Title of article
Evaluation of grain yield stability of barley genotypes using additive main effects and multiplicative interaction model
Author/Authors
Ramzi ، Elnaz Faculty of Agriculture and Natural Resources - University of Mohaghegh Ardabili , Asghari ، Ali Faculty of Agriculture and Natural Resources - University of Mohaghegh Ardabili , Ebadi ، Asghar Faculty of Agriculture and Natural Resources - University of Mohaghegh Ardabili , Sofalian ، Omid Faculty of Agriculture and Natural Resources - University of Mohaghegh Ardabili , Mehraban ، Asghar Moghan Agricultural Research Center
From page
51
To page
66
Abstract
Objective: Barley as one of the most important cereals is crucial to supplying the required energy for both humans and animals. Grain yield is strongly influenced by environmental conditions and breeders often determine the stability of high-yielding genotypes across various locations before recommending a cultivar for release. Methods: For this research, 18 barley genotypes were tested at four different research stations including Gachsaran, Moghan, Khorramabad, and Gonbad in Iran. The additive main effects and multiplicative interaction (AMMI) model was used to identify the stable genotypes. Results: Partitioning of the GE interaction indicated that the first interaction principal component axes (IPCA) captured 35.9% of the interaction sum of squares. However, the five IPCAs accounted for 87.4% of the total interaction. Moreover, 13 AMMI-based stability statistics were calculated. Using cluster analysis, AMMI stability indices were divided into four groups. This analysis showed that most indices do not correlate with the grain yield. AMMI indices were placed in separate groups with large distances from the grain yield. However, the yield stability index (YSI) showed the highest correlation with grain yield, and based on that, G13, G18, and G11 genotypes were recognized as superior genotypes. G13 and G18 genotypes had an acceptable performance in two years and four locations, so they may be regarded as genotypes with both high yield and stability in these environments. However, by using the AMMI2 mega-environmental analysis to select suitable cultivars for each mega-environment, the target region was divided into three sub-regions, and the winner genotypes of each sub-region were identified. The first mega-environment consisted of the areas Gonbad and Ghachsaran, where genotype G14 was the winner; the second mega-environment consisted of the Khorramabad area, where genotype G2 was the winner, and the third mega-environment included only the Moghan area, where genotype G13 was the winner. Conclusion: In conclusion, the AMMI2 mega-environmental analysis identified three mega environments and the best genotypes specifically adapted to these environments. Since two test areas Gonbad and Ghachsaran were located in the first mega-environment, it seems that the performance ranking of the test genotypes in these areas will be almost the same, and in coming years, the test can be performed in only one of these areas.
Keywords
AMMI , Barley , Mega , environment. SIIG index
Journal title
Journal of Plant Physiology and Breeding
Journal title
Journal of Plant Physiology and Breeding
Record number
2774370
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