Loading...

Farming & Management

Stability and adaptability of food barley genotypes in multiple environments using AMMI and GGE biplot analysis 


DOI: 10.31830/2456-8724.2026.FM-182    | Article Id: FM-182 | Page : 18-32
Citation :- Stability and adaptability of food barley genotypes in multiple environments using AMMI and GGE biplot analysis. Farm. Manage. 11: 18-32
SHEGAW DERBEW, SOLOMON SHIBESHI, TARIKU SEMION, SHIMELES MOHAMMED, MULUNEH MEKISO, SHIFERAW MEKONEN AND MELESE LEMA dshegaw@yahoo.com
Address : Sidama Agricultural Research Institute, Hawassa Agricultural Research Center, Hawassa, P. O. Box 2126, Ethiopia
Submitted Date : 5-02-2026
Accepted Date : 11-04-2026
Online Published:

Abstract

Barley in Ethiopia is among the major cereal crops grown and used for making various types of foods, and home-made and industrial beverages. The field experiment was conducted in randomized complete block design with four replications at seven environments from mid-July to January of 2022 to 2024 in the main cropping season. The objectives of this study were to investigate the effect of genotype by environment interaction on the grain yield performance of barley genotypes and to identify high yielding and stable genotypes across environments.  The analysis of variance demonstrated that the trait considered differed significantly (P<0.001) among genotypes, indicating that the traits under investigation displayed genetic variability. In the AMMI analysis of variance, it was discovered that the environment (E), genotype (G), and G×E interaction accounted for 44.37%, 29.52%, and 27.11% of the treatment sum of squares, respectively. The two IPCAs were sufficient for cross-validation of the grain yield variation explained by GEI because they accounted for a combined 62.39% of the interaction sum of squares. There were two mega environments found in the current investigation. Identifying mega environments with optimal genotypes can significantly enhance production in each area and also increase farmers’ income. Bule is more discriminating of the genotypes and representative of the test environments. The AMMI stability value, Yield Stability Index (YSI), AMMI and GGE biplot techniques selected genotypes G2, G3, G13 and G5 as stable and high yielding in all situations. These genotypes would be proposed for official release. Moreover, G4, which was high yielding, widely adaptable in five environments among the seven environments and moderately stable and selected by two parameters YSI and GGE biplot, would also be proposed for release and grow in its suitable agro-ecology.

Keywords

AMMI analysis barley GGE biplot multi-environment stability yield stability index 

