Identification of high-yielding genotypes for cold climate in Iran using the GGE Biplot method
Type
Journal article
Language
English
Date issued
2025
Author
Habibollah, Ghazvini
Alireza, Pour-Aboughadareh
Seyed Shahriyar, Jasemi
Soleiman, Mohammadi
Sayed Alireza, Razavi
Mehrdad, Chaichi
Marefat Ghasemi, Kalkhoran
Hassan, Monirifar
Hamid, Tajali
Afshin, Rozbehani
Bita, Jamshidi
Faculty
WydziaĆ Rolnictwa, Ogrodnictwa i Biotechnologii
PBN discipline
agriculture and horticulture
Journal
Crop Breeding and Applied Biotechnology
ISSN
1984-7033
Volume
25
Number
4
Pages from-to
e53512548
Abstract (EN)
The development of high-yielding and stable cultivars necessitates a comprehensive understanding of genotype-by-environment interaction (GEI) effects through multi-trial experiments (MTEs). In this study, the grain yield per-formance, stability, and adaptability of newly developed barley genotypes were assessed across eight locations in Iran over two cropping seasons (2020â2022) using GGE biplot analysis. Analysis of variance of the grain yield data revealed significant effects of genotype, environment, and their interaction. The GGE biplot analysis identified two mega-environments, with Ardabil, Arak, and Ta-briz being the most discriminating and representative test sites. Based on the âwhich-won-whereâ and âmean vs. stabilityâ views, genotypes G5, G17, and G18 were identified as high-yielding, stable, and ideal candidates. Genotype G17 exhibited specific adaptability to Hamedan, Miandoad, and Karaj, whereas G5 and G18 were best adapted to Jolgeh Rokh, Mashhad, Tabriz, Ardabil, and Arak. These genotypes warrant further on-farm evaluation prior to their po-tential commercial release.
License
CC-BY - Attribution
Open access date
November 10, 2025