Volume 5, Issue 6, November 2017, Page: 93-98
AMMI Model for Yield Stability Analysis of Linseed Genotypes for the Highlands of Bale, Ethiopia
Tadele Tadesse, Oromia Agriculture Research Institute, Sinana Agriculture Research Center, Bale-Robe, Ethiopia
Amanuel Tekalign, Oromia Agriculture Research Institute, Sinana Agriculture Research Center, Bale-Robe, Ethiopia
Gashaw Sefera, Oromia Agriculture Research Institute, Sinana Agriculture Research Center, Bale-Robe, Ethiopia
Behailu Muligeta, Oromia Agriculture Research Institute, Sinana Agriculture Research Center, Bale-Robe, Ethiopia
Received: Oct. 11, 2017;       Accepted: Oct. 25, 2017;       Published: Dec. 7, 2017
DOI: 10.11648/j.plant.20170506.12      View  1611      Downloads  62
Abstract
In order to determine stable linseed genotypes with high grain yield, field experiments were conducted with 14 genotypes for two years (2014-2015) at three locations in the highlands of Bale zone, Ethiopia. The genotypes were laid out in randomized complete design with four replications in each environment. The objective of this study was to identify and recommend high yielder, stable genotypes for testing sites and similar agro-ecologies using the stability parameters. The combined analysis of variance showed highly significant differences for the genotypes, environment, and genotype by environment interaction indicating the possible existence of stable genotypes among the tested once. The results of AMMI (additive main effect and multiplicative interaction) analysis indicated that the first two AMMI (AMMI1-AMMI2) were highly significant (P<0.01). The partitioning of the total sum of square exhibited that the effect of environment was a predominant source of variation followed by genotypes and GE interaction effect. Based on the stability parameters regression coefficient, deviation from regression and mean grain yield out of the tested G6, G9, G11, and G8 were found to be stable. However, the AMMI Stability Value (ASV) discriminated genotypes G12, G4, G6, G13, and G9 as stable genotypes respectively. Based on the Genotypes Selection Index (GSI) the most stable genotypes with high grain yield were G6 and G9. Therefore these two genotypes were identified as candidate genotypes to be verified for possible release.
Keywords
AMMI, ASV, Stability, GSI
To cite this article
Tadele Tadesse, Amanuel Tekalign, Gashaw Sefera, Behailu Muligeta, AMMI Model for Yield Stability Analysis of Linseed Genotypes for the Highlands of Bale, Ethiopia, Plant. Vol. 5, No. 6, 2017, pp. 93-98. doi: 10.11648/j.plant.20170506.12
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reference
[1]
Becker HC and Leon J. 1988. Stability analysis in plant breeding. Plant breeding, 101: 1-23
[2]
Crosaa J. 1990. Statistical analysis of multilocation trials. Advance in Agronomy, 44: 55-85
[3]
Crossa J, Fox PN, Pfeiffer WH, Rajaram S and Gauch HG. 1991 AMMI adjustment for statistical analysis of an interactional wheat yield trial. Theor. App Gent, 81: 27-37
[4]
CSO. 1984. Time Series Data on Area, Production and Yield of Principal Crops by Regions, 1979/80-1983/84. Central Statistics Office, Addis Ababa
[5]
Farshadfar E, Farshadfar and M, Sutka J. 2000. Combining ability analysis of drought tolerance in wheat over different water regiems. Acta Agron Hung, 48(4): 353-361
[6]
Farshadfar E and Sutka J. 2003. Locating QTLs controlling adaptation in wheat using AMMI model. Cereal Res Commun 31: 249-254
[7]
Farshadfar E, and Sutka E. 2006. Biplot analysis of genotype-environment interacting in durum wheat using the AMMI model. Acta Agron. Hung, 54: 459-467
[8]
Farshadfar E. 2008. Incorporation of AMMI stability value and grain yield in a single non-parametric index (GSI) in bread wheat. Pak J Biol Sci, 11(4): 1791-1796
[9]
Gauch HG. 1992. Statistical anlyis of regional yield trials. AMMI analysis of factorial designs. 1st edn, Elsevier, New York, ISBN: 0-444-89240-0
[10]
Gauch HG and Zobel Rw. 1996. AMMI analysis of yield trials. In: Kang MS, Gauch HG (eds) Genotype by environment interaction. CRC press Boca Raton FL
[11]
Getinet A, and Negusei A. 1997. Highland Oil Crops: A Three Decade Research Experience in Ethiopia. Research report No. 30. Institute of Agricultural Research, Addis Ababa, Ethiopia.