References

Abdulla, A. A. and Mustafa, K. M. (2024). Performance and stability for grain yield and yield components of six-row barley cultivars under various environments in Kurdistan Region-Iraq.  Iraqi Journal of Agricultural Sciences 55:  1698-710.
Abera, D., Raga, W., Negash, G., Guta, A. and Alemu, B. (2019). Evaluation of improved food barley (Hordeum Vulgare L.) varieties in the mid-land areas of West and Kelem Wollega Zones of Western Oromia. International Journal of Research Studies in Agricultural Sciences 5: 1-8.
Amini, A., Sadi, A. A., Arazmjoo, E., Chaychi, M., Eyvozi, A., Nikkhah, H., Ahmadi, M. E., Ahmadi, M., Ghadiri, A., HosseiniBay, S. K., Salehi, P., Salehi, N. M. and Fattah, S. M. M. (2025).  Evaluation of grain yield stability of promising wheat (Triticum aestivum L.). 2025.  Genotypes in the Cold Climate of Iran Using Multivariate Methods. Journal of Crop Health, 7: doi:10.1007/s10343-025-01173-1.
Angela,P., Mateo, V., Gregorio, A., Francisco,R., Marco,L., Jose, C. and Juan, B. (2016). GEA-R (Genotype x Environment Analysis with R for Windows) Version 4,1. CIMMYT Research Data and software Repository Network.
Ayenew, A. W., Bekis, D. and Sharie, S. (2025). Adaptability and yield stability analysis of food barley (Hordeum vulgare L.) in South Gondar Zone, Northwest Ethiopia.        doi:10.21203/rs.3.rs-6605179/v1.
Balcha, A. (2020). Additive main effects and multiplicative interaction and other stability analyses of tef [Eragrostis tef (Zucc.) Trotter] grain yield. American Journal of Plant Sciences, 11: 793-802. doi:10.4236/ajps.2020.116056.
Balcha, A. (2023). Stability of finger millet (Eleusine coracana L.) yield using additive main effects and multiplicative interaction analysis. Int. J. Agril. Res. Innov. Tech 13: 60-66.  doi:10.3329/ijarit.vl3i1.86008.
Bekela, G., Terbush, A. and Assegid, D. (2025).  Genotype by environment and grain yield stability of food barley (Hordeum vulgare L.) genotypes West Hararhge Zone, Eastern Ethiopia. American Journal of Bioscience and Bioengineering 13: 77-91.
Bose, L. K., Jambhulkar, N. N. and Pande, K. (2014). Genotype by environment interaction and stability analysis for rice genotypes under boro condition. Genetika 46: 521-28.
Chala, G., Terbush, A. and Assegid, D. (2021). Performance evaluation and selection of improved food barley (Hordeum vulgare L.) varieties for their adaptability in West Hararghe Zone, Eastern Oromia, Ethiopia. Asian Journal of Plant Science and Research 11: 49-56.
CSA (2021). Central Statistical Agency. Agricultural sample survey (private peasant holdings, meher season). Reports on Farm management practices. Statistical Bulletin 590. CSA, Addis Ababa, Ethiopia.
Derbew, S. (2023). Yield and agronomic performance of food barley varieties in southern Ethiopia highlands. Trends Agric. Sci. 2: 281-87.  doi:10.17311/tas. 2023.281.287.
Derbew, S.  (2025). Performance evaluation and adaptability of food barley varieties in Gedeo Zone of South Ethiopia.  Asian Journal of Research and Review in Agriculture 7: 346–52. doi:10.56557/ajrra/2025/v7i1183.
Derbew, S., Mekbib, F., Bekele, A., Berhane L. and Bishaw, Z. (2024b). Genotype by environment interaction and stability analysis of barley grain yield in South Ethiopia. Ethiop. J. Agric. Sci. 34: 58-80.
Derbew, S., Mekbib, F., Lakew, B., Bekele, A., Bekele, A. and Bishaw, Z. (2024a). AMMI and GGE biplot analysis for barley genotype yield performance and stability under multi environment condition in southern Ethiopia. Agrosystems, Geosciences & Environmentm 7: doi:10.1002/agg2.20565.
Dimova, D., Krasteva, L., Panayotov, N., Svetleva D., Dimitrova, M. and Georgieva, T. (2012). Evaluation of the yield and the yield stability of perspective lines of barley. Agroznanje 13: 55-60.
