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:: Volume 25, Issue 4 (winter 2024) ::
علوم زراعی 2024, 25(4): 325-341 Back to browse issues page
Analysis of stability and evaluation of genotype-by-environment interaction for grain yield in promising genotypes of barley using the AMMI model and stability parameters
Salim Rahmati , Reza Azizinezhad , Alireza Pour-Aboughadareh , Alireza Etminan , Lia Shooshtari
Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran
Abstract:   (240 Views)
Introduction: Multi-environmental trials (METs) and analysis of genotype-by-environment (GE) interaction have a critical role in breeding programs related to the release of high-yielding cultivars with high yield satbility for cultivation across different environments. Different statistical and graphical methods have been proposed to evaluate the GE interaction effects. In the present study, the effect of GE interaction on grain yield in set of new promising lines of barley was evaluated using the additive main effect and multiplicative interaction (AMMI) model.
Materials and methods: A set of promising lines of barley including 18 new advanced lines along with two commercial cultivars (cv. Golchin and cv. Oxin) as reference checks were evaluated in the multi-environment trials. Experiments were carried out in five geographical regions in the warm agro-climatic of Iran which included Ahvaz (E1 and E2), Darab (E3 and E4), Gonbad (E5 and E6), Zabol (E7 and E8), and Moghan (E9 and E10) for two consecutive cropping seasons (2021-2022 and 2022-2023). The AMMI model and some stability and adaptability statistics were used to evaluate the effect of GE interaction on grain yield and identify the high yielding with yield stability promising lines.
Results: The results indicated that grain yield was significantly affected by environments (E), genotypes (G), and their interaction (GEI). Environments and GE interaction effect explained the highest portion of observed variation of grain yield. Moreover, the GEI effect was further divided into three principal components (IPCAs) and accounted for 68.99 of the total GE interaction variation. Mean comparison showed that promising lines 14, 3, 10, and 17 had higher grain yield (4960, 4920, 4750, and 4670 kg.ha-1, respectively) when compared to the other promising lines and check cultivars. According to the AMMI-based stability statistics, promising lines 17 had the highest yield stability. Moreover, this genotype along with promising lines 1, 3, 10, and 14 were selected as superior promising lines based on the BLUP-based stability and adaptability statistics. Principle components analyisis based on biplot rendered using the WAASB index and grain yield clustered all studied promising lines and experimental environments into four quadrants. Accordingly, promising lines 3, 10, and 17 were placed into the highest yield stability group.
Conclusion: The results of this research revealed that promising lines 4 and 14 had specific adaptability to the northern regions (Moghan and Gonbad), and promising lines 3 and 10 showed specific adaptability to the southern regions (Ahvaz, Darab, and Zabol). Therefore, further evaluation of these promising lines, for selection and releasing some of them as new commercial cultivars as well as using them as parents in the national barley breeding programs, is required.
 
Keywords: Barley, Multi-environmental trails, Principal component analysis and Specific adaptability
Full-Text [PDF 789 kb]   (140 Downloads)    
Type of Study: Scientific & Research | Subject: Special
Received: 2024/01/13 | Accepted: 2024/02/4 | Published: 2024/03/15
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Rahmati S, Azizinezhad R, Pour-Aboughadareh A, Etminan A, Shooshtari L. Analysis of stability and evaluation of genotype-by-environment interaction for grain yield in promising genotypes of barley using the AMMI model and stability parameters. علوم زراعی 2024; 25 (4) :325-341
URL: http://agrobreedjournal.ir/article-1-1341-en.html


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Volume 25, Issue 4 (winter 2024) Back to browse issues page
نشریه علوم زراعی ایران Iranian Journal of Crop Sciences
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