Assessment genotype x environment interactions for grain yield in maize hybrids using AMMI and GGE biplot analyses

Assessment genotype x environment interactions for grain yield in maize hybrids using AMMI and GGE biplot analyses

Seventeen hybrid maize genotypes were evaluated at four locations (Yenişehir- Marmora Region; Bornova-Aegean Region; Ceyhan-Mediterranean Region; Seyhan- Mediterranean Region) in 2005 and 2006 cropping seasons under irrigated conditions in Turkey. The analysis of variance for grain yield of the 17 hybrid genotypes tested in eight environments showed mean squares of environments, genotypes and GEI (genotype x environment interaction) were highly significant and accounted for 62.1%, 12.5% and 25.4% of treatment combination sum of squares, respectively. To determine the effects of GEI on yields, the data were subjected to additive main effects and multiplicative interaction (AMMI) and the GGE biplot analysis. Although mean grain yield of the check cultivar G12 was higher than those of experimental hybrids, difference between G12 and G16, which is the most stable genotype according to AMMI and GGE biplot, was insignificant. It is understood that the experimental hybrid maize G16 can be proposed in reliably for growing by the farmers. Also, it was detected that only the test environment E3 (Ceyhan location) may be sufficient for deciding about which experimental hybrids can be recommended, instead of four test locations (Ceyhan, Seyhan, Bornova and Yenişehir) in this study. In addition, it is concluded that there is no difference between the AMMI and GGE biplot analysis in evaluation of experimental maize hybrids and test environments in this research and that both methods can be used successfully in determining suitable locations for maize hybrids in the environments under Mediterranean climate conditions.

___

  • Annicchiarico, P., 1997. Joint regression vs. AMMI analysis of genotype-environment interactions for cereals in Italy. Euphytica 94: 53-62.
  • Admassu, S., Nigussie, M., Zelleke, H., 2008. Genotype x environment interaction and stability analysis for grain yield (Zea mays L.) in Ethiopia. Asian J. Plant Sci., 7 (2): 163-169.
  • Crossa, J., 1990. Statistical analysis of multilocation trials. Adv. Agron., 44: 55-85.
  • Crossa, J., Gauch, H.G., Zobel, R.W., 1990. Additive main effects and multiplicative interaction analysis of two international maize cultivar trials. Crop Sci., 30: 493-500.
  • Ding, M., B. Tier, W. Yan, 2007. Application of GGE biplot analysis to evaluate Genotype (G), Environment (E) and GxE interaction on P. radiata: a case study. Paper presented to Australasian Forest Genetics Conference Breeding for Wood Quality, 11-14 April 2007, Hobart, Tasmania, Australia.
  • Eberhart, S.A., and W. A. Russel. 1966. Stability parameters for comparing varieties. Crop Science, 6:36-40.
  • Fan, X.M., Kang, M.S., Chen, H., Zhang, Y., Tan, J., Xu, C., 2007. Yield stability of maize hybrids evaluated in multi-environment trials in Yunnan, China. Agron. J., 99: 220–228.
  • Finlay, K.W., and G. N. Wilkinson. 1963. The analysis of adaptation in a plant breeding programme. Aust. J. Agri. Res. 14: 742-754.
  • Gauch, H.G., 1992. Statistical analysis of regional yield trials: AMMI analysis of factorial designs. Elsevier, Amsterdam, 278 pp.
  • Gauch, H.G. and Zobel, R.W., 1996. AMMI analysis of yield trials. In: Genotype by Environment Interaction (Kang, M.S., Gauch, H.G., ed.). CRC Press, Boca Raton, FL, pp.85-122.
  • Gauch, H.G. and Zobel, R.W., 1997. Identifying mega-environment and targeting genotypes. Crop Sci., 37: 311-326.
  • Gauch, H.G., 2006. Statistical analysis of yield trials by AMMI and GGE. Crop Sci., 46: 1488-1500.
  • Kaya, Y., Palta, C., Taner, S., 2002. Additive main effects and multiplicative interactions analysis of yield performance in bread wheat genotypes a cross environments. Turk. J. Agric. For., 26: 275-279.
  • Kaya, Y., Akcura, M., Taner, S., 2006. GGE-biplot analysis of multi-environment yield trials in bread wheat. Turk. J. Agric. For., 30: 325-337.
  • Kroonenberg, P.M., 1997. Introduction to biplots for GxE Tables, University of Queensland, Brisbane. http://www.ggebiplot.com/Kroonenberg1997.pdf Access date: 07.08.2009.
  • Lin, C.S., Binns, M.R., Lefkovitch L.P., 1986. Stability analysis: Where do we stand? Crop Sci., 26: 894-900.
  • Ma, B. L., W. Yan, L. M. Dwyer, J. Frégeau-Reid, H. D. Voldeng, Y. Dion, and H. Nass. 2004. Graphic analysis of genotype, environment, Nitrogen fertilizer, and their interaction on Spring Wheat yield. Agron. J., 96: 169-180.
  • Nachit, M.N., Sorrells, M.E., Zobel, R.W., Gauch, H.G., Fischer, R.A., Coffman, W.R., 1992. Association of environmental variables with sites’mean grain yield and components of genotype-environment interaction in durum wheat. J. Genet. Breed., 46: 369-372.
  • Yamada, Y. 1962. GEI and genetic correlation of the same trait under different environments. Jap. J. Genetics, 37:498-509.
  • Yan, W., Hunt, L.A., Sheng, Q., Szlavnics, Z., 2000. Cultivar evaluation and megaenvironment investigation based on GGE biplot. Crop Sci., 40: 596-605.
  • Yan, W., 2001. GGE biplot: A windows application for graphical analysis of multienvironment trial data and other types of two-way data. Agron. J., 93: 1111- 1118.
  • Yan, W., Kang, M.S., 2003. GGE biplot analysis: A graphical tool for breeders, geneticists, and agronomists. CRC Press, Boca Raton, FL, 288 pp.
  • Yan, W., Kang, M.S., Ma, B., Woods, S., Cornelius, P.L., 2007. GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Sci., 47: 643-655.
  • Zobel, R.W., Wright, M.J., Gauch, J.H.G., 1988. Statistical analysis of a yield trial. Agron. J., 80: 388-393.