Genetic sources of yield and stability for winter barley breeding under conditions of the Ukrainian Forest-Steppe

Authors

DOI:

https://doi.org/10.21498/2518-1017.21.1.2025.327499

Keywords:

Hordeum vulgare L., statistical parameter of adaptability, AMMI, GGE biplot, correlation, cluster analysis

Abstract

Purpose. To determine the peculiarities of the level of manifestation and yield variability of winter barley accessions, and to identify genetic sources for breeding in the Ukrainian Forest-Steppe. Methods. The research was conducted at the V. M. Remeslo Myronivka Institute of Wheat of NAAS in 2018/19, 2020/21 and 2021/22. A total of 74 spring barley samples of different origins were used for the research. The interaction “genotype × year” was determined and the accessions characterized using the statistical parameters of adaptability and graphical models AMMI and GGE biplot. The latter were then grouped using cluster analysis. Analysis of variance and correlation analyses were used to determine the level of reliability in the experiment and the relationship between the adaptability parameters, respectively. Results. Significant variability in yield was found both between years of the study (from 436 g/m2 in 2018/19 to 621 g/m2 in 2021/22) and between accessions within a year (2018/19 – from 625 to 171 g/m2, 2020/21 – from 738 to 138 g/m2, 2021/22 – from 855 to 374 g/m2). According to the AMMI model, statistically high shares of contribution to the total phenotypic variation were found for all its sources: year (41.72%), genotype (37.30%), and “genotype × year” interaction (21.15%). The first two principal components of this model covered 100% of the “genotype × year” variation, while the GGE biplot covered 85.14%. There were 12 accessions of winter barley of different origin [‘Merlo’ (FRA), ‘MIR 12-11’ (UKR), ‘Titus’ (DEU), ‘Akademichnyi’ (UKR), ‘MIR 12-9’ (UKR), ‘Snihova koroleva’ (UKR), ‘Novosadski 525’ (SRB), ‘Novosadski 737’ (SRB), ‘Matador’ (FRA), ‘Radical / Pervenets’ (SYR), ‘Scarpia’ (DEU), ‘Manitum’ (FRA)], which had significantly higher yields than the standard ‘Zherar’ (UKR) (587–685 g/m2 vs. 534 g/m2). However, even among them, the level of the latter showed different reactions to the conditions of particular years. This was reflected in different values of statistical parameters of adaptability and graphical distribution of accessions in the coordinates of the principal components of the AMMI and GGE biplot models. Based on the yield variation limits and statistical parameters of adaptability, the selected accessions were divided into five distinct clusters. Conclusions. The combination of high-yielding accessions from different clusters as the parental components of crosses, in accordance with ecological and geographical principles, will be of great practical importance in creating source material to increase winter barley yields and adaptability in Ukrainian Forest-Steppe region.

Downloads

Download data is not yet available.

References

Jiang, C., Kan, J., Gao, G., Dockter, C., Li, C., Wu, W., Yang, P., & Stein, N. (2025). Barley2035: A decadal vision for barley research and breeding. Molecular Plant, 18(2), 195–218. https://doi.org/10.1016/j.molp.2024.12.009

Yigit, A., & Chmielewski, F.-M. (2024). A deeper insight into the yield formation of winter and spring barley in relation to weather and climate variability. Agronomy, 14(7), Article 1503. https://doi.org/10.3390/agronomy14071503

Mittermayer, M., Maidl, F.-X., Donauer, J., Kimmelmann, S., Liebl, J., & Hülsbergen, K.-J. (2025). Optimizing nitrogen use efficiency and yield in winter barley: a three-year study of fertilization systems in southern Germany. Applied Sciences, 15(1), Article 391. https://doi.org/10.3390/app15010391

Heil, K., Gerl, S., & Schmidhalter, U. (2021). Sensitivity of winter barley yield to climate variability in a Pleistocene loess area. Climate, 9(7), Article 112. https://doi.org/10.3390/cli9070112

Hudzenko, V. M. (2018). Yield and stability of Myronivka winter barley varieties. Plant Breeding and Seed Production, 113, 55–77. https://doi.org/10.30835/2413-7510.2018.134358 [In Ukrainian]

Laidig, F., Piepho, H. P., Rentel, D., Drobek, T., & Meyer, U. (2017). Breeding progress, genotypic and environmental variation and correlation of quality traits in malting barley in German official variety trials between 1983 and 2015. Theoretical and Applied Genetics, 130(11), 2411–2429. https://doi.org/10.1007/s00122-017-2967-4

