Pattern analysis of genotype-by-environment interaction for grain yield in durum wheat

Abstract

SU MMARYPattern analysis, cluster and ordination techniques, was applied to grain yield data of 20 durum wheat genotypes grown in 19 diversified environments during 2005-07 to identify patterns of genotype (G), environment (E) and genotype-by-environment (GrE) interaction in durum multienvironment trials (METs). Main effects due to E, G and GrE interaction were highly significant, and 0 . 85 of the total sum of squares (SS) was accounted for by E. Of the remaining SS, the GrE interaction was almost 12 times the contribution of G alone. The knowledge of environmental and genotype classification helped to reveal several patterns of GrE interaction. This was verified by ordination analysis of the GrE interaction matrix. Grouping of environments, based on genotype performance, resulted in the separation of different types of environments. Pattern analysis confirmed the cold and warm mega-environments, and allowed the discrimination and characterization of adaptation of genotypes. However, several patterns of GrE interaction in Iran's regional durum yield trials were further discerned within these mega-environments. The warm environments tended to be closer to one another, suggesting that they discriminate among durum genotypes similarly, whereas cold environments tended to diverge more. The dwarf and early maturing breeding lines from ICARDA with low to medium yields and high contribution to GrE interaction were highly adapted to warm environments, whereas the tall and later maturing genotypes with low to high yields were highly adapted to the cold environments of Iran.

Stability analysis of maize cultivars adapted to tropical environments using AMMI analysis

“…This result is in agreement with the findings of earlier workers (BaduApraku et al 2003;Sabaghnia et al 2008;Moghaddam and Pourdad 2009). The high proportion of 63.5% contributed by environments to the total variation in grain yield, 32.8% contributed by GEI and low (3.5%) contribution by genotypes fall within the range reported by earlier workers (Fakorede and Adeyemo 1986;Badu-Apraku et al 2003, 2011aMohammadi et al 2009). However, the contribution of locations to the environmental variation is much higher than the effect of years and location × year interactions.…”

Trait association for improved grain yield of extra-early maturing maize hybrids evaluated in the forest and transitional zones of Ghana

“…The magnitude of environmental mean squares observed was higher than genotypic mean squares for all the traits under study (Table 1), indicating great influence of environment on these traits. This result is in agreement with the findings of Badu-Apraku et al (1995; and Mohammadi et al (2009) who also reported similar environmental and G x E effects. Significant G x E has been reported by Comstock and Moll, (1963) to reduce progress from selection of superior genotypes resulting from environmental effects that inhibits the expression of desired traits of genotypes evaluated across diverse environments, implying that the lack of significant G x E mean squares observed for anthesis-silking interval, grain yield, plant height, root lodging and plant stand makes these traits more reliable as part of an index for the selection of superior genotypes as compared with the other traits measured in this study.…”

Consistency of performance of early-maturing maize cultivars in Striga-infested and Striga-free environments

“…The high proportion of the contribution of the environmental main effects and the low proportion of the genotypic main effects to the total sum of squares for grain yield revealed by the AMMI analysis in the present study are consistent with the findings of BaduApraku et al (2003) and Mohammadi et al (2009). The AMMI analysis showed that G30 had grain yield above mean performance and produced similar yield in the presence and absence of Striga infestation, indicating its superior Striga resistance.…”