Application of advanced graphical models (GGE biplot, AMMI, WAASB) for assessing yield stability in practical breeding of winter hexaploid triticale
DOI:
https://doi.org/10.61308/WFRE2463Keywords:
triticale; yield stability; genotype × environment; GGE biplot; AMMI analysisAbstract
This study presents the application of advanced graphical and statistical models – GGE biplot, AMMI, and WAASB for the assessment of productivity and yield stability in winter hexaploid triticale. Sixteen genotypes (four standard varieties and twelve advanced breeding lines) were evaluated across three agro-ecologically contrasting growing seasons (2021–2024). The primary objective was to identify genotypes that combine high yield potential with stability across diverse environments. The results indicated considerable variability in yield performance depending on year and environmental conditions. The use of GGE biplot and AMMI models enabled a comprehensive analysis of genotype × environment interaction, revealing that lines G14 (193т/112-1), G7 (202/10-246), and G11 (107/09-273) exhibited both consistently high yields and notable stability, rendering them particularly promising for breeding and cultivation. The WAASB model provided an integrated evaluation of both productivity and stability, while the WAASBY index ranking further substantiated the superiority of these genotypes. The study also discusses the methodological limitations and emphasizes the necessity for further analyses employing advanced bioinformatics tools and a broader range of selection criteria. The practical relevance of these findings is the recommendation of stable, high-yielding genotypes suitable for a wide range of agro-ecological conditions.
References
Ashango, Z. B. A., Tumisa, K., Negash, K., & Fikre, A. (2016). Seed yield stability and genotype x environment interaction of common bean (Phaseolus vulgaris L.) lines in Ethiopia. International Journal of Plant Breeding and Crop Science, 3(2), 135-144.
Ayalew, H., Anderson, J. D., Krom, N., Tang, Y., Butler, T. J., Rawat, N., & Ma, X. F. (2022). Genotyping-by-sequencing and genomic selection applications in hexaploid triticale. G3, 12(2), jkab413.
Bilgin, O., Balkan, A., Korkut, Z. K., & Başer, İ. (2018). Multi-environmental evaluation of triticale, wheat and barley genotypes by GGE biplot analysis. Journal of Life Sciences, 12(1), 13-23.
Bocianowski, J., Tratwal, A., & Nowosad, K. (2021). Genotype by environment interaction for main winter triticale varieties characteristics at two levels of technology using additive main effects and multiplicative interaction model. Euphytica, 217(2), 26.
Bornhofen, E., Benin, G., Storck, L., Woyann, L. G., Duarte, T., Stoco, M. G., & Marchioro, S. V. (2017). Statistical methods to study adaptability and stability of wheat genotypes. Bragantia, 76, 1-10.
Cheshkova, A. F., Stepochkin, P. I., Aleynikov, A. F., Grebennikova, I. G., & Ponomarenko, V. I. (2020). A comparison of statistical methods for assessing winter wheat grain yield stability. Vavilov Journal of Genetics and Breeding, 24(3), 267.
Derejko, A., Studnicki, M., Wójcik-Gront, E., & Gacek, E. (2020). Adaptive grain yield patterns of Triticale (× Triticosecale Wittmack) cultivars in six regions of Poland. Agronomy, 10(3), 415.
de Melo, G. G., de Oliveira, L. A., da Silva, C. P., da Silva, A. Q., Nascimento, M. R., de Sousa Gonçalves, R. J., ... & da Silva, J. W. (2023). AMMI-Bayesian perspective in the selection of pre-cultivars of carioca beans in Agreste-Sertão of Pernambuco, Brazil. Scientific Reports, 13(1), 4700.
Derbew, S., Mekbib, F., Lakew, B., Bekele, A., & Bishaw, Z. (2024). AMMI and GGE biplot analysis for barley genotype yield performance and stability under multi environment condition in southern Ethiopia. Agrosystems, Geosciences & Environment, 7(3), e20565.
