AMMI and GGE biplot analysis of grain yield of bread wheat (Triticum aestivum L.) genotypes at moisture deficit environment of Wollo, Ethiopia

Mekonnen, Agegnehu; Mekbib, Firew; Gashaw, Arega

doi:10.31248/jasp2019.123

Cited by 6 publications

(2 citation statements)

References 29 publications

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“…Hence, the Ethiopian durum wheat germplasm can be considered an invaluable reservoir of economically useful genes for developing new durum wheat cultivars through breeding. Research on phenotypic stability and GEI targeting Ethiopian wheat germplasm has primarily focused on hexaploid wheat genotypes and cultivars [58][59][60][61]. Given the highly limited use of Ethiopian durum wheat germplasm in previous studies on genotype stability and GEI [62][63][64], information regarding the effects of GEI on its landraces and cultivars is scarce and insufficient.…”

Section: Introductionmentioning

confidence: 99%

Multivariate analyses of Ethiopian durum wheat revealed stable and high yielding genotypes

et al. 2022

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Improving crop adaptation and stability across diverse and changing environmental conditions is essential to increasing grain yield per unit area. In turn, this contributes to meeting the increasing global food demand. Nevertheless, a number of factors challenge the efficiency of crop improvement programs, of which genotype-by-environment interaction (GEI) is one of the major factors. This study aimed to evaluate the performance and phenotypic stability of 385 Ethiopian durum wheat landraces and 35 cultivars; assess the pattern of genotype by environment interaction (GEI) effect, and identify stable and high-yielding landraces or cultivars using the additive main effect and multiplicative interaction (AMMI) and genotype main effect plus genotype by environment interaction biplot (GGE-biplot). The experiment was laid out in an alpha lattice design with two replications at five test sites (Akaki, Chefe Donsa, Holeta, Kulumsa, and Sinana). The combined analysis of variance revealed highly significant effects (P ≤ 0.01) of environments (E), genotype (G), and GEI on a phenotypic variation of traits evaluated, including grain yield. For all traits, the amount of phenotypic variance and GEI explained by the GGE biplot was higher than in AMMI2, but both exhibited significant effects of E and GEI on the genotypes. The AMMI model identified G169, G420, G413, G139, G415, G416, G417, and G418 as stable genotypes across testing sites. Whereas, the GGE biplot identified G169, G420, G415, G139, G106, G412, G413, and G417 as both high-yielding and stable across test sites. Hence, genotypes identified as stable and high yielding in the present study could be used in a durum wheat breeding program aimed at identifying genes and molecular markers associated with the crop’s productivity traits as well as developing stable and high-yielding cultivars for use in East Africa and beyond.

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Section: Introductionmentioning

confidence: 99%

Multivariate analyses of Ethiopian durum wheat revealed stable and high yielding genotypes

et al. 2022

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“…Different genotypes appeared at the top corners of the polygon. These genotypes were either the best or the worst in a certain environment or all environments because they were far away from the center of the biplot (Mekonnen et al., 2019). In the GGE biplot analysis, PC1 and PC2 accounted for 45.77% of the total variation in terms of GP, and PC1 and PC2 explained 32.33 and 13.44% of the total variation, respectively.…”

Section: Resultsmentioning

confidence: 99%

A study on genotype × environment interactions for the multiple traits of maize hybrids in China

et al. 2021

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The correct interpretation of the adaptability and stability of maize (Zea mays L.) hybrids in different ecological environments is very important for plant breeders. Additive main effect and multiplicative interaction model and genotype main effects and genotype × environment interaction biplot are the two most popular methods in the analysis of genotype × environment interaction in multienvironment trials. We conducted an experiment designed to examine and evaluate the adaptability and stability of four agronomic traits of 19 tested maize genotypes in two consecutive growth cycles across seven provinces including 37 locations using a randomized completely block design with three replicates. The combined ANOVA for all traits showed that the effect of genotype, environment, and genotype × environment interaction were significant at 0.1% probability levels. In order to evaluate multiple agronomic traits more accurately, multitrait stability index (MTSI) as an emerging selection method based on mean performance and stability was adopted. Agronomic trait grain yield (GY) was positively correlated with grain weight per ear and growth period. In addition, it was also found that GY and bar tip length showed obvious negative correlation. The MTSI is very helpful for breeders who hope to select mean performance and stability based on a variety of agronomic traits because it provides a convenient selection process while taking into account the relevant results of the traits.

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AMMI and GGE biplot analysis for barley genotype yield performance and stability under multi environment condition in southern Ethiopia

Derbew,

Mekbib,

Lakew

et al. 2024

Agrosystems Geosci & Env

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Barley (Hordeum vulgare L.) is a major grain crop farmed in Ethiopia throughout the long rainy season (Meher) and the short rainy season (Belg) of the year. Barley genotypes were subjected to multi‐environment experiments in six different settings to identify stable genotypes and estimate the impact of genotype × environment interaction (GEI) on grain production. In each area, the field experiment was conducted from mid‐July to January during the primary cropping season of 2021. Three replications of a randomized complete block design were used to set up the trials. According to the additive main effects and multiplicative interaction (AMMI) study, genotype (18.19%), GEI (22.98%), and environment (58.83%) all had an impact on the major treatment sum of squares. The more variance attributed to the environments is a sign of environmental diversity. Given that the two interaction principal component analysis (IPCAs) accounted for 76.94% of the interaction sum of squares, they were sufficient for cross‐validation of the grain yield variance explained by GEI. In contrast to the GGE biplot approaches, which indicated genotypes G12, G3, and G9 as stable and high‐yielding genotypes throughout the environments, the AMMI stability value identified genotypes G3, G12, and G9 as high yielding with stable performance across environments. In general, the GGE biplot and AMMI analysis models demonstrated that genotypes G12, G3, and G9 were stable and yielded well, making G3 acceptable for cultivation in a wider range of environments and G12 and G9 suitable for release.

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AMMI and GGE biplot analysis of grain yield of bread wheat (Triticum aestivum L.) genotypes at moisture deficit environment of Wollo, Ethiopia

Cited by 6 publications

References 29 publications

Multivariate analyses of Ethiopian durum wheat revealed stable and high yielding genotypes

Multivariate analyses of Ethiopian durum wheat revealed stable and high yielding genotypes

A study on genotype × environment interactions for the multiple traits of maize hybrids in China

AMMI and GGE biplot analysis for barley genotype yield performance and stability under multi environment condition in southern Ethiopia

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