article · BMC Agriculture
Garlic is one of the most important vegetable crops in the world as well as in Ethiopia. However, GxE interaction manifested as an inconsistent performance of genotypes across varying environments, has been the main bottleneck for crop improvement since it reduces genetic gain. Hence, the current experiment was designed to estimate the magnitude of GxE interaction for bulb yield and yield-related traits and to identify widely or specifically adapted garlic genotypes. Thirteen garlic genotypes along with a standard check variety, Chefe, were evaluated at six different environments in central Ethiopia using a Randomized Complete Block Design with three replications. Phenology, growth, yield and yield component data were collected for each genotype. To assess the GxE interaction and evaluate the stability of the genotypes, AMMI, GGE, ASV, GSI and Eberhart and Russell stability matrices were done following analysis of variance. Combined ANOVA revealed highly significant differences between environments and between genotypes for marketable bulb yield and other agronomic traits. The GxE interaction was also significant for marketable bulb yield and six of the twelve traits. For marketable bulb yield, the Environment, Genotype and GxE interaction accounted for 85.68%, 5.03% and 9.30% of the total treatment sum of squares, respectively. The marketable bulb yield of the genotypes ranged from 5.31 t/ha (G-063/06) to 6.68 t/ha (G-091/06). AMMI and GGE indicated that E5 and E6 (Debre Birhan, 2021 and Kulumsa, 2021) were the most favorable and discriminating environments. The univariate stability matrices (Eberhart and Russell’s βi and Sdi2, ASV and GSI) identified that variety Chefe, G-129/06 and G-009/06 were widely adapted genotypes with high marketable bulb yield of 6.29 t/ha, 6.08 t/ha and 6.26 t/ha respectively. The study highlights the inconsistent performance of garlic genotypes across environments, emphasizing the necessity of evaluating genotypes in multiple locations to develop high yielding and stable varieties. Additionally, the use of AMMI and GGE biplots has proven to be effective for visualizing multi-environment trials and assessing GxE interactions.
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DOI: 10.1186/s44399-025-00015-9
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