Laidig, F., Feike, T., Klocke, B. Macholdt, J., Miedaner, T., Rentel, D., & Piepho, H. P. (2021). Long term breeding progress of yield, yield related, and disease resistance traits in five cereal crops of German variety trials. Theoretical and Applied Genetics, 134(12), 3805–3827. https://doi.org/10.1007/s00122-021-03929-5

Kyrychenko, V. V., Vasko, N. I., Leonov, O. Yu., Shchypak, H. V., Suvorova, K. Yu., & Morhun, O. V. (2022). Current strategy of cereal breeding. Plant Breeding and Seed Production, 122, 100–112. https://doi.org/10.30835/2413-7510.2022.271759

Rodrigues, O., Minella, E., & Costenaro, E. R. (2020). Genetic improvement of barley (Hordeum vulgare L.) in Brazil: yield increase and associated traits. Agricultural Sciences, 11(04), 425–438. https://doi.org/10.4236/as.2020.114025

Rodrigues, O., Minella, E., Costenaro, E. R., Scariotto, S., & Marchese, J. A. (2022). Improvement in Brazilian barley breeding: changes in developmental phases and ecophysiological traits. Frontiers in Plant Science, 13, Article 1032243. https://doi.org/10.3389/fpls.2022.1032243

Laidig, F., Feike, T., Hadasch, S., Rentel, D., Klocke, B., Miedaner, T., & Piepho, H. P. (2021). Breeding progress of disease resistance and impact of disease severity under natural infections in winter wheat variety trials. Theoretical and Applied Genetics, 134(5), 1281–1302. https://doi.org/10.1007/s00122-020-03728-4

Zetzsche, H., Friedt, W., & Ordon, F. (2020). Breeding progress for pathogen resistance is a second major driver for yield increase in German winter wheat at contrasting N levels. Scientific Reports, 10(1), Article 20374. https://doi.org/10.1038/s41598-020-77200-0

Muñoz-Amatriaín, M., Hernandez, J., Herb, D., Baenziger, P. S., Bochard, A. M., Capettini, F., Casas, A., Cuesta-Marcos, A., Einfeldt, C., Fisk, S., Genty, A., Helgerson, L., Herz, M., Hu, G., Igartua, E., Karsai, I., Nakamura, T., Sato, K., Smith, K., … Hayes, P. (2020). Perspectives on low temperature tolerance and vernalization sensitivity in barley: prospects for facultative growth habit. Frontiers in Plant Science, 11, Article 585927. https://doi.org/10.3389/fpls.2020.585927

Wójcik-Jagła, M., Daszkowska-Golec, A., Fiust, A., Kopec, P., & Rapacz, M. (2021). Identification of the genetic basis of response to de-acclimation in winter barley. International Journal of Molecular Sciences, 22(3), Article 1057. https://doi.org/10.3390/ijms22031057

Wójcik-Jagła, M., & Rapacz, M. (2023). Freezing tolerance and tolerance to de acclimation of European accessions of winter and facultative barley. Scientific Reports, 13(1), Article 19931. https://doi.org/10.1038/s41598-023-47318-y

Thabet, S. G., Moursi, Y. S., Karam, M. A., Börner, A., & Alqudah, A. M. (2020). Natural variation uncovers candidate genes for barley spikelet number and grain yield under drought stress. Genes, 11(5), Article 533. https://doi.org/10.3390/genes11050533

Slawin, C., Ajayi, O., & Mahalingam, R. (2024). Association mapping unravels the genetic basis for drought related traits in different developmental stages of barley. Scientific Reports, 14(1), Article 25121. https://doi.org/10.1038/s41598-024-73618-y

Sapkota, S., Mndolwa, E., Hu, G., Fiedler, J., Nandety, S. R., Carlson, C. H., & Klos, K. E. (2025). Association mapping of drought stress response for yield and quality traits in barley. Crop Science, 65(1), Article e21431. https://doi.org/10.1002/csc2.21431

Bai, Y., Zhao, X., Yao, X., Yao, Y., Li, X., Hou, L., An, L., Wu, K., & Wang, Z. (2023). Comparative transcriptome analysis of major lodging resistant factors in hulless barley. Frontiers in Plant Science, 14, Article 1230792. https://doi.org/10.3389/fpls.2023.1230792