Dogan, Y. Kendal, E. and Oral, E. (2016). Identifying of relationship between traits and grain yield in spring barley by GGE biplot analysis. Agriculture and Forestry 62: 239–52.
Elakhdar, A., El-Naggar, A. A., El-Wakeell, S. and Ahmed, A. A. (2024). Assessment of yield stability in barley using univariate and multivariate statistical models. This work is licensed under a Creative Commons Attribution 4.0 International.  doi:10.21203/rs.3.rs-4239501/v1.
Fana, G., Tadese, D., Sebsibe, H. and Verma, R. P. S. (2018). Multi-environment trial analysis of food barley in ethiopia using AMMI and GGE biplot methods. Journal of Plant Breeding and Genetics, 06: 75-85. doi:10.33687/pbg.006.03.2579.
Farshadfar, E., Mahmodi, E. and Yaghotipoor, A. (2011). AMMI stability value and simultaneous estimation of yield and yield stability in bread wheat (Triticum aestivum L.). Australian Journal of Crop Science 5: 1837-44.
Farshadfar, E., Rashidi, M., Mahadijowkar, M. and Zali, H. (2013). GGE biplot analysis of genotype × environment interaction in chickpea genotypes. Euro. J. Exp. Bio. 3: 417-23.
Fekadu. W., Mekbib, F. and Lakew (2023). Genotype × environment interaction and yield stability in barley (Hordeum vulgare L.) genotypes in the central highland of Ethiopia. J. Crop Sci. Biotechnol. 26: 119–33.  doi:10.1007/s12892-022-00166-0.
Gadisa A. Wardofa, Dawit, Asnake. and Hussein, Mohammed. (2019). GGE biplot analysis of genotype by environment interaction and grain yield stability of bread wheat genotypes in central Ethiopia. Journal of Plant Breeding and Genetics 07: 75-85.
Gauch, H. G. and Zobel, R.W. (1997). Identifying mega-environment and target genotypes. Crop Science 37: 311-26. doi:10.2135/cropsci1997.0011183X003700020002x.
Gauch, H. G., Piepho H. and Annicchiarico P. (2008). Statistical analysis of yield trials by AMMI and GGE: further considerations. Crop Sci. 48: 866-89.
Gauch, H. G. (1992). Statistical analysis of regional yield trials: AMMI analysis of factorial designs. Elsevier, Amsterdam.
GenStat (2014). Release 16th Edition (PC/Windows 7) Copy right. VSN international Ltd. Germplasm. In: Fatukuma CA, Tarawali SA, Singh BB, Kormawa PM, Tamo M(eds.)
Ghazvini, H.,   Pour-Aboughadareh, A.,   Jasemi, S. S.   Mohammadi, S., Razavi, S. A., Chaichi, M., Kalkhoran, G., Monirifar, H., Tajali, H., Rozbehani, A., Jamshidi, B. and Bocianowski, J. (2025).  Identification of high-yielding genotypes for cold climate in Iran using the GGE Biplot method. Crop Breeding and Applied Biotechnology 25: doi:10.1590/1984-703320 25v25n4a53.
Gomez, A. K. and A. A. Gomez. (1984). Statistical procedure for agricultural research. John Wiley and Sons. pp: 680.
Hebbache, H., Benkherbache, N., Mohamed Mefti, M., Houcine Bendada, H., Achouche, A., Liamine Hassous Kenzi, L. H. (2021). Genotype by environment interaction analysis of barley grain yield in the rain-fed regions of Algeria using AMMI model. Acta fytotechn zootechn, 24: 117–23.
Kendal, E., Karaman, M., Tekdal, S. Doğan, S. (2019). Analysis of promising barley (Hordeum vulgare L.) lines performance by AMMI and GGE biplot in multiple traits and environment. Applied Ecology and Environmental Research 17: 5219-33.
Khanzadeh, H., Vaezi, B., Mohammadi, R., Mehraban, A., Hosseinpor, T., and Shahbazi, K. (2018). Indian Journal of Agricultural Research 52: 16-21. doi:10.18805/IJARe.A-290.
Kilic, H. (2014). Additive main effect and multiplicative interactions (AMMI) analysis of grain yield in barley genotypes across environments. Journal of Agricultural Science 20: 337-44.
Lemma, M., Simion, T. and Markos, S. (2022). Evaluation of late maturing food barley varieties in Gamo highlands of southern Ethiopia. Advanced Journal of Biology 3: 7-11.
