African Journal of
Plant Science

  • Abbreviation: Afr. J. Plant Sci.
  • Language: English
  • ISSN: 1996-0824
  • DOI: 10.5897/AJPS
  • Start Year: 2007
  • Published Articles: 785

Full Length Research Paper

Adaptability and yield stability of bread wheat (Triticum aestivum) varieties studied using GGE-biplot analysis in the highland environments of South-western Ethiopia

Leta Tulu
  • Leta Tulu
  • National Agricultural Biotechnology Research Centre, P. O. Box 249, Holeta, Ethiopia.
  • Google Scholar
Addishiwot Wondimu
  • Addishiwot Wondimu
  • Department of Plant Sciences, College of Agriculture and Veterinary Science, Ambo University. P. O. Box 19, Ambo, Ethiopia.
  • Google Scholar

  •  Received: 13 February 2019
  •  Accepted: 11 April 2019
  •  Published: 30 June 2019


The objectives of this study were to evaluate released Ethiopian bread wheat varieties for yield stability using the GGE biplot method and identify well adapted and high-yielding genotypes for the highland environments of South-western Ethiopia. Twenty five varieties were evaluated in a randomized complete block design with three replications at Dedo and Gomma during the main cropping season of 2016 and at Dedo, Bedelle, Gomma and Manna during the main cropping season of 2017, generating a total of six environments in location-by-year combinations. Combined analyses of variance for grain yield indicated highly significant (p<0.001) mean squares due to environments, genotypes and genotype-by-environment interaction. Yield data were also analyzed using the GGE (that is, G, genotype + GEI, genotype-by-environment interaction) biplot method. Environment explained 73.2% of the total sum of squares, and genotype and genotype X environment interaction explained 7.16 and 15.8%, correspondingly. The first 2 principal components (PC1 and PC2) were used to create a 2-dimensional GGE biplot and explained 63.88 and 15.71% of GGE sum of squares, respectively. The GGE biplot identified two wheat growing mega-environments. The first mega environment consisted of environments E1 (Gomma-2016), E2 (Dedo-2016), E3 (Bedele-2017), E4 (Manna-2017) and E5 (Gomma-2017) with G6 (Ogolcho) as a vertex genotype. The second mega environment consisted of E6 (Dedo-2017) with G8(Hulluka) as its vertex genotype. Genotypes (G10) Mekelle-4, (G7) Hoggana, (G16) Danda’a and (G14) Ga’ambo did not fit in any of the mega-environments. Genotypes (G5) Hidasse, (G15) Kakaba, (G21) Sofumar, (G11) Shorima, (G20) Tay, (G14) Ga'ambo, (G17) Gassay and (G4) Millan were found to be the most stable genotypes with mean grain yield exceeding the grand mean. Genotypes (G14) Ga'ambo and (G20) Tay were found to be benchmarks/ideal genotypes and could be used as checks to evaluate the performance of other genotypes and also can be recommended for wider cultivation in the highland environments of South-western Ethiopia. However, bread wheat breeding research should be started to identify higher yielding genotypes for these environments with testing sites established at Bedelle and Dedo to address the two mega environments.


Key words: GGE biplot, GXE interaction, Ideal genotypes/environments, mega-environments.