In multi-environment trials, accurate estimation of yields in individual environments and
astute choice of models to extract and display agronomically relevant signals enhance
genotype evaluation and accelerate breeding progress. The objective of this study is to (i)
compare patterns of genotype × environment interaction (GE) using additive main effect
and multiplicative interaction (AMMI) biplots arising from cell means versus best linear
unbiased predictors (BLUPs), and (ii) examine some features of the genotype main effect
plus GE interaction (GGE) in relation to AMMI in comprehending the GE patterns. A
data set generated from 39 barley genotypes grown in 18 environments (three sowing
dates and two crop protection treatments over three years) in the central highlands of
Ethiopia was used. AMMI analysis of variance based on cell means depicted the first five
principal components (PCs) to be significant. However, only the first two PCs were
significant when BLUPs were used. Partitioning of the original GE sum of squares into
signal and noise confirmed that only the first two AMMI PCs contained signals required
to explain the real GE pattern. AMMI PC1 contained 76.5% and AMMI PC2 15.9% of
the total GE variance. AMMI biplot based on BLUPs depicted patterns that were more in
tandem with agronomic interpretations than biplot based on cell mean data. PC1 of GGE
contained 66.9%, PC2 11.2% and PC3 14.5% of the total GE variance. AMMI2 explained
as much GE variance as PC1, PC2 and PC3 of GGE put together. AMMI2 biplot depicted
a GE pattern that was not obvious from GGE2. AMMI2 biplot was more similar to GGE
PC1 versus PC3 biplot than GGE2 biplot. AMMI2 was more efficient than GGE2 for
displaying patterns of GE interaction in this data set. However, GGE2 was quite elegant
and simple for presenting G and GE combined in a biplot graph including the which-wonwhere
pattern. BLUPs might improve yield estimation and pattern recognition, and that
attempting both AMMI and GGE analysis might provide important insights on genotype
performance and GE.
