[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
Journal Information::
Articles archive::
For Authors::
For Reviewers::
Registration::
Contact us::
Site Facilities::
::
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
:: Volume 22, Issue 3 (autumn 2020) ::
علوم زراعی 2020, 22(3): 212-224 Back to browse issues page
Evaluation of grain yield stability of irrigated barley (Hordeum vulgare L.) promising lines in warm regions of Iran using GGE biplot analysis
Ali Barati , Iraj Lakzadeh , Mehdi Jabbari , Omid Poodineh , Jabbar Alt Jafarbby , Kamal Shahbazihomonlo , Ahmad Gholipour , Nosratollah Tabatabaei Fard
Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
Abstract:   (1678 Views)
The main purpose of this research was to identify barley promising lines with high grain yield and yield stability for warm region of Iran. In this experiment, 17 barley promising lines and two check cultivars were evaluated in five agricultural research stations; Ahvaz, Darab, Zabol, Gonbad and Moghan, Iran, in 2015-16 and 2016-17 cropping seasons, using randomized complete block design with three replications. Combined analysis of variance showed significant effect of year, year × location and year × location × genotype on grain yield. To identify genotypes with high grain yield and yield satbilty, Lin and Bin's superiority statistic and GGE biplot analysis method were employed. The lowest values of Lin and Bin's superiority statistic were for lines No. 2, 3 and 9. GGE biplot analysis revealed that the first and second principle components explained 40% and 24% of total variation, respectively. In this experiment, two mega- environments were identified. The first mega-environment included Ahavaz and Darab, and the second mega-environment included Zabol, Gonbad and Moghan. Considering grain yield and yield stability stability estimates, line NO. 2 has been identified with wide adpatation and released for warm regions (north and south) and line NO. 3 with specific adaptaion for the north warm region of Iran.
 
Keywords: Adoptability, Barley, Principal components, Warm regions and Yield stability.
Full-Text [PDF 868 kb]   (718 Downloads)    
Type of Study: Scientific & Research | Subject: Special
Received: 2019/03/16 | Accepted: 2020/10/24 | Published: 2020/11/30
References
1. Ahakpaz, F. and F. Ahakpaz. 2014. Stability analysis of barley lines and cultivars grain yield using GGE biplot model. Agroecol. J. 9(4): 1-12.##Ahmadi, K., H. R. Ebadzadeh, H. Abdeshah, A. Kazemian and M. Rafeie. 2018. Agricultural Statistics of 2016-2017 Cropping Season. Ministry of Agriculture-Jahad. Vol. 1. (In Persian).##Ahmadi, J., B. Vaezi and M. H. Fotokian. 2012. Graphical analysis of multi-environment trials for barley yield using AMMI and GGE-biplot under rain-fed conditions. J. Plant Physiol. Breed. 2: 43-54. ##Dehghani, H., A. Ebadi and A. Yousefi. 2006. Biplot analysis of genotype by environment interaction for barley yield in Iran. Agron. J. 98(2): 388-393.##Falconer, D. S. 1981. Introduction to Quantitative Genetics (2nd Ed.). Longman Press. London, UK.##FAO. 2016. http://www.fao.org/faostat##Ghazvini, H., SH. A. Kohkan, I. Lakzadeh, H. A. Fallahi, J. Alt Jafarby, M. Ghasemi, A. A. Amini, S. M. Tabib Ghaffari and B. Sorkhi Lalelu. 2014. Zahak, a New Irrigated Barley Cultivar with Wide Adaptability in the Warm and Dry Agro-Climate Zone in the South of Iran. Research Achievements for Field and Horticulture Crops. 3(1): 15-26. (In Persian). ##Jalata, Z. 2011. GGE-biplot analysis of multi-environment yield trials of barley (Hordeum vulgare L.) genotypes in southeastern Ethiopia highlands. Int. J. Plant Breed. Genet. 