Additive main effects and multiplicative interactions model (AMMI) and genotype main effect and genotype by environment interaction (GGE) biplot analysis of multi-environmental wheat variety trials | Zendy

Worku Negash Asnake | Zendy; Mwambi Henry | Zendy; Zewotir Temesgen | Zendy; Taye Girma | Zendy

Open Access

Additive main effects and multiplicative interactions model (AMMI) and genotype main effect and genotype by environment interaction (GGE) biplot analysis of multi-environmental wheat variety trials

Author(s) -

Worku Negash Asnake,

Mwambi Henry,

Zewotir Temesgen,

Taye Girma

Publication year - 2013

Publication title -

african journal of agricultural research

Language(s) - English

Resource type - Journals

ISSN - 1991-637X

DOI - 10.5897/ajar2012.6648

Subject(s) - ammi , biplot , gene–environment interaction , genotype , main effect , grain yield , principal component analysis , interaction , repeatability , cultivar , stability (learning theory) , yield (engineering) , multiplicative function , microbiology and biotechnology , agronomy , mathematics , biology , statistics , genetics , computer science , mathematical analysis , materials science , machine learning , gene , metallurgy

Genotype by environment (G×E) interaction is associated with the differential performance of genotypes tested at different locations and in different years, and influences selection and recommendation of cultivars. Wheat genotypes were evaluated in six environments to determine the G×E interactions and stability of the genotypes. Additive main effects and multiplicative interactions (AMMI) was conducted for grain yield of both year and it showed that grain yield variation due to environments, genotypes and (G×E) were highly significant (p <0.01). Stability for grain yield was determined using genotype plus genotype by environment interaction (GGE) biplot analysis. The first two principal components (PC1 and PC2) were used to create a 2-dimensional GGE biplot. Which-wonwhere pattern was based on six locations in the first and five locations in the second year for all the 20 genotypes. The resulting pattern is one realization among many possible outcomes, and its repeatability in the second was different and a future year is quite unknown. A repeatability of whichwon-where pattern over years is the necessary and sufficient condition for mega-environment delineations and genotype recommendation.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research