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Tahmasebi, S., Esmaeilzadeh Moghaddam, M., Tabib Ghaffari, M., Sayyahfar, M., Miri, Kh., Lotfi Ayeneh, Gh., Akbari Moghadam, H., Osroosh, S.. (1378). Summarizing the genotype × environment interaction and mega-environments delineation using LG biplot analysis of unrepeatable multi-environment bread wheat yield trials data of southern warm and dry agro-climatic zone in Iran. سامانه مدیریت نشریات علمی, 11(2), 45-57. doi: 10.22092/cbj.2023.361025.1077
S. Tahmasebi; M. Esmaeilzadeh Moghaddam; M. Tabib Ghaffari; M. Sayyahfar; Kh. Miri; Gh. Lotfi Ayeneh; H. Akbari Moghadam; S. Osroosh. "Summarizing the genotype × environment interaction and mega-environments delineation using LG biplot analysis of unrepeatable multi-environment bread wheat yield trials data of southern warm and dry agro-climatic zone in Iran". سامانه مدیریت نشریات علمی, 11, 2, 1378, 45-57. doi: 10.22092/cbj.2023.361025.1077
Tahmasebi, S., Esmaeilzadeh Moghaddam, M., Tabib Ghaffari, M., Sayyahfar, M., Miri, Kh., Lotfi Ayeneh, Gh., Akbari Moghadam, H., Osroosh, S.. (1378). 'Summarizing the genotype × environment interaction and mega-environments delineation using LG biplot analysis of unrepeatable multi-environment bread wheat yield trials data of southern warm and dry agro-climatic zone in Iran', سامانه مدیریت نشریات علمی, 11(2), pp. 45-57. doi: 10.22092/cbj.2023.361025.1077
Tahmasebi, S., Esmaeilzadeh Moghaddam, M., Tabib Ghaffari, M., Sayyahfar, M., Miri, Kh., Lotfi Ayeneh, Gh., Akbari Moghadam, H., Osroosh, S.. Summarizing the genotype × environment interaction and mega-environments delineation using LG biplot analysis of unrepeatable multi-environment bread wheat yield trials data of southern warm and dry agro-climatic zone in Iran. سامانه مدیریت نشریات علمی, 1378; 11(2): 45-57. doi: 10.22092/cbj.2023.361025.1077

Summarizing the genotype × environment interaction and mega-environments delineation using LG biplot analysis of unrepeatable multi-environment bread wheat yield trials data of southern warm and dry agro-climatic zone in Iran

Crop Breeding Journal
دوره 11، شماره 2، آبان 2021، صفحه 45-57  XML اصل مقاله (910.31 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22092/cbj.2023.361025.1077
نویسندگان
S. Tahmasebi email orcid 1؛ M. Esmaeilzadeh Moghaddamorcid 2؛ M. Tabib Ghaffari3؛ M. Sayyahfar4؛ Kh. Miri5؛ Gh. Lotfi Ayeneh6؛ H. Akbari Moghadam7؛ S. Osroosh8
1Seed and Plant Improvement Department, Fars Agriculture and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Shiraz, Iran. Department of Seed and Plant Improvement, Fars Agricultural and natural Resources Research and Education Center, AREEO, Darab, Iran
2Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization, Karaj, IranSeed and Plant Improvement Institute, Karaj, Iran.
3SeeSeed and Plant Improvement Department, Safiabad Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Dezful, Iran. d and plant Improvement department, Safiabad Agricultural and Natural Resource Research Center, AREEO, Dezful, Iran
4Seed and Plant Improvement Department, Lorestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Khorramabad, Iran. Seed and plant Improvement department, Lorestan Agricultural and Natural Resource Research Center, AREEO, Khoramabad, Iran
5Seed and Plant Improvement Department, Baloochestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Iranshahr, IranSeed and plant Improvement department, Baluoohestan Agricultural and Natural Resource Research Center, AREEO, Iranshahr, Iran
6Seed and Plant Improvement Department, Khuzestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Ahvaz, Iran. Seed and plant Improvement department, Khuzestan Agricultural and Natural Resource Research Center, AREEO, Ahvaz, Iran
7Seed and Plant Improvement Department, Sistan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Zabol, Iran. Seed and plant Improvement department, Sistan Agricultural and Natural Resource Research Center, AREEO, Zabol, Iran
8Seed and Plant Certification and Registration Institue, Agricultural Research, Education and Extension Organization, Karaj, Iran.
چکیده
In this study LG (location-grouping) biplot analysis, as a new method, was used to identify repeatable and unrepeatable GEI patterns and to delineate mega-environments using grain yield data of five multi-environment bread wheat trials from six southern warm and dry agro-climatic zone of Iran including Khorramabad (KHR), Darab (DAR), Dezful (DEZ), Iranshahr (ISH), Ahvaz (AHV) and Zabol (ZAB). The trials included 18, 32, 28, 28 and 28 elite bread wheat genotypes. Each of genotype sets was evaluated in two successive cropping seasons of 2012-14, 2013-15, 2014-16, 2015-17 and 2016-18, respectively. The highest (7.99 ton ha-1) and lowest (4.33 ton ha-1) grand mean of testing locations across ten trials were observed in KHR and AHV, respectively. Results of the yearly GGE biplots based on the grain yield data from the 2012-13 to 2016-18 cropping seasons of 10 bread wheat yield trials across six locations varied from cropping cycle to cropping cycle, thus it was difficult to extract the common patterns across cropping seasons and grouping the test locations using two-year grain yield data. When these datasets were incorporated in a LG biplot analysis, six locations were divided into four MEs. The LG biplot explained 49.86% of the total variation of the two-way correlation table. KHR ZAB locations formed ME1 and ME2, respectively. AHV and Iranshahr ISH formed ME3, while DAR and DEZ grouped in ME4. Unlike ME1 and ME2, which had negative correlation with each other and with other MEs, ME3 and ME4 were weakly correlated, therefore, a genotype with the highest grain yield in ME3 may perform well in ME2, and vice versa. Result of this study can help bread wheat breeders to understand the bread wheat growing MEs in the southern warm and dry agro-climatic zone of Iran, and lead to better decision-making for the analysis of multi-environments yield trial data and to identify and release high-yielding bread wheat cultivars adapted to each ME.
کلیدواژه‌ها
bread wheat؛ Cropping season؛ LG biplot؛ high yielding cultivar؛ total variation
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