Journal of
Plant Breeding and Crop Science

  • Abbreviation: J. Plant Breed. Crop Sci.
  • Language: English
  • ISSN: 2006-9758
  • DOI: 10.5897/JPBCS
  • Start Year: 2009
  • Published Articles: 363

Article in Press

GGE-Biplot Analysis of Multi-Environment Yield Trials of common bean (Pharsalus vulgaris L.) in the southern Ethiopia

Yayis Rezene Tedla

  •  Received: 28 December 2016
  •  Accepted: 19 September 2018
The present study was conducted on thirty-six common bean (Pharsalus vulgaris L.) Genotypes across six contrasting environments defined for its different soil fertility status and located at the southern Ethiopia. The genotypes were arranged in 4 x 4 triple lattice design and executed for two successive main cropping seasons with the objectives to evaluate yield performance of common bean genotypes and identification of mega environments. GGE (i.e., G = genotype and GE = genotype by environment, interaction) biplot methodology was used for graphical presentation of yield data after subjecting the genotypic means of each environment to GGE Biplot software. The first two principal components (AXIS 1 and AXIS2) were used to display a two-dimensional GGE biplot. Thus, genotypic AXIS1 scores >0 classified the high yielding genotypes while AXIS2 scores <0 identified low yielding genotypes. Unlike genotypic AXIS1, genotypic AXIS2, scores near zero showed stable genotypes whereas large AXIS2 scores classified the unstable ones. The environmental AXIS1 were related to crossover nature of GEI while AXIS2 scores were associated with non-cross over GEI. The six test environments in the southern region were divided in to two distinct mega environments (Mega-1 and 2). Mega-1 constituted GOHF13, ARMF12 and ARLF13 while genotype 14 (SCR10) being the best winner, on the other hand, Mega-2 contained GOHF12 and while common bean genotype 20(SCR17) being the best winner. The results of this study indicated that breeding for specific adaptation should be taken as a breeding strategy in southern region to exploit positive GEI to increase production and productivity of common bean

Keywords: GGE, GEI, mega environments