5(1): 59-75.##Kaya, Y., M. Akcura and S. Taner. 2006. GGE-Biplot analysis of multi-environment yield trials in bread wheat. Turk. J. Agric. Forest. 30: 325-337.##Khanzadeh, H., B. Vaezi, R. Mohammadi, A. Mehraban, T. Hosseinpour and K. Shahbazi. 2018. Grain yield stability of barley genotypes in uniform regional yield trials in warm and semi warm dryland area. Indian J. Agric. Res. 52(1): 16-21. ##Kendal, E., M. Karamian, S. Tekdal and S. Dogan. 2019. Analysis of promising barley (Hordeum vulgare L.) lines performance by AMMI and GGE BIPLOT in multiple traits and environment. Appl. Ecol. Environ. Res. 17(2): 5219-5233. ##Lin, C. S. and M. R. Binns. 1988. A superiority measure of cultivar performance for cultivar × location data. Can. J. Plant Sci. 68(1): 193-198.##Mohamed, N. E. and A. A. Ahmed. 2013. Additive main effects and multiplicative interaction (AMMI) and GGE-biplot analysis of genotype × environment interaction for grain yield in bread wheat (Triticum aestivum). Afr. J. Agric. Res. 8: 5197-5203.##Mortazavian, S. M., H. R. Nikkhah, F. A. Hassani, M. Sharif-al-Hosseini, M. Taheri and M. Mahlooji. 2014. GGE-biplot and AMMI analysis of barley genotypes across different environment in Iran. J. Agric. Sci. Technol. 16(3): 609-622.##Perkinz, J. M. and J. L. Jinks. 1971. Environments and genotype environment components of variability III. Multiple lines and crosses. Heredity, 23(3): 339-356. ##Shiri, M. R. and T. Bahrampour. 2015. Genotype × Environment interaction analysis using GGE biplot in grain maize (Zea mays L.) hybrids under different irrigation conditions. Cereal Res. 5(1): 83-4. (In Persian with English abstract).##Taheripourfard, Z. S., A. Izadi-Darbandi, H. Ghazvini, M. Ebrahimi, S. M. M. Mortazavian and M. Abdipour. 2017. Identifying superior barley (Hordeum vulgare L.) genotypes using GGE-biplot across warm and moderate environments under irrigated conditions in Iran. Crop Breed. J. 7(2): 23-35.##Yan, W. 2002. Singular-value partitioning in Biplot analysis of multi-environment trial data. Agron. J. 94(5): 990-996.##Yan, W. and I. Rajcan. 2002. Biplot analysis of test sites and trait relations of soybean in Ontario. Crop Sci. 42: 11-20.##Yan, W., L. A. Hunt, Q. Sheng and Z. Szlavnics. 2000. Cultivar evaluation and mega-environment investigations based on the GGE biplot. Crop Sci. 40(3): 597-605. ##Yan, W. and M. S. Kang. 2003. GGE biplot analysis: a graphical tool for breeders, geneticists and agronomists. CRC Press Inc. Boca Raton, USA. ##Yan, W., M. S. Kang, B. Ma, S. Woods and P. L. Cornelius. 2007. GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Sci. 47(2): 643-655.##Yan, W. and N. A. Tinker. 2006. Biplot analysis of multi-environment trial data: principles and applications. Can. J. Plant Sci. 86(3): 623-645.##
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA


XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Barati A, Lakzadeh I, Jabbari M, Poodineh O, Alt Jafarbby J, Shahbazihomonlo K, et al . Evaluation of grain yield stability of irrigated barley (Hordeum vulgare L.) promising lines in warm regions of Iran using GGE biplot analysis. علوم زراعی 2020; 22 (3) :212-224
URL: http://agrobreedjournal.ir/article-1-979-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 22, Issue 3 (autumn 2020) Back to browse issues page
نشریه علوم زراعی ایران Iranian Journal of Crop Sciences
Persian site map - English site map - Created in 0.05 seconds with 37 queries by YEKTAWEB 4645