[12]
Hayward MD, Besemard NO and Romagosa L. 1993. Palnt breeding, Principles and Prospects. 1st edn. Chapman and Hall, London U.K. ISBN: 0-412-43390-7
[13]
Hussein MA, Bjornstad A and Aastveit AH. 2000. SASG3 ESTAB: A SAS program for computing genotype 3 environment stability statistics. Agron J, 92: 454-459
[14]
Lin CS, Binns Mr and Lefkovitch LP. 1986. Stability analysis: where do we stand? Crop Sci, 26: 894-900
[15]
Lin CS and Binns MR. 1994. Concepts and methods for analyzing regional trial data for cultivar and location selection. Plan breed Rev, 12: 271-297
[16]
Mohamaddi R and Haghparast R. 2007 Biplot analysis of multi-environment trials for identification of winter wheat mega-environment in Iran. World J. Agri Sci, 3: 475-480
[17]
Mohammadi R and Amri A. 2008. Comparsion of parametric and non-parametric methods for selecting stable and adapted durum wheat genotypes in variable environments. Euphytica, 159: 419-432
[18]
Mohammadi R, Mozaffar Roostaei M, Yousef A, Mostafa A and Amri A. 2010. Relationship of phenotypic stability measures for genotypes of three cereal crops. Can J Plant Sci, 90:819-830
[19]
Pourdad SS and Mohammadi R. 2008. Use of stability parameters for comparing safflower genotypes in multi-environment trials. Asian J. Plant Sc, i 7: 100-104
[20]
Purchase JL, Hatting H and Vandenventer CS. 2000. Genotype x environment interaction of winter wheat in south Africa: II. Stability analysis of yield performance. South Afr J Plant Soil, 17: 101-107
[21]
Solomon A, Nigussie M, and Habtamu Z. 2008. Genotype-environment interaction and stability analysis for grain yield of maize (Zea mays L.) in Ethiopia. Asian J. Plant Sci, 7: 163-169
[22]
Tarakanovas P and Rusgas V. 2006. Additive main effect and multiplicative interaction analysis of grain yield of wheat varieties in Lithuania. Agron Res, 4: 91-98
[23]
Wade LJ, Sarkarung S, Melran CG, Guhey A and Quader B. 1995. Genotype by environment interaction and selection method for identifying improved rainfed lowland rice genotypes. 1st edn, International Rice Research Institute pp: 883-900
[24]
Yaghotipoor A and Farshadfar E. 2007. Non-parametric estimation and component analysis of phenotypic stability in chickpea (Cicer arietinum L.) Pak J Biol Sci, 10: 2646-2649
[25]
Vavilov NI. 1926. Studies on the origin of cultivated plants. Bull. Bet. and Pl. breed, 16: 139-248
[26]
Jacobsz MJ, Merwe WJCV and Westhuizen MMV 2015. Additive Main Effects and Multiplicative Interaction Analysis of European Linseed (Linum Ustatissimum L.) Cultivars under South African Conditions. Adv Plants Agric Res 2(3): 00049. DOI: 10.15406/apar.2015.02.00049
[27]
Marisol B, Susana F, Rosemarie W, Felicitas H and Burton J. 2010. Adaptation and genotype x environment interaction of flaxseed (linum usitatissimum l.) genotypes in south central chile. Chilean J. Agri. Res. 70(3): 345-356
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