The Eleventh Regional Wheat Workshop For Eastern ... - Cimmyt

Sources ofvariation for grain yield performance - Tadesse et al.
varies from place to place. Multi-environmental trials play important role in selecting the best
cultivars (or agronomic practices) for different locations and in assessing a cultivar's stability
across environments before it's commercial release (Mateo et at., 1999). Grain yield is the
major criterion for selection in multi-environment testing. Cultivars react differently to
environmental changes and differential responses of cultivars vary from one environment to
another i.e., genotype by environment (GE) interaction. The potential of a genotype to be
stable under different environments is important and understanding of the interaction is vital
for selecting superior genotypes.
GE interaction can be a result of genotype rank changes from one environment to another,
difference in scale among environments, or a combination of both (Cornelius et at., 1993).
The occurrence or absence of GE interaction in multi-environment testing of genotypes is
important in a plant breeding program. In GE interaction, it is worthwhile distinguishing
between interaction due to heterogeneity of genotypic variances among environments and the
lack of correlations of genotypic perfOlmance among environments, the latter results in reranking
of genotypes across environments (Cooper and DeLacy, 1994). Yield data observed
during multi-location trials can be divided into pattern and noise (Freeman, 1973). The
observed mean should not be taken as a true mean because of error and noise in the data and
therefore it is important to adjust (Gauch and Zobel, 1988; Zobel et at., 1988) past yields to
predict and improve future yields.
The options to improve predictive accuracy of a yield trial include improved experimental
techniques, improved experimental design (more replications or sophisticated layouts of the
replications) or more efficient statistical analysis. Many models have been developed to
describe GE interaction and the additive main effects and multiplicative interaction (AMMI)
model is a widely used statistical analysis of yield trial data. AMMI gives adjusted means,
which have better predictive accuracy and hence greater value for making selection than
unadjusted (observed) means (Gauch and Zobel, 1989). The total sum of squares (SS) for
grain yield data can be partitioned into several sources: the genotype main effect, the
environment main effect, and the genotype by environment interaction. By definition, main
effects are additive and interactions (residual from the additive model) are non-additive, and
all the three sources are important (Zobel et at., 1988) .. AMMI uses the usual analysis of
variance (ANOVA) to compute genotype and environmental additive effects and appJies
principal component analysis (PCA) to analyze non-additive interaction effects. Furthermore,
the biplot of AMMI displays both main effects (genotype and environment means) and
interactions (IPeAs) for interpretation of these relationships. Changes in Y-axis and X-axis
on the biplot shows changes in interaction and main effects, respectively. This paper uses
AMMI to analyze the multi-location yield trial conducted in 1997 and 1998 in Northwestern
Ethiopia and examines the GE interaction and identify sources for grain yield variation.
MATERIALS AND METHODS
A regional variety yield trial was conducted in 1997 and 1998 in Northwestern Ethiopia. The
trial was a full factorial consisting of 20 varieties along with the standard and local checks in
12 environments (two years at six locations). Year by site combinations were taken as an
environment. The design was a randomized complete block in four replications with a plot
size of 3 m 2 , i.e., 6 rows at 20 cm spacing and 2.5 m length. Seed rate of 150 kg ha- I and
fertilizer rate of 92/46 kg N/P 2 0 s ha- 1 were used. All other growing practices were as
recommended for all sites. The locations were Adet, Motta, Debre Tabor, Dabat, Fenote
Selam and Injibara, Ethiopia separated between 75 to 300 km from the breeding center, Adet,
17