AMMI analysis of genotype × environment interaction in bread wheat over rainfed and irrigated conditions
Paper Details
AMMI analysis of genotype × environment interaction in bread wheat over rainfed and irrigated conditions
Abstract
In order to determine stable bread wheat accessions, field experiments were conducted with 20 genotypes for 4 consecutive years under two different irrigated and rainfed conditions. The experiment was laid out in a completely randomized block design with three replications in each environment. Combined analysis of variance showed highly significant differences for the GE interaction indicating the possibility of selection for stable entries. The results of additive main effect and multiplicative interaction (AMMI) analysis revealed that 10% of total variability was justified by the GE interaction which was 2.5 times more than that of genotypes. Ordination techniques displayed high differences for the interaction principal components (IPC1, IPC2 and IPC3), exhibiting that 83% of the GE sum of squares was justified by AMMI1, AMMI2 and AMMI3, i.e. 3.77 times more than that explained by the linear regression model displaying the relative efficiency of AMMI1 model in comparison with regression model. The results of AMMI model and biplot analysis indicated 3 stable genotypes with high grain yield and general adaptability tfor both rainfed and irrigated conditions.
Alagaswamy G, Chandra S. 1998. Parttern analysis of international sorghum multi-environment trials for grain-yield adaptation. Theoretical Applied Genetic 96, 397-405.
Asenjo CA, Benzus R, Acciaresi H. 2003. Genotype-environment interactions in rice (Oriza sativa L.) in temperate region using the joint regression analysis and AMMI methods. Cereal Research Communication 31, 97-104.
Basford KE, Federer WT, Delacy IH. 2004. Mixed model formulations for Multi-environment trails. Agronomy Journal 96, 143-147.
Crossa J, Fox PN, Pfeiffer WH, Rajaram S, Gauch, HG. 1991. AMMI adjustment for statistical analysis of an interactional wheat yield trail. Theoretical Applied Genetic 81, 27-37.
Eberhart SA, Russel W A. 1966. Stability parameters for comparing varieties. Crop Science 6, 36-40.
Farshadfar E. 1998. Application of biometrical genetic in plant breeding. vol 2. Razi University press. Kermanshah. Iran.
Farshadfar E, Farshadfar M, Sutka J. 1999. Genetic analysis of phenotypic stability parameters in wheat .Acta Agronomica Hungarica. 47, 109-116.
Farshadfar E, Sutka J. 2003. Locating QTLs controlling adaptation in wheat using AMMI model .Cereal Research Communication 31, 249-254.
Farshadfar E, Sutka J. 2006. Biplot analysis of genotype- environment interactin in durum wheat using the AMMI model. Acta Agronomica Hungarica 54, 459-467.
Finlay KW, Wilkinson GN. 1963. The analysis of adaptation in plant-breeding program. Australian Journal of Agricultural Research 14, 742-754.
Gabriel KR. 1971. The biplot graphic display of matrices with application to principal component analysis. Biometrika 58, 453-467.
Gauch HG, Zobel RW. 1989. Accuracy and selection success in yield trials analysis. Theoretical. applied genetics 77, 443-481.
Gauch HG. 1992. Statistical analysis of regional yield trials. AMMI analysis of factorial designs. Elsevier, New York.
Hayward MD, Bosemard NO, Romagosa L. 1993. Plant Breeding, Principles and Prospects. Chapman and Hall. London. U.K.
Hugh G, Gauch GH. 1988. Model selection and trials with interaction. validation for yield Biometrics 44, 705-715.
Jalilnejad N. 2002. Evaluation of Genotype × environment interaction in hexaploid and tetraploid wheat using AMMI model and pattern analysis. M.Sc. Thesis.Razi University. Kermanshah, Iran.
Manrique K, Hermann H. 2000. Effect of G × E interaction on root yield and beta-carotene content of selected sweet potato varieties and breeding clones. Tropical Agriculture 119, 281-286.
Oritza R, Wagorie WW, Hill J, Chandra S, Madsen S, Stolen O. 2001. Heritability and correlation among genotype by environment stability statistics for grain yield in bread wheat. Theoretical Applied Genetic 103, 469-474.
Snedecor GW, Cochan WG. 1989. Statistical methods. Iowa State University Press, Ames/IO.
Tarakanovas P, Rusgas V. 2006. Additive main effect and multiplicative interaction analysis of grain yield of wheat varieties in Lithuania. Agronomy Research 4, 91-98
Thamson WE, Philips SB. 2006. Methods to evaluate wheat cultivar testing environment and improve cultivar selection protocols. Field Crops Research 99, 87-95.
Vergas M, Crossa J, Eeuwijk FV, Sayre KD, Reynolds MP. 2001. Interpreting treatment×environment interaction in agronomy trials. Agronomy Journals 93, 949-960.
Wade LJ, Sarkarung S, Melran CG, Guhey A, Quader B, Boonrite C, Amarante ST, Sarawgi AK, Hauge A, Harnpichitritaya D, Pamplona A, Bhamri MC. 1995. Genotype by environment interaction and selection method for indentifying improved rainfed lowland rice genotypes. International Rice Research Institute. P. O. box 933. Manila. Philippines. 883-900.
Weikai Y, Hant LA, Qinglai S, Szalvincs Z. 2000. Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Sci 40, 597-605.
Zobel RW, Wright MJ, Gauch HG. 1988. Statistical analysis of yield trial. Agronomy Journal. 80, 388-393.
Ezatollah Farshadfar, Bita Jamshidi, Azam Nazari, 2013. AMMI analysis of genotype × environment interaction in bread wheat over rainfed and irrigated conditions. J. Biodiv. Environ. Sci., 3(12), 134-139.
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