The study focused on assessing the stability of 55 F5:8 bread wheat genotypes across multiple locations in Khyber Pakhtunkhwa, Pakistan. Using an alpha lattice design over two years during 2014 and 2015, researchers analyzed the genotype × environment (GE) interaction and its impact on grain yield. Results from the additive main effect and multiplicative interaction (AMMI) analysis highlighted significant GE interactions influencing grain yield variability. Genotypes, environments, and their interaction contributed 9.0 %, 35.1 %, and 28.9 %, respectively, to total explainable phenotypic variation, respectively. Certain genotypes, such as G17, G45, and G40 showed average yield at well across different environments, while G58, G53 and G1 excelled in specific environments. GGE biplot analysis identified stable genotypes (e.g., G51, G36, and G53) and grouped environments into mega-environments based on yield performance. The AMMI and GGE biplot analyses explained similar proportions of the genotype × environment interaction (56.1 % and 55.5 %, respectively). Because the two methods have complementary objectives, AMMI was used to investigate GE interaction patterns, whereas GGE biplot facilitated genotype evaluation, mega-environment identification, and visualization of genotype performance, the two methods should be regarded as complementary rather than competing tools for evaluating genotype performance across environments.
Climate change and environmental variability pose major challenges to sustainable wheat production, highlighting the need for stable and high-yielding cultivars. This study evaluated fifteen bread wheat (Triticum aestivum L.) genotypes across twelve environments during two consecutive growing seasons using a randomized...
M. Genedy, Mahmoud A. Hussein, A. R. Ibrahim et al.· Sustainability· 0 citations
This study aimed to identify high-yielding and stable bread wheat genotypes through genotype × environment interaction analysis using GGE biplot methodology. A total of 160 genotypes were evaluated during the 2023 and 2024 cropping seasons at Dabat and Adet in northwestern Ethiopia using an alpha lattice design with tw...
Workineh Fenta, A. Sintayehu, Tesfaye Alemu et al.· Turkish Journal Of Field Cro...· 0 citations
Genotype × environment interaction (G×E) complicates the identification of high-yielding and stable cowpea genotypes across variable production environments. This study evaluated 20 advanced cowpea breeding lines for grain yield, stability, and multi-trait performance across five location-year environments in Ghana...
T. K. Tengey, P. Attamah, Peter Quandahor et al.· Frontiers in Plant Science· 0 citations
Genotype and environment interaction plays a crucial role in plant breeding since the performance of crop varieties often varies considerably with changes in sowing date, season and location. Therefore, identifying stable genotypes that perform consistently across diverse environments is essential for the development o...
E. Sudhishna, Y. Mohan, J. Kumar et al.· Agricultural Research Journa...· 0 citations
The assessment of genotype-by-environment interaction (GE interactions) plays a significant role in identifying high-yielding and stable maize hybrids over trials at multiple locations. In the present research, 19 maize single cross hybrids, along with one check, were assessed for two years across eight environments ba...
S. Saleem, Musab Imtiaz, Mubashir Ahmed Khan et al.· Discover Agriculture· 0 citations
Barley is a crucial crop worldwide, but it faces significant production challenges due to limited adaptable varieties, poor management practices, and environmental factors. Food barley varieties often struggle in unfamiliar environments, leading to crop loss. To address this issue, a study was conducted to evalua...
S. Alamerew, Wami Hailu, Wondimu Fekadu et al.· BMC Plant Biology· 0 citations
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