Stability analysis for grain yield of black cumin (Nigella sativa L.) genotypes in Bale, South-East Ethiopia
Keywords:
AMMI, ASV, Yield, Biplot, Genotypes, GxE interaction, PCAAbstract
Yield data of 12 black cumin (Nigella sativa L.) cultivars tested across 9 rain-fed environments during the 2013-2015 growing season using RCBD in 3 replications. The AMMI analysis tested in nine environments (years) were showed that the yield was significantly affected (P<0.001) by genotypes and environment main effects. But non significant for GxE interaction. The model revealed that differences between the environments accounted for about 90% of the treatment sum of squares. The genotypes and the GxE interaction also accounted significantly for 4% and 6% respectively of the treatment SS. The first principal component axis (PCA 1) of the interaction captured 51.32% of the interaction sum of squares. Similarly, the second principal component axis (PCA2) explained a further 18.20% of the GEI sum of squares. The mean squares for the PCA 1 and PCA 2 were significant at P=0.01 and cumulatively contributed to 69.52% of the GxE interaction SS, leaving 30.37% of the variation in the GxE interaction in the residual. The AMMI and AMMI stability value (ASV) identified G10 as the most stable and high yielding genotype.
References
Crossa, J., 1990. Statistical analysis of multilocation trials. Adv. Agron., 44, 55-85.
Ebdon, J.S., Gauch, H.G., 2002a. Additive main effect and multiplicative interaction analysis of national turfgrass performance trials: I. Interpretation of genotype x environment interaction. Crop. Sci., 42, 489-496.
Gauch, H.G., 1988. Model selection and validation for yield trials with interaction. Biometrics, 44, 705-715.
Gauch, H.G., 2006. Statistical analysis of yield trials by AMMI and GGE. Crop. Sci., 46, 1488-1500.
Gauch, H.G., Zobel, R.W., 1990. Imputing missing yield trial data. Theor. Appl. Genet., 79, 753-761.
Holhs, T., 1995. Analysis of genotype environment interactions. S. Afr. J. Sci., 91, 121-124.
Lin, C.S., Binns, M.R., 1988b. A method of analyzing cultivar × location 10 year experiments: A new stability parameter. Theor. Appl. Genet., 76, 425-430.
Mohammadi, R., Amri, A., 2008. Comparison of parametric and non-parametric methods for selecting stable and adapted durum wheat genotypes in variable environments. Euphytica, 159, 419-432.
Mohammadi, R., Roostaei, M., Ansari, Y., Amri, A., 2010. Relationships of phenotypic stability measures for genotypes of three cereal crops. Can. J. Plant Sci., 90, 819-830.
Samonte, S.O.P.B., Wilson, L.T., McClung, A.M., Medley, J.C., 2005. Targeting cultivars onto rice growing environments using AMMI and SREG GGE biplot analysis. Crop. Sci., 45, 2414-2424.
Yan, W., Hunt, L.A., Sheng, Q., Szlavnics, Z., 2000. Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop. Sci., 40, 597-605.
Zobel, R.W., Wright, M.S., Gauch, H.G., 1988. Statistical analysis of a yield trial. Agron. J., 80, 388-393.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2017 Mohammed Beriso, Getachew Asefa
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.