Guo, J., Zhao, C., Gupta, S., Platz, G., Snyman, L., & Zhou, M. (2024). Genome wide association mapping for seedling and adult resistance to powdery mildew in barley. Theoretical and Applied Genetics, 137(3), Article 50. https://doi.org/10.1007/s00122-024-04550-y

Backes, A., Guerriero, G., Ait Barka, E., & Jacquard, C. (2021). Pyrenophora teres: taxonomy, morphology, interaction with barley, and mode of control. Frontiers Plant Science, 12, Article 614951. https://doi.org/10.3389/fpls.2021.614951

Basak, P., Gurjar, M. S., Kumar, T. P. J., Kashyap, N., Singh, D., Jha, S. K., & Saharan, M. S. (2024). Transcriptome analysis of Bipolaris sorokiniana – Hordeum vulgare provides insights into mechanisms of host-pathogen interaction. Frontiers in Microbiology, 15, Article 1360571. https://doi.org/10.3389/fmicb.2024.1360571

Salgotra, R. K., & Chauhan, B. S. (2023). Genetic diversity, conservation, and utilization of plant genetic resources. Genes, 14(1), Article 174. https://doi.org/10.3390/genes14010174

Dempewolfa, H., Krishnana, S., & Guarinoa, L. (2023). Our shared global responsibility: safeguarding crop diversity for future generations. Proceedings of the National Academy of Sciences of the United States of America, 120(14), Article e2205768119. https://doi.org/10.1073/pnas.2205768119

Ebert, A. W., Engels, J. M. M., Schafleitner, R., van Hintum, T., & Mwila, G. (2023). Critical review of the increasing complexity of access and benefit-sharing policies of genetic resources for genebank curators and plant breeders – a public and private sector perspective. Plants, 12(16), Article 2992. https://doi.org/10.3390/plants12162992

Riabchun, V. K., Kuzmyshyna, N. V., & Bohuslavskyi, R. L. (2022). State of national plant genebank of Ukraine in wartime of 2022. Plant Genetic Resources, 30, 1–21. https://doi.org/10.36814/pgr.2022.30.01 [In Ukrainian]

Galluzzi, G., Seyoum, A., Halewood, M., Noriega, I. L., & Welch, E. W. (2020). The role of genetic resources in breeding for climate change: the case of public breeding programmes in eighteen developing countries. Plants, 9(9), Article 1129. https://doi.org/10.3390/plants9091129

Cortés, A. J., & López-Hernández, F. (2021). Harnessing crop wild diversity for climate change adaptation. Genes, 12(5), Article 783. https://doi.org/10.3390/genes12050783

Monteiro, V. A., Amabile, R. F., Spehar, C. R., Faleiro, F. G., Vieira, E. A., Peixoto, J. R., Junior, W. Q. R., & Montalvão, A. P. L. (2020). Genetic diversity among 435 barley accessions based in morpho-agronomical characteristics under irrigation in the Brazilian savannah. Australian Journal of Crop Science, 14(9), 1385–1393. https://doi.org/10.21475/ajcs.20.14.09.p2281

Czembor, J. H. (2023). Barley genetic resources: advancing conservation and applications for breeding. Agronomy, 13(12), Article 2901. https://doi.org/10.3390/agronomy13122901

Bernád, V., Al-Tamimi, N., Langan, P., Gillespie, G., Dempsey, T., Henchy, J., Harty, M., Ramsay, L., Houston, K., Macaulay, M., Shaw, P. D., Raubach, S., Mcdonnel, K. P., Russell, J., Waugh, R., Khodaeiaminjan, M., & Negrão, S. (2024). Unlocking the genetic diversity and population structure of the newly introduced two-row spring European HerItage barley collecTion (ExHIBiT). Frontiers in Plant Science, 15, Article 1268847. https://doi.org/10.3389/fpls.2024.1268847

Kostrzewska, M. K., & Jastrzebska, M. (2024). Exploiting the yield potential of spring barley in Poland: the roles of crop rotation, cultivar, and plant protection. Agriculture, 14(8), Article 1355. https://doi.org/10.3390/agriculture14081355

Bai, Y., Zhao, X., Yao, X., Yao, Y., An, L., Li, X., Wang, Y., Gao, X., Jia, Y., Guan, L., Li, M., Wu, K., & Wang, Z. (2021). Genome wide association study of plant height and tiller number in hulless barley. PLoS One, 16(12), Article e0260723. https://doi.org/10.1371/journal.pone.0260723