Dyulgerova, B., & Dyulgerov, N. (2024). Genotype-by-year interaction and simultaneous selection for grain yield and stability in winter barley. Bulgarian Journal of Agricultural Science, 30(3), 466–475
Đekić, V., Milivojević, J., & Branković, S. (2018). The interaction of genotype and environment on yield and quality components in triticale. Biologica Nyssana, 9(1), p. 45.
Ferreira, V., Grassi, E., Ferreira, A., Santo, H. D., Castillo, E., & Paccapelo, H. (2015). Genotype-environment interaction and stability of grain yield in triticales and tricepiros. Chilean Journal of Agricultural & Animal Sciences, ex Agro-Ciencia, 31(2), 93-104.
Gauch, H. J. (1992). Statistical analysis of regional yield trials: AMMI analysis of factorial designs (pp. 278).
Gauch Jr, H. G. (2006). Statistical analysis of yield trials by AMMI and GGE. Crop Science, 46(4), 1488-1500.
Gauch Jr, H. G., Piepho, H. P., & Annicchiarico, P. (2008). Statistical analysis of yield trials by AMMI and GGE: Further considerations. Crop Science, 48(3), 866-889.
Georgieva, R. G., & Kirchev, H. K. (2020). Ecological Plasticity and Stability of Some Agronomical Performances in Triticale Varieties (x Triticosecale Wittm). Ecologia Balkanica, 12(1), p. 93.
Goyal, A., Beres, B. L., Randhawa, H. S., Navabi, A., Salmon, D. F., & Eudes, F. (2011). Yield stability analysis of broadly adaptive triticale germplasm in southern and central Alberta, Canada, for industrial end-use suitability. Canadian Journal of Plant Science, 91(1), 125-135.
Grebennikova, I. G., Cheshkova, A. F., Stepochkin, P. I., Aleynikov, A. F., & Chanyshev, D. I. (2021). Environmental adaptive cultivar model development methods on the spring triticale example. In IOP Conference Series: Earth and Environmental Science (Vol. 839, No. 3, p. 032041). IOP Publishing.
Güngör, H., Çakir, M. F., & Dumlupinar, Z. (2022). Evaluation of triticale: Genotype by Environment interaction and GGE biplot analysis. JAPS: Journal of Animal & Plant Sciences, 32(6), p. 1637.
Jandong, E. A., Uguru, M. I., & Oyiga, B. C. (2011). Determination of yield stability of seven soybean (Glycine max) genotypes across diverse soil pH levels using GGE biplot analysis. Journal of Applied Biosciences, 43, 2924-2941.
Kaya, Y., & Ozer, E. (2014). Parametric stability analyses of multi-environment yield trials in triticale (xTriticosecale Wittmack). Genetika, 46(3), 705-718.
Kaya, Y., Akçura, M., & Taner, S. (2006). GGE-Biplot Analysis of Multi-Environment Yield Trials in Bread Wheat. Turkish Journal of Agriculture and Forestry, 30(5), Article 3.
Kendal, E., & Sayar, M. S. (2016). The stability of some spring triticale genotypes using biplot analysis. JAPS: Journal of Animal & Plant Sciences, 26(3), 754-765.
Kendal, E., Sayar, M. S., Tekdal, S., Aktas, H., & Karaman, M. (2016). Assessment of the impact of ecological factors on yield and quality parameters in triticale using GGE biplot and AMMI analysis. Pakistan Journal of Botany, 48(5), 1903-1913.
Kendal, E., Tekdal, S., & Karaman, M. (2019). Proficiency of biplot methods (AMMI and GGE) in the appraisal of Triticale genotypes in multiple environments. Applied Ecology & Environmental Research, 17(3), 5995-6007.
Kutlu, I., & Gülmezoğlu, N. (2017). Genotypic response on stability for yield and nitrogen use efficiency in triticale (X Triticosecale Wittmack) under different nitrogen regimes. Biol Divers Conserv, 10(1), 84-91.
Lule, D., Tesfaye, K., & Mengistu, G. (2014). Genotype by environment interaction and grain yield stability analysis for advanced triticale (x. Triticosecale Wittmack) genotypes in Western Oromia, Ethiopia. SINET: Ethiopian Journal of Science, 37(1), 63-68.