Mackaye, M, H., Bennani, S., Gaboun, F., Hassikou1, R., Diria, G., Abdellaoui, M. A., Taghouti, M. (2025). Identifying high-yielding and stable durum wheat genotypes using G×E analysis in in climate change. Plant Science Today 12: 1-11. doi:10.14719/pst.6023.
Mamo, T. (2017). Evaluation of improved food barley (Hordeum vulgare L.) varieties in the highland areas of Kaffa Zone, Southwestern Ethiopia. Agriculture, Forestry and Fisheries 6: 161-65.
Mansour, A. E., Moustafa, E. S. A., El-Naggar, N. Z. A., Abdelsalam, A. and Igartua, C. E. (2024). Grain yield stability of high-yielding barley genotypes under Egyptian conditions for enhancing resilience to climate change. Crop and Pasture Science 69: 681-90.doi:10.1071/CP18144.
Mekonnen, A., Mekbib, F. and Gashaw, A. (2019). AMMI and GGE biplot analysis of grain yield of bread wheat (Triticum aestivum L.) genotypes at moisture deficit environment of Wollo, Ethiopia. Journal of Agricultural Science and Practice 4: 9-19.  doi:10. 31248/JASP2019.123.
Purchase, J. L., Hatting, H. and Van Deventer, C. S. (2000). Genotype× environment interaction of winter wheat (Triticum aestivum L.) in South Africa: II. Stability analysis of yield performance. South African J. of Plant and Soil 17: 101-107.
SAS Institute Inc. (2016). SAS/STAT User’s Guide, Version 9, Carry, NC, USA.
Sayed, M. A., Badawy, A. F. and Khalil, M. A. (2018). Stability analysis and yield potentials of promising food barley genotypes under different environments. Australian Journal of Crop Science 12: 713-21.
Shibeshi, S. and Mekiso, M. (2022). Performance evaluation yield stability test of released food barley (Hordeum vulgare L.) varieties in highland areas of Siltie and Gurage Zones. Advances in Agriculture, Food Science and Forestry 10: 12-23.
Solonechnyi, P. M., Kozachenko, M. R., Vasko, N. I., Naumov, O. G., Solonechna, O. V., Vazhenina, O. and Kompanets, K. V. (2016). AMMI (Additive main effect and multiplicative interaction) model for assessment of yield stability of spring barley genotypes. Book: Plant Breeding and Seed Production. pp. 131-41. ISSN 1026-9959.
Tolesa, T., Ashagre, H. and Abera, T. (2019). Agronomic performance of food barley (Hordeum vulgare L.) varieties and their response to seed rate at Elfeta District, West Showa Zone, Oromia National Regional State. Journal of Science and Sustainable Development 7: 20-31.
Vaezi, B., Pour-Aboughadareh, A., Mohammadi, R., Armion, M., Mehraban, A., Hossein, T. and Dorrii. (2017). GGE biplot and AMMI analysis of barley yield performance in Iran. Crop Research Communications 45: 500-11.
Wardofa, G. A., Asnake, D. and Mohammed, H. (2019). GGE Biplot analysis of genotype by environment interaction and grain yield stability of bread wheat genotypes in Central Ethiopia. Journal of Plant Breeding and Genetics 07: 75-85.
Wijata, M., Suwara, I., Studnicki, M., Perzanowska, A., Ghafoor, A. Z. and Leszczy´nska, R. (2025). Yield and yield components stability of winter wheat and spring barley in long-term experiment in Poland. Sustainability 17: doi:10.3390/su17104577.
Yadav, O. P., Razdan, A. K. and Kumar, B. (2019). Genotype by environment interaction and stability analysis of grain yield in barley (Hordeum vulgare L.).  Journal of Pharmacognosy and Phytochemistry 8: 686-88.
Yan W, and Rajcan I. (2002). Biplot analysis of test sites and trait relations of soybean in Ontario. Crop Science 42:11–20. doi:10.2135/cropsci2002.1100.
Yan, W. (2002). Singular-value partitioning in biplot analysis of multi-environment trial data. Agron. J. 94: 990-96.
Yan, W., Hunt, L. A., Sheng, Q. and Szlavnics, Z. (2000). Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Sci. 40: 597-605.

Global Footprints