AMMI and GGE Biplot Analysis of Genotype-Environment Interaction in Environmental Trials of Pea Cultivars

Authors

  • A. O. Vasylenko Yuriev Plant Production Institute of NAAS of Ukraine, Ukraine
  • V. I. Sichkar Plant Breeding and Genetic Institute, Ukraine
  • L. M. Shevchenko Yuriev Plant Production Institute of NAAS of Ukraine, Ukraine
  • N. O. Vus French National Institute for Agriculture, Food, and Environment (INRAE), France
  • P. M. Solonechnyi Yuriev Plant Production Institute of NAAS of Ukraine, Ukraine
  • S. I. Silenko Ustymivka Experimental Station of Plant Production, Yuriev Plant Production Institute, Ukraine
  • Р. В. Solomonov Odessa State Agrarian University, Ukraine
  • V. I. Serdyuk Yuriev Plant Production Institute of NAAS of Ukraine, Ukraine
  • A. V. Glyantsev Yuriev Plant Production Institute of NAAS of Ukraine, Ukraine

DOI:

https://doi.org/10.30835/2413-7510.2025.333727

Keywords:

environmental trials, pea, AMMI, GGE biplot, cultivars, yield

Abstract

Results of AMMI and GGE biplot analysis summarizing data of environmental trials of pea cultivars are presented. The results of these methods were not identical and indicate the importance of each of these algorithms. Thus, the distribution of pea accessions by ranks (ASV) in the AMMI model placed cv. ‘Haiduk’ in the first position, but according to the results of the GGE biplot analysis, cv. ‘Oplot’ was the best ("ideal") genotype. Graphical visualization of results marking megaenvironments and cultivars that are the best in these environments is additional information to adjust breeding programs and to create adaptable pea cultivars for different growing zones. A separate advantage of GGE biplot is that it is able to assess the informativeness of test environments. In our study, not only the trial locations (Odesa State Experimental Station [Odeska Oblast], Ustymivka Experimental Station [Poltavska Oblast] and Yuriev Plant Production Institute [Kharkivska Oblast]) but also each year of trials at each location differed. Thus, AMMI and GGE biplot analysis, which process data of environmental trials of pea, do not exclude each other, but on the contrary, provide more detailed and complete information.

References

Eberhart S. A., Russell W. A. Stability parameters for comparing varieties. Crop Sci. 1966. Vol. 6(1). P. 36–40.

Yan W., Pageau D., Frégeau‐Reid J., Durand J. Assessing the representativeness and repeatability of test locations for genotype evaluation. Crop Sci. 2011. Vol. 51(4). P. 1603-1610. 10.2135/cropsci2011.01.0016

Yang X., Soliman A. A., Hu C., Yang F., Lv M., Yu H., Wang Y., Zheng A., Dai Z., Li Q., Yang Y., Yang J., Zhang Y., Niu W., Wang L., He Y. Yield Adaptability and Stability in Field Pea Genotypes Using AMMI, GGE, and GYT Biplot Analyses. Agriculture. 2023. Vol. 13. 1962. https://doi.org/10.3390/agriculture13101962

Ansarifard I., Mostafavi K., Khosroshahli M., Bihamta Reza M., Ramshini H. A study on genotype–environment interaction based on GGE biplot graphical method in sunflower genotypes (Helianthus annuus L.). Food Sci. Nutr. 2020. 00:1–8. https://doi.org/10.1002/fsn3.1610.

