AMMI and AMMI based analysis of phenotypic stability in wheat-agropyron disomic addition lines

Paper Details

Research Paper 01/10/2014
Views (189) Download (8)
current_issue_feature_image
publication_file

AMMI and AMMI based analysis of phenotypic stability in wheat-agropyron disomic addition lines

Ezatollah Farshadfar, Mojgan Farhadi
J. Bio. Env. Sci.5( 4), 548-557, October 2014.
Certificate: JBES 2014 [Generate Certificate]

Abstract

In order to identify QTLs controlling yield stability in Agropyron using AMMI and AMMI based stability statistics an experiment was conducted in three environments. Combined analysis showed significant genotype × environment interaction (GEI) indicating the presence of genetic variation and possible chromosomal localization of QTLs controlling adaptation in agropyron. AMMI analysis exhibited that the two multiplicative axis terms explained 71.35% and 28.75% of GEI sum of squares, respectively. According to biplot analysis G1(E1) and G2 (E2) (adaptive group 1) exhibited specific adaptability for irrigated environment. Genotypes G5 (E5) and G7 (E7) (adaptive group 2) revealed specific adaptation for rainfed environments E2 and E3. The accessions G3 (E3), G6 (E6) and G8 (E8) (adaptive group 3) on the IPCA= 0 showed stability and general adaptability with grain yield close to mean yield and negligible interaction. AMMI1 (IPCA1) and AMMI2 (IPCA2) biplot introduced G7 (E7) and G4 (E4) with high grain yield and specific adaptability for environments E3 and E2 (stress conditions), G1 (E1) and G2 (E2) with low grain yield and specific adaptation for irrigated environment (E1). G5 (E5) and G6 (E6) were discriminated as stable genotypes with high and average yield, respectively. It is concluded that QTLs controlling specific adaptation in agropyron are distributed on chromosomes E1and E2 (irrigated conditions) and chromosomes E5 and E7 (rainfed conditions), while QTLs monitoring stability and general adaptability are mainly located on chromosome E3, E5 with average grain yield and E6 with high grain yield. AMMI based stability statistics were positively correlated (an acute angle), and associated with grain yield except AMGEi (right angle). It is concluded that all of the AMMI based measures except AMGEi discriminate stable entries with high grain yield at the same manner.

VIEWS 5

Annicchiarico P. 1997. Additive main effects and multiplicative interaction (AMMI) analysis of genotype location interaction in variety trials repeated over years. Theoretical and Appllied Genetic 94, 1072-1077.

Crossa J. 1990. Statistical analysis of multilocation trials. Advances in Agronomy 44, 55-85.

Dehghani H, Sabaghpour SH, Ebadi A. 2010. Study of genotype× environment interaction for chickpea yield in Iran. Agronomy Journal 102(1), 1-8.

Farshadfar E, Sutka J. 2003. Locating QTLs controlling adaptation in wheat using AMMI model. Cereal Research Communication 31, 249–255.

Farshadfar E. 2008. Incorporation of AMMI stability value and grain yield in a single non-parametric index (GSI) in bread wheat. Pakistan Journal of Biological Sciences 11(14), 1791-1796.

Gabriel KR. 1971. The biplot graphic display of matrices with application to principal component analysis. Biometrika 58, 453-467.

Gale MD, Miller TE. 1987. The introduction of alien genetic variation into wheat. In: Wheat Breeding, Its Scientific Basis (Ed. FGH Lupton). Chapman and Hall, UK. 173-210.

Gauch HG, Zobel RW. 1996. AMMI analysis of yield trials. In: Kang, M.S. and Gauch, Jr. H.G. (eds.). Genotype by environment interaction. PP. 85-122. Press. Boca Raton, FL

Gauch HG. 1992. Statistical analysis of regional yield trials. AMMI Analysis of Factorial Designs. Elsevier, New York

Gollob HF. 1968. A statistical model which combines features of factor analytic and analysis of variance techniques. Psychometrika 33, 73-115.

Kempton RA. 1984. The use of biplot in interpreting variety by environment interaction. Journal of Agricultural Sciences 122, 335-342.

Khodadadi  M,  Fotokian  MH,  Miransari  M. 2011. Genetic diversity of wheat (Triticum aestivum L.) genotypes based on cluster and principal component analyses for breeding strategies. Australian Journal of Crop Science 5(1),17-24.

Kroonenberg PM. 1995. Introduction to biplots for G.E tables. Dep. of Mathematics Research. Report. No. 51, University of Queensland Australia

Mortazavian SMM, Nikkhah HR, Hassani FA, M. Sharif-al-Hosseini M. 2014. GGE Biplot and AMMI Analysis of yield performance of barley genotypes across different environments in Iran. Journal of Agricultural Science and Technology 16, 609-622.

Pourdad SS, Mohammadi R. 2008. Use of stability parameters for comparing safflower genotypes in multienvironment trials. Asian Journal of Plant Science 7, 100-104.

Purchase JL,  Hatting H,  Van  Deventer CS. 2000. Genotype × environment interaction of winter wheat in South Africa: II. Stability analysis of yield performance. South African Journal of Plant and Soil 17, 101-107.

Romagosa I, Fox PN. 1993. Genotype × environment interaction and adaptation. In: Hayward, M.D., Bosemark, N.O., Romagosa, I. (Eds.), Plant Breeding: Principles and Prospects. Chapman & Hall, London. pp. 373-390.

Rozgard F, Farshadfar E. 2014. Locating QTLs controlling genotypic stability in Rye using AMMI model and AMMI based stability statistics. Journal of Biodiversity and Environmental Sciences 4(5), 85-93.

Rubio J, Flores F, Moreno MT, Cubero JI, Gil J. 2004. Effects of the erect/bushy habit, single/double pod and late/early flowering genes on yield and seed size and their stability in chickpea. Field Crops Research 90, 255–262.

Sneller CH, Kilgore-Norquest L, Dombek D. 1997. Repeatability of yield stability statistics in soybean. Crop science 37(2), 383-390.

Raju BMK. 2002. Study of AMMI model and its biplots. Journal of the Indian Society of Agricultural Statistics 55(3), 297-322.

Szakacs E, Molnar-Lang M. 2010. Molecular cytogenetic evaluation of chromosome instability in Triticum aestivumSecale cereale disomic addition lines. Journal of Appllied Genetics 51(2), 149-152.

Voltas FA, Sombrero A, Lafarga A, Igartua E, Romagosa I. 1999. Integrating statistical and ecophysiological analyses of genotype by environment interaction for grain filling of barley I. Field Crops Research 62, 63–74.

Yan W. 2002. Singular value partitioning in biplot analysis of multi-environment trial data. Agronomy Journal 94, 990-996.

Zali H, Farshadfar E, Sabaghpour SH. 2011. Non-parametric analysis of phenotypic Stability in chickpea (Cicer arietinum L.) genotypes in Iran. Crop Breeding Journal 1(1), 89-100.

Zali H, Farshadfar E, Sabaghpour SH, Karimizadeh R. 2012. Evaluation of genotype × environment interaction in chickpea using measures of stability from AMMI model. Annals of Biological Research 3 (7), 3126-3136.

Zavala-Garcia F, Bramel-Cox PJ, Eastin JK, Witt MD, Andrews DJ. 1992. Increasing the efficiency of crop selection for unpredictable environments. Crop Science. 32, 51-57.

Zobel RW, Wright MJ, Gauch HG. 1988. Statistical analysis of a yield trial. Agronomy Journal 80, 388-393.