Neykov, N. (2024). Evaluation of the stability and adaptability of yield in triticale varieties using non-parametric methods. Bulgarian Journal of Agricultural Science, 30(2), 301-304.
Olivoto, T., Lúcio, A. D., da Silva, J. A., Marchioro, V. S., de Souza, V. Q., & Jost, E. (2019). Mean performance and stability in multi‐environment trials I: combining features of AMMI and BLUP techniques. Agronomy Journal, 111(6), 2949-2960.
Olivoto, T., & Lúcio, A. D. C. (2020). metan: An R package for multi‐environment trial analysis. Methods in Ecology and Evolution, 11(6), 783-789.
Oral, E. (2018). Effect of nitrogen fertilization levels on grain yield and yield components in triticale based on AMMI and GGE biplot analysis. Applied Ecology & Environmental Research, 16(4), 65-4878.
Milgate, A., Ovenden, B., Adorada, D., Lisle, C., Lacy, J., & Coombes, N. (2015). Genetic improvement of triticale for irrigated systems in southeastern Australia: a study of genotype and genotype× environment interactions. Crop and Pasture Science, 66(8), 782-792.
Mossie, T., Biratu, K., & Yifred, H. (2024). Agronomic performance and dry matter yield stability of Napier grass (Pennisetum purpureum) genotypes in Southwestern Ethiopia. Agronomy Journal, 116(5), 2304-2317.
Motzo, R., Giunta, F., & Deidda, M. (2001). Factors affecting the genotype × environment interaction in spring triticale grown in a Mediterranean environment. Euphytica, 121(3), 317-324.
Naroui Rad, M. R., Bakhshi, B., Ghasemi, A., Ghasemi, M. M., & Kohpalekani, J. A. (2025). Identification of High‐Yielding and Drought‐Tolerant Melon Genotypes Based on Yield–Trait Combinations: A Comparison of Pcor Index and GYT Biplot Approaches. Food Science & Nutrition, 13(3), e70048.
Saed-Moucheshi, A., Babaei, S., & Ansarshourijeh, F. (2024). Innovative multi-trial breeding and genotype screening in triticale (x Triticosecale Wittmack) for enhanced stability under drought stress. Scientific Reports, 14(1), 28273.
Stoyanov, H., Baychev, V., Petrova, T., & Mihova, G. (2017). Triticale cultivars suitable for growing under high level of abiotic stress. Journal of Mountain Agriculture on the Balkans (JMAB), 20(6), 223-242.
Stoyanov, H., & Baychev, V. (2018). Tendencies in the yield and its components of the Bulgarian varieties of triticale, grown under contrasting conditions of the environment. Bulgarian Journal of Crop Science, 55(3), 16-26 (Bg).
Stoyanov, H. (2021). Environment adjusted yield model for ranking and stability assessment of winter triticale (X Triticosecale Wittm.) Genotypes. International Journal of Innovative Approaches in Agricultural Research, 5(1), 141-157.
Stoyanov, H., & Baychev, V. (2023). Analysis of genotype x environment interaction in triticale lines with AMMI and PCA. AgroLife Scientific Journal, 12(2), 190-199.
Stoyanov, H. (2024). Productivity and Stability Characteristics of Winter Hexaploid Triticale Cultivars with Different Geographical Origins. I. Real Yield Features. Journal of Mountain Agriculture on the Balkans, 27, 6, 220–244.
Stoyanov, H. (2025). A conceptual method for value determination of the contrast between common winter wheat genotypes in terms of their productivity. Bulgarian Journal of Crop Science, 62(2) 16-33 (Bg).
Tsenov, N., Gubatov, T. & Yanchev, I. (2022). Indices for assessing the adaptation of wheat in the genotype x environment interaction. Rastenievadni nauki, 59(2), 16-34 (Bg).
Yan, W., & Kang, M. S. (2002). GGE biplot analysis: A graphical tool for breeders, geneticists, and agronomists. CRC Press.
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), 643-653.
Yan, W., & Holland, J. B. (2010). A heritability-adjusted GGE biplot for test environment evaluation. Euphytica, 171(3), 355-369.
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