysis of rainfed lowland rice (Oryza sativa) trials in Nigeria. Plant Breeding, 117(4), 395-397.
spellingShingle oryza sativa
g × e interaction
varietal testing
Abamu, F.J.
Alluri, K.
AMMI analysis of rainfed lowland rice (Oryza sativa) trials in Nigeria
title AMMI analysis of rainfed lowland rice (Oryza sativa) trials in Nigeria
title_full AMMI analysis of rainfed lowland rice (Oryza sativa) trials in Nigeria
title_fullStr AMMI analysis of rainfed lowland rice (Oryza sativa) trials in Nigeria
title_full_unstemmed AMMI analysis of rainfed lowland rice (Oryza sativa) trials in Nigeria
title_short AMMI analysis of rainfed lowland rice (Oryza sativa) trials in Nigeria
title_sort ammi analysis of rainfed lowland rice oryza sativa trials in nigeria
topic oryza sativa
g × e interaction
varietal testing
url https://hdl.handle.net/10568/96000
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