Evaluation of new winter wheat varieties under different environmental conditions of Ukraine
DOI:
https://doi.org/10.32819/202601Keywords:
cereals; winter wheat; variety; environment; AMMI-analyse; yield; adaptability.Abstract
Yield stability depends largely on the resistance of varieties and hybrids to environmental stress factors. Assessing the extent of genotype × environment interaction (GEI) helps breeders select the best genotypes for submission to the State Variety Testing system. Multienvironment trials are a key tool for evaluating the adaptability of genotypes to contrasting soil and climatic conditions. In this study, the grain yield of 20 winter wheat varieties was analyzed across 17 environments represented by branches of the UIESR, covering the three major agroecological zones of Ukraine: the Steppe, Forest-Steppe, and Polissia. The AMMI analysis showed that the largest share of the total variance was attributable to the genotype × environment interaction, which exceeded the contributions of genotype and environment considered separately. This variance structure indicates substantial changes in cultivar ranking depending on the location of cultivation and confirms the need to account for adaptability when selecting varieties. Among the evaluated genotypes, the highest mean yield was recorded for LG Orlice, CHIKO, Bosporus, Khvylia Dnipra, and LG Quadrant. Special attention should be given to LG Orlice, which ranked among the leaders in most environments and demonstrated the broadest adaptability. The most stable genotype was MIP Roksolana, characterized by minimal interaction with the environment and high ecological plasticity. The group of relatively stable varieties also included LG Quadrant, CHIKO, and LG Orlice. Considering the combination of high yield and stability, the most promising candidates for broad adoption are LG Orlice, CHIKO, and LG Quadrant. In the Steppe zone (Dnipropetrovsk, Kirovohrad, and Odesa environments), the highest productivity was shown by CHIKO and LG Orlice, whereas in the Kirovohrad branch Khvylia Dnipra and Bosporus dominated, indicating specific adaptation to drier conditions. In the Forest-Steppe zone, the most frequent leaders were Bosporus, Khvylia Dnipra, LG Orlice, and CHIKO, which characterizes them as high-yielding genotypes for moderately moist conditions. In Polissia, LG Orlice and CHIKO dominated in virtually all environments, demonstrating consistently high yields under sufficient moisture supply. Bosporus and LG Quadrant are also considered promising for this zone. The obtained results confirm the necessity of a zonal approach to the deployment of winter wheat varieties and demonstrate the feasibility of using universally adapted genotypes as a foundation for large-scale production. The objective of the research was to determine the degree of influence of genotype, environment, and their interaction on yield and to identify stable and productive genotypes. The experiment was established in a randomized design with three replications. Analysis of variance of yield data quantified the contributions of environmental effects (37.7%), genotype (14.3%), and genotype × environment interaction (48.0%) to overall yield variability.
References
Abdelghany, A. M., Lamlom, S. F., & Naser, M. (2024). Dissecting the resilience of barley genotypes under multiple adverse environmental conditions. BMC Plant Biology, 24, 16.
Abdolshahi, R., Nazari, M., Safarian, A., Sadathossini, T., Salarpour, M., & Amiri, H. (2015). Integrated selection criteria for drought tolerance in wheat (Triticum aestivum L.) breeding programs using discriminant analysis. Field Crops Research, 174, 20–29.
Abebe, A. T., Adewumi, A. S., Adebayo, M. A., Shaahu, A., Mushoriwa, H., Alabi, T., Derera, J., Agbona, A., & Chigeza, G. (2024). Genotype × environment interaction and yield stability of soybean (Glycine max L.) genotypes in multi-environment trials (METs) in Nigeria. Heliyon, 10(19), e38097.
Ahmadi, J., Mohammadi, A., & Najafi Mirak, T. (2012). Targeting promising bread wheat (Triticum aestivum L.) lines for cold climate growing environments using AMMI and SREG GGE biplot analyses. Journal of Agricultural Science and Technology, 14, 645–657.
Al-Ghumaiz, N. S., Motawei, M. I., Aggag, A. M., Al-Otayk, S. M., & Alzamil, A. A. (2025). Phenotypic stability and adaptability of wheat genotypes under organic and conventional farming systems over five years using AMMI and GGE biplot analysis. Frontiers in Plant Science, 16, 1693316.