Gasparis, S., & Miłoszewski, M. M. (2023). Genetic basis of grain size and weight in rice, wheat, and barley. International Journal of Molecular Sciences, 24(23), Article 16921. https://doi.org/10.3390/ijms242316921

Thirulogachandar, V., & Schnurbusch, T. (2021). ‘Spikelet stop’ determines the maximum yield potential stage in barley. Journal of Experimental Botany, 72(22), 7743–7753. https://doi.org/10.1093/jxb/erab342

Lenartowicz, T., Bujak, H., Przystalski, M., Piecuch, K., Jnczyk, K., & Feledyn-Szewczyk, B. (2024). Yield stability and adaptability of spring barley (Hordeum vulgare) varieties in Polish organic field trials. Agronomy, 14(9), Article 1963. https://doi.org/10.3390/agronomy14091963

Kulheri, A., Rajput, S. S., Punia, S. S., & Jakhar, K. (2024). Stability analysis in six-row barley genotypes for grain yield in multi-environmental trails using Eberhart and Russel (1966). International Journal of Environment and Climate Change, 14(7), 10–15. https://doi.org/10.9734/ijecc/2024/v14i74247

Elakhdar, A., El-Naggar, A. A., El-Wakeell, S., & Ahmed, A. H. (2025). Integrating univariate and multivariate stability indices for breeding clime-resilient barley cultivars. BMC Plant Biology, 25(1), Article 76. https://doi.org/10.1186/s12870-024-05530-6

Anshori, M. F., Musa, Y., Farid, M., Jayadi, M., Padjung, R., Kaimuddin, K., Huang, Y. C., Casimero, M., Bogayong, I., Suwarno, W. B., Sembiring, H., Purwoko, B. S., Nur, A., Wahyuni, W., Wasonga, D. O., & Seleiman, M. F. (2024). A comprehensive multivariate approach for G×E interaction analysis in early maturing rice varieties. Frontiers in Plant Science, 15, Article 1462981. https://doi.org/10.3389/fpls.2024.1462981

Wang, R., Wang, H., Huang, S., Zhao, Y., Chen, E., Li, F., Qin, L., Yang, Y., Guan, Y., Liu, B., & Zhang, H. (2023). Assessment of yield performances for grain sorghum varieties by AMMI and GGE biplot analyses. Frontiers in Plant Science, 14, Article 1261323. https://doi.org/10.3389/fpls.2023.1261323

Demelash, H. (2024). Genotype by environment interaction, AMMI, GGE biplot, and mega environment analysis of elite Sorghum bicolor (L.) Moench genotypes in humid lowland areas of Ethiopia. Heliyon, 10(5), Article e26528. https://doi.org/10.1016/j.heliyon.2024.e26528

Wondaferew, D., Mullualem, D., Bitewlgn, W., Kassa, Z., Abebaw, Y., Ali, H., Kebede, K., & Astatkie, T. (2024). Cultivating sustainable futures: multi-environment evaluation and seed yield stability of faba bean (Vicia faba L.) genotypes by using different stability parameters in Ethiopia. BMC Plant Biology, 24(1), Article 1108. https://doi.org/10.1186/s12870-024-05829-4

Esan, V. I., Oke, G. O., Ogunbode, T. O., & Obisesan, I. A. (2023). AMMI and GGE biplot analyses of Bambara groundnut [Vigna subterranea (L.) Verdc.] for agronomic performances under three environmental conditions. Frontiers in Plant Science, 13, Article 997429. https://doi.org/10.3389/fpls.2022.997429

Mekonnen, B., & Gurmu, F. (2024). Evaluation of the performance and stability of early maturing orange-fleshed sweet potato genotypes in selected areas in Ethiopia. PLoS ONE, 19(10), Article e0310273. https://doi.org/10.1371/journal.pone.0310273

Nagrale, S. C., Sakhare, S. B., Nichal, S. S., Yadirwar, P. V., Tayade, N. R., & Verma, L. K. (2023). Stability and G×E interaction study in sunflower (Helianthus annuus L.) for diverse environments. Electronic Journal of Plant Breeding, 14(2), 601–607. https://doi.org/10.37992/2023.1402.077

