Genotype × environment interaction in rice using measures of stability from AMMI model
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Keywords:
Rice, AMMI model, stability, genotype × environment interaction, heatmapAbstract
The present research was conducted to study the stability analysis and comparison between different stability measures from AMMI model in nine rice genotypes. The experiment was conducted in rabi/dry season during 2010-11 in randomized complete block design with three replications at experimental farm of NRRI research station. Eleven stability measures of AMMI model have been used in this study. Spearman's rank correlation was used to measure the relationship between measures of stability from AMMI model. Genotypic and environment effects are significant at 1% whereas their GE interaction is significant at 5%. WITA12 genotype was found to be the most stable while Lalat was found to be the least stable using seven models AMMI Stability Index, AMMI based stability parameter, Sum Across Environments of Absolute Value of GEI Model, Annicchiarico's D Parameter values, Stability Measure based on Fitted AMMI Model, Modified AMMI Stability Index and Absolute Value of the Relative Contribution of IPCs to the Interaction. Annada was most stable and Naveen was least stable using three models Zhang's D Parameter value, Averages of the Squared Eigenvector Values and Simultaneous Selection Index for Yield and Stability. IR64 was the most stable using Sums of the Absolute Value of the IPC Scores Model. Sums of the Absolute Value of the IPC Scores positively and significantly correlated with AMMI Stability Value, Averages of the Squared Eigenvector Values, Modified AMMI Stability Value but not correlated with Sum Across Environments of GEI Model. Modified AMMI Stability Value positive and significantly correlated with Averages of the Squared Eigenvector Values while negatively correlated with Sum Across Environments of GEI Model. Averages of the Squared Eigenvector Values significantly and positively correlated with AMMI Stability Value but negatively correlated with Sum Across Environments of GEI Model.
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