Yihunie T. A., Gesesse C. A. GGE Biplot Analysis of Genotype by Environment Interaction in Field Pea (Pisum sativum L.) Genotypes in Northwestern Ethiopia. J. Crop Sci. Biotechnol. 2018. Vol. 21. P. 67–74. https://doi.org/10.1007/s12892-017-0099-0

Girgel U., Cokkizgin A. GGE BIPLOT analysis in wild (Pisum sativum L. subsp. elatius and subsp. sativum) and cultivated pea (Pisum sativum L.) genotypes in Northern and Southern Turkey. Applied Ecology and Environmental Research. 2020. Vol. 18(1). P. 1237–1251. https://doi.org/10.15666/aeer/1801_12371251

Moraes Cunha Gonçalves G., Ferreira-Gomes R. L., Almeida Lopes Â. C., Melo Jorge Vieira P. F. Adaptability and yield stability of soybean genotypes by REML/BLUP and GGE Biplot. Crop Breeding and Applied Biotechnology. 2020. Vol. 20(2). e282920217. http://dx.doi.org/10.1590/1984-70332020v20n2a33

Solonechnyi P. N. AMMI and GGE biplot analysis of genotype-environment interaction of spring barley lines. Vavilovskiy Zhurnal Genetiki i Selektsii. 2017. Vol. 21(6). P. 657–662. https://doi.org/10.18699/VJ17.283 [in Russian]

Bezugla O. M., Kobyzeva L. N., Vus N. M., Solonechnyi P. M. Environmental trials of a model population of Phaseolus vulgaris L. in contrast climates. Plant Breeding and Seed Production. 2020. Vol. 118. P. 8–21. https://doi.org/10.30835/2413-7510.2020.222257

Das A., Parihar A. K., Saxena D., Singh D., Singha K. D., Kushwaha K. P. S., Chand R., Bal R. S., Chandra S., Gupta S. Deciphering genotype-by- environment interaction for targeting test environments and rust resistant genotypes in field pea (Pisum sativum L.). Front. Plant Sci. 2019. Vol. 10. 825. https://doi.org/10.3389/fpls.2019.00825

Osei O, Abaidoo RC, Opoku A, Rouws JRC, Boddey RM, Ahiabor BDK, Rouws LFM. Native bradyrhizobium strains from ghana can enhance grain yields of field-grown cowpea and groundnut. Front. Agron. 2020, 2:2. https://doi.org/10.3389/fagro.2020.00002.

Methodology of state variety trials of agricultural crops. K., 2000. Issue 1. 100 p. [in Ukrainian]

Methodology of state variety trials of agricultural crops. K., 2001. Issue 2. 68 p. [in Ukrainian]

GGE biplot. 2011. URL:www.ggebiplot.com

Purchase J. L., Hatting H., van Deventer C. S. Genotype × environment interaction of winter wheat (Triticum aestivum L.) in South Africa: II. Stability analysis of yield performance. South African J. Plant Soil. 2000. Vol. 17(3). P. 101–107. https://doi.org/10.1080/02571862.2000.10634878

Amelework A. B., Bairu M. W., Marx R., Laing M., Venter S. L. Genotype × environment interaction and stability analysis of selected cassava cultivars in South Africa. Plants. 2023. Vol. 12(13). 2490. https://doi.org/10.3390/plants12132490

Mullualem D., Tsega A., Mengie T., Fentie D., Kassa Z., Fassil A., Wondaferew D., Gelaw T. A., Astatkie T. Genotype-by-environment interaction and stability analysis of grain yield of bread wheat (Triticum aestivum L.) genotypes using AMMI and GGE biplot analyses, Heliyon. 2024. Vol. 10(12). e32918. https://doi.org/10.1016/j.heliyon.2024.e32918

Farshadfar E. Incorporation of AMMI stability value and grain yield in a single non-parametric index (GSI) in bread wheat Pakistan J. Biol. Sci. 2008. Vol. 11(14). P. 1791-1796. https://doi.org/10.3923/pjbs.2008.1791.1796

Pour-Aboughadareh A., Khalili M., Poczai P., Olivoto T. Stability indices to deciphering the genotype-by-environment interaction (GEI) effect: an applicable review for use in plant breeding programs Plants. 2022. Vol. 11 (3). 414. https://doi.org/10.3390/plants11030414

Goa Y., Mohammed H., Worku W., Urage E. Genotype by environment interaction and yield stability of cowpea (Vigna unguiculata (L.) Walp.) genotypes in moisture limited areas of Southern Ethiopia Heliyon. 2022. Vol. 8(3). e09013. https://doi.org