Sadhu, S., Chakraborty, M., Roy, S. K., Mondal, A., & Dey, S. (2024). Stability analysis on elite genotypes of Indian Mustard (Brassica juncea L.) in Terai agro-climatic region. Electronic Journal of Plant Breeding, 15(3), 660–670. https://doi.org/10.37992/2024.1503.084

Bomma, N., Shruthi, H. B., Soregaon, C. D., Gaddameedi, A., Suma, K., Pranati, J., Chandappa, L. H., Patil, D. K., Kumar, N., Sandeep, S., Vemula, A., & Gangashetty, P. I. (2024). Multi-environment testing for G×E interactions and identification of high-yielding, stable, medium-duration pigeonpea genotypes employing AMMI, GGE biplot, and YREM analyses. Frontiers in Plant Science, 15, Article 1396826. https://doi.org/10.3389/fpls.2024.1396826

Azon, C. F., Fassinou Hotegni, V. N., Sogbohossou, D. E. O., Gnanglè, L. S., Bodjrenou, G., Adjé, C. O., Dossa, K., Agbangla, C., Quenum, F. J. B., & Achigan-Dako, E. G. (2023). Genotype × environment interaction and stability analysis for seed yield and yield components in sesame (Sesamum indicum L.) in Benin Republic using AMMI, GGE biplot and MTSI. Heliyon, 9(11), Article e21656. https://doi.org/10.1016/j.heliyon.2023.e21656

Jayalakshmi, V., Laxuman, C., Patil, M. D., Ramadevi, S., & Reddy, A. L. (2024). Stability analysis for yield and yield related traits in advance breeding lines of chickpea (Cicer arietinum L.). Electronic Journal of Plant Breeding, 15(1), 132–137. https://doi.org/10.37992/2024.1501.022

Eberhart, S. A., & Russel, W. A. (1966). Stability parameters for comparing varieties. Crop Science, 6(1), 36–40. https://doi.org/10.2135/cropsci1966.0011183X000600010011x

Wricke, G. (1962). Über eine Methode zur Erfassung der ökologischen Streubreite in Feldversuchen. Zeitschrift für Pflanzenzüchtung, 47, 92–96.

Lin, C. S., & Binns, M. R. (1988). A superiority measure of cultivar performance for cultivar × location data. Canadian Journal of Plant Science, 68(1), 193–198. https://doi.org/10.4141/cjps88-018

Huehn, M. (1990). Nonparametric measures of phenotypic stability. Part 1: Theory. Euphytica, 47(3), 189–194. https://doi.org/10.1007/BF00024241

Hudzenko, V. M., Buniak, N. M., Tsentylo, L. V., Demydov, O. A., Fedorenko, I. V., Fedorenko, M. V., Ishchenko, V. A., Kozelets, H. M., Khudolii, L. V., Lashuk, S. O., & Syplyva, N. O. (2022). Evaluation of grain yield performance and its stability in various spring barley accessions under condition of different agroclimatic zones of Ukraine. Biosystems Diversity, 30(4), 406–422. https://doi.org/10.15421/012240

Frutos, E., Galindo, M. P., & Leiva, V. (2014). An interactive biplot implementation in R for modeling genotype-by-environment interaction. Stochastic Environmental Research and Risk Assessment, 28(7), 1629–1641. https://doi.org/10.1007/s00477-013-0821-z

Yan, W., & Tinker, N. A. (2006). Biplot analysis of multi-environment trial data: principles and applications. Canadian Journal of Plant Science, 86(3), 623–645. https://doi.org/10.4141/P05-169

Yan, W., Kang, M. S., Ma, B., Woods, S., & Cornelius, P. L. (2007). GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Science, 47(2), 641–653. https://doi.org/10.2135/cropsci2006.06.0374

Gauch, H. G., Piepo, H.-P., & Annicchiarico, P. (2008). Statistical analysis of yield trials by AMMI and GGE: Further consideration. Crop Science, 48(3), 866–889. https://doi.org/10.2135/cropsci2007.09.0513

Published

2025-04-27

How to Cite

Hudzenko, V. M., Lysenko, A. A., Polishchuk, T. P., Buniak, N. M., Kuzmenko, Y. A., Yurchenko, T. V., Khudolii, L. V., & Kochovska, I. V. (2025). Genetic sources of yield and stability for winter barley breeding under conditions of the Ukrainian Forest-Steppe. Plant Varieties Studying and Protection, 21(1). https://doi.org/10.21498/2518-1017.21.1.2025.327499

Issue

Section

BREEDING AND SEED PRODUCTION