Bhandari, R., Poudel, M. R., Paudel, H., Neupane, M. P., Solanki, P., & Kushwaha, U. K. S. (2026). Breeding climate-resilient wheat for Nepalese agricultural system under diverse abiotic stresses using an integrated AMMI, GGE and stress tolerance indices. Scientific Reports, 16(1), 1751.
Bishwas, K. C. B., Poudel, M. R., & Regmi, D. (2021). AMMI and GGE biplot analysis of yield of different elite wheat line under terminal heat stress and irrigated environments. Heliyon, 7(6), e07206.
Brković, P., Matković Stojšin, M., Nikolić, O., Perišić, V., Luković, K., Babić, S., & Roljević Nikolić, S. (2025). Yield stability and antioxidant response of wheat under multi-environment conditions: Insights from AMMI and GGE Biplot Analyses. Agronomy, 15(12), 2684.
Cohen, I., Zandalinas, S. I., Huck, C., Fritschi, F. B., & Mittler, R. (2021). Meta-analysis of drought and heat stress combination impact on crop yield and yield components. Physiologia Plantarum, 171(1), 66–76.
Dang, X., Hu, X., Ma, Y., Li, Y., Kan, W., & Dong, X. (2024). AMMI and GGE biplot analysis for genotype × environment interactions affecting the yield and quality characteristics of sugar beet. PeerJ, 12, e16882.
Dehghani, M. R., Majidi, M. M., Mirlohi, A., & Saeidi, G. (2017). Study of genotype by environment interaction in tall fescue genotypes and their polycross progenies in Iran based on AMMI model analysis. Crop and Pasture Science, 67, 792–799.
Ejaz, I., Pu, X., Naseer, M. A., Bohoussou, Y. N. D., Liu, Y., Farooq, M., Zhang, J., Zhang, Y., Wang, Z., & Sun, Z. (2023). Cold and drought stresses in wheat: A global meta-analysis of 21st century. Journal of Plant Growth Regulation, 42(9), 5379–5395.
Güngör, H., Türkoğlu, A., Çakır, M. F., Dumlupınar, Z., Piekutowska, M., Wojciechowski, T., & Niedbała, G. (2024). GT biplot and cluster analysis of barley (Hordeum vulgare L.) germplasm from various geographical regions based on agro-morphological traits. Agronomy, 14(10), 2188.
Gupta, V., Mehta, G., Kumar, S., Ramadas, S., Tiwari, R., Singh, G. P., & Sharma, P. (2023). AMMI and GGE biplot analysis of yield under terminal heat tolerance in wheat. Molecular Biology Reports, 50(4), 3459–3467.
Jha, U. C., Bohra, A., & Jha, R. (2017). Breeding approaches and genomics technologies to increase crop yield under low-temperature stress. Plant cell reports, 36(1), 1–35.
Kebede, G., Worku, W., Feyissa, F., & Jifar, H. (2023). Genotype by environment interaction for agro-morphological traits and herbage nutritive values and fodder yield stability in oat (Avena sativa L.) using AMMI analysis in Ethiopia. Journal of Agriculture and Food Research, 14, 100862.
Mohammadi, R., Abdipour, M., Rahmati, M., Armion, M., Mehri, N., & Mehraban, A. (2025). Genotype × environment interaction analysis and climatic factors impacts on grain yield in rainfed durum wheat trials in Iran. BMC Plant Biology, 25(1), 1065.
Mullualem, D., Tsega, A., Mengie, T., Fentie, D., Kassa, Z., Fassil, A., Wondaferew, D., Gelaw, T. A., & Astatkie, T. (2024). Genotype-by-environment interaction and stability analysis of grain yield of bread wheat (Triticum aestivum L.) genotypes using AMMI and GGE biplot analyses. Heliyon, 10(12), e32918.
Murphy, M. E., Boruff, B., Callow, J. N., & Flower, K. C. (2020). Detecting frost stress in wheat: A controlled environment hyperspectral study on wheat plant components and implications for multispectral field sensing. Remote Sensing, 12(3), 477.
Nazarenko, M., Izhboldin, O. & Izhboldina, O. (2022). Study of variability of winter wheat varieties and lines in terms of winter hardness and drought resistance. AgroLife Scientific Journal, 11(2), 116–123.
Nazarenko, M., Mykolenko, S., & Chernysky, V. (2019). Modern Ukrainian winter wheat varieties grain productivity and quality at ecological exam. Agriculture and Forestry, 65(1), 127–136.
Nazarenko, M., Okselenko, O., & Pozniak, V. (2023). Ecology-and geography-related features of winter wheat varieties for the areas of insufficient humidification. Agriculture and Forestry, 69(3), 159–177.
Omrani, A., Omrani, S., Khodarahmi, M., Shojaei, S. H., Illés, Á., Bojtor, C., Mousavi, S. M. N., & Nagy, J. (2022). Evaluation of grain yield stability in some selected wheat genotypes using AMMI and GGE biplot methods. Agronomy, 12(5), 1130.
Pour-Aboughadareh, A., Jamshidi, B., Jadidi, O., Bocianowski, J., & Niemann, J. (2025). Multi-trait stability index in the selection of high-yielding and stable barley genotypes. Journal of Applied Genetics, in press.
Saeidnia, F., Majidi, M. M., Dehghani, M. R., Saeidi, G., & Mirlohi, A. (2022). Drought tolerance and stability of native Iranian tall fescue genotypes: Comparison of AMMI and GGE biplot analyses. Agronomy Journal, 114, 2180–2185.
Saeidnia, F., Shoormij, F., Mirlohi, A., Soleimani Kartalaei, E., Mohammadi, M., & Sabzalian, M. R. (2023). Drought adaptability of different subspecies of tetraploid wheat (Triticum turgidum) under contrasting moisture conditions: Association with solvent retention capacity and quality-related traits. PLoS One, 18(2), e0275412.
Saeidnia, F., Taherian, M., & Nazeri, S. M. (2023). Graphical analysis of multi-environmental trials for wheat grain yield based on GGE-biplot analysis under diverse sowing dates. BMC Plant Biology, 23(1), 198.
Sallam, A., Alqudah, A. M., Dawood, M. F. A., Baenziger, P. S., & Börner, A. (2019). Drought stress tolerance in wheat and barley: Advances in physiology, breeding and genetics research. International Journal of Molecular Sciences, 20(13), 3137.
Taherian, M., Saeidnia, F., Hamid, R., & Nazeri, S. M. (2024). Identification of high-yielding and stable cultivars of wheat under different sowing dates: Comparison of AMMI and GGE-biplot analyses. Heliyon, 10(20), e39599.
Tshikunde, N. M., Mashilo, J., Shimelis, H., & Odindo, A. (2019). Agronomic and physiological traits, and associated quantitative trait loci (QTL) affecting yield response in wheat (Triticum aestivum L.): A review. Frontiers in Plant Science, 10, 1428.
Urbanaviciute, I., Bonfiglioli, L., & Pagnotta, M. A. (2024). Selection of durum wheat and SSR markers for agronomic farming in Central Italy using AMMI analysis. Agronomy, 14(3), 458.
Yan, W. (2024). Two types of biplots to integrate multi-trial and multi-trait information for genotype selection. Crop Science, 64, 1608–1618.
Ye, X., Li, J., Cheng, Y., Yao, F., Long, L., Wang, Y., Wu, Y., Li, J., Wang, J., Jiang, Q., Kang, H., Li, W., Qi, P., Lan, X., Ma, J., Liu, Y., Jiang, Y., Wei, Y., Chen, X., Liu, C., Chen, G. (2019). Genome-wide association study reveals new loci for yield-related traits in Sichuan wheat germplasm under stripe rust stress. BMC Genomics, 20(1), 640.
Yue, H., Wang, Y., Chen, Z., Zhu, J., Behera, P. P., Liu, P., Yang, H., Wei, J., Bu, J., Jiang, X., & Ma, W. (2025). Assessing the role of genotype by environment interaction of winter wheat cultivars using envirotyping techniques in North China. Frontiers in Plant Science, 16, 1538661.
