Genotype-environment interaction and stability analysis for tuber yield of potato (Solanumtuberosum L.) genotypes

Authors

  • Mohammed Beriso Sinana Agricultural Research Center, Oromia Agricultural Research Institute, Ethiopia.
  • Getachaw Asefa Sinana Agricultural Research Center, Oromia Agricultural Research Institute, Ethiopia.

Keywords:

AMMI, ASV, Yield, Biplot, Genotypes, GxE interaction, PCA

Abstract

Yield data of 12 potato (Solanumtuberosum L.) genotypes tested across 9 rain-fed environments during the 2016-2018 growing season using RCBD in 3 replications were analyzed using the AMMI model. 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 as well as GxE interaction. The model revealed that differences between the environments accounted for about 57.73% of the treatment sum of squares. The genotypes and the GxE interaction also accounted significantly for 16.87 % and 25.41% respectively of the treatment SS. The first principal component axis (PCA 1) of the interaction captured 56.44% of the interaction sum of squares. Similarly, the second principal component axis (PCA2) explained a further 13.67% 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 70.11% of the GxE interaction SS, leaving 29.89% of the variation in the GxE interaction in the residual. The AMMI and AMMI stability value (ASV) identified G3 and G12 as the stable and high yielding genotypes.

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. Biometr., 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., Mozaffar Roostaei, M., Yousef, A., Mostafa, A., 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.

Published

2020-07-20

How to Cite

Beriso, M., & Asefa, G. . (2020). Genotype-environment interaction and stability analysis for tuber yield of potato (Solanumtuberosum L.) genotypes. Scientific Journal of Crop Science, 9(4), 425-429. Retrieved from http://sjournals.com/index.php/sjcs/article/view/1524

Issue

Section

Original Article