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  4. Identification of High Yielding and Stable Barley Genotypes for Drought Conditions in the Moderate Climate of Iran Using AMMI Model and GGE Biplot Analysis
 
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Identification of High Yielding and Stable Barley Genotypes for Drought Conditions in the Moderate Climate of Iran Using AMMI Model and GGE Biplot Analysis

Type
Journal article
Language
English
Date issued
2025
Author
Barati, Ali
Pour-Aboughadareh, Alireza
Arazmjoo, Elias
Tabatabaei, Seyed Ali
Bocianowski, Jan 
Jamshidi, Bita
Faculty
Wydział Rolnictwa, Ogrodnictwa i Biotechnologii
Journal
Journal of Crop Health
ISSN
2948-264X
DOI
10.1007/s10343-024-01080-x
Volume
77
Number
1
Pages from-to
art. 8
Abstract (EN)
Drought stress is one of the major environmental factors that significantly reduces agricultural production worldwide. Among cereal crops, barley (Hordeum vulgare L.) plays a key role in both food and feed security. The main objective of this study was to identify high-yielding, drought-tolerant and stable genotypes using the additive main effect and multiplicative interaction (AMMI) and genotype main effect (G) plus genotype by environment interaction (GE) (GGE) biplot models. For this purpose, a set of promising new barley genotypes was studied in three drought-prone regions of Iran (Varamin, Yazd and Birjand) during two consecutive growing seasons (2020–2021 and 2021–2022). The results of the combined analysis of variance (ANOVA) and AMMI model showed significant effects for genotypes (G), environments (E), and their interaction (G × E). Based on the grain yield data under irrigated and drought stress conditions and the stress tolerance index (STI), genotypes G3, G11, and G15 were identified as the most tolerant genotypes across test environments. Of the genotypes tested, G11 was identified as the most stable genotype using AMMI-based stability parameters. Moreover, sum across environments of absolute value of GEI modelled by AMMI (AVAMGE) and stability measure based on fitted AMMI model (FA) parameters showed a “dynamic” concept of stability. The result of the GGE biplot analysis showed that the first two principal components (PCA1 and PCA2) accounted for 49.73% of the total grain yield variation. Based on the polygon viewpoint of the GGE model, all test environments clustered in four main sectors. Among the test environments, the Varamin location (E5 and E7) was identified as the ideal environment (Type II) for identifying the highest quality genotypes. In a pooled analysis using various statistical methods, genotypes G3 and G11 were proposed as superior genotypes. Consequently, these genotypes may be candidates for commercial introduction in drought-prone regions in Iran’s temperate climate.
Keywords (EN)
  • Hordeum vulgare L.

  • grain yield

  • genotype -by-environment interac...

  • STI index

  • water scarcity condition

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