, 215:63 | Cite as

Integrating different stability models to investigate genotype × environment interactions and identify stable and high-yielding barley genotypes

  • Behrouz Vaezi
  • Alireza Pour-AboughadarehEmail author
  • Rahmatolah Mohammadi
  • Asghar Mehraban
  • Tahmasb Hossein-Pour
  • Ehsan Koohkan
  • Soraya Ghasemi
  • Hoda Moradkhani
  • Kadambot H. M. Siddique


Barley is the fourth largest grain crop globally with varieties suited to temperate, subarctic, and subtropical areas. The identification and subsequent selection of superior varieties are complicated by genotype-by-environment interactions. The main objective of this study was to use parametric and non-parametric stability measures along with a GGE biplot model to identify high-yielding stable barley genotypes in Iran. Eighteen barley genotypes (16 new genotypes and two control varieties) were evaluated in a randomized complete block design with four replications at five locations over three growing seasons (2013–2014, 2014–2015, 2015–2016). The combined analysis of variance indicated that the environment main effect accounted for > 69% of all variation, compared with < 31% for the combined genotype (G) and genotype-by-environment interaction effects. The mean grain yield of each genotype across the five test sites and three seasons ranged from 1900 to 2302 kg ha−1. Using Spearman’s rank correlation and principal component analyses, the stability measures were divided into three groups: the first included mean yield, TOP and b, which are related to the dynamic concept of stability, the second comprised θi, W i 2 , σ i 2 , CVi, \(S_{di}^{2}\), KR, and the non-parametric measures, S(i) and NP(i), which are related to the static concept of stability, and the third included θi and R2. The GGE biplot analysis indicated that, of the five test locations, Gonbad and Moghan had the most discriminating and representative environments. Hence, these locations are recommended as ideal test locations in Iran for the selection of superior genotypes. The numerical and graphical methods both produced similar results, identifying genotypes G12, G13, and G17 as the best material for rainfed conditions in Iran; these genotypes should be promoted for commercial production.


Barley Genotype-by-environment interaction GGE biplot Parametric and non-parametric statistics Yield stability 



This research was supported by a grant and genetic material from the Dryland Agricultural Research Institute (DARI) of Iran. We would like to thank all members of the project who contributed to the implementation of the field work.

Supplementary material

10681_2019_2386_MOESM1_ESM.docx (18 kb)
Supplementary material 1 (DOCX 17 kb)


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Behrouz Vaezi
    • 1
  • Alireza Pour-Aboughadareh
    • 2
    Email author
  • Rahmatolah Mohammadi
    • 3
  • Asghar Mehraban
    • 4
  • Tahmasb Hossein-Pour
    • 5
  • Ehsan Koohkan
    • 6
  • Soraya Ghasemi
    • 7
  • Hoda Moradkhani
    • 8
  • Kadambot H. M. Siddique
    • 9
  1. 1.Kohgiluyeh and Boyerahmad Agricultural and Natural Resources Research and Education CenterAgricultural Research, Education and Extension Organization (AREEO)YasujIran
  2. 2.Department of Agronomy and Plant BreedingTehran UniversityKarajIran
  3. 3.Golestan Agricultural and Natural Resources Research and Education CenterAgricultural Research, Education and Extension Organization (AREEO)GonbadIran
  4. 4.Ardabil Agricultural and Natural Resources Research Center, Agricultural Research, Education and Extension Organization (AREEO)ArdebilIran
  5. 5.Lorestan Agricultural and Natural Resources Research and Education CenterAgricultural Research, Education and Extension Organization (AREEO)Ilam, KohdashtIran
  6. 6.Kohgiluyeh and Boyerahmad Metrological Organization, Synoptic Metrological ManagementYasujIran
  7. 7.Safiabad Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO)DezfulIran
  8. 8.Department of Plant BreedingKermanshah Branch, Islamic Azad UniversityKermanshahIran
  9. 9.The UWA Institute of AgricultureThe University of Western AustraliaPerthAustralia

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