scholarly journals Genotype - Environment Interaction for Plant Development and Some Yield Components in Common Bean (Phaseolus vulgaris L.) during the 2012 Wet Season

2014 ◽  
Vol 2 (1) ◽  
pp. 001-008 ◽  
Author(s):  
Christopher Nwadike ◽  
◽  
Terkimbi Vange ◽  
A.E. Ochigbo
Keyword(s):  
Phaseolus Vulgaris ◽  
Common Bean ◽  
Plant Development ◽  
Yield Components ◽  
Environment Interaction ◽  
Phaseolus Vulgaris L ◽  
Wet Season ◽  
Genotype Environment Interaction

Effect of Seedbed Type on Yield and Yield Components of Common bean (Phaseolus vulgaris L.) Commercial Cultivars

2006 ◽  
Vol 5 (4) ◽  
pp. 583-588 ◽  
Author(s):  
Loth S. Mulungu ◽  
Akwilin J.P. Tarim ◽  
Shazia O.W.M. Reuben . ◽  
Daniel N. Lema . ◽  
Rhodes H. Makundi . ◽  
...  
Keyword(s):  
Phaseolus Vulgaris ◽  
Common Bean ◽  
Yield Components ◽  
Phaseolus Vulgaris L ◽  
Commercial Cultivars ◽  
Yield And Yield Components

scholarly journals GGE-Biplot Analysis of Multi-Environment Yield Trials of Common Bean (Phaseolus vulgaris L.) in the southern Ethiopia

2019 ◽  
Vol 8 (1) ◽  
pp. 35
Author(s):  
Yayis Rezene
Keyword(s):  
Phaseolus Vulgaris ◽  
Common Bean ◽  
Genotype By Environment Interaction ◽  
Breeding Strategy ◽  
Southern Region ◽  
Southern Ethiopia ◽  
Environment Interaction ◽  
Phaseolus Vulgaris L ◽  
Yield Data ◽  
Lattice Design

The present study was conducted on thirty-six common beans (Phaseolus 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 6 x 6 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) bi-plot methodology was used for graphical presentation of yield data after subjecting the genotypic means of each environment to GGE Bi-plot software. The first two principal components (AXIS 1 and AXIS2) were used to display a two-dimensional GGE bi-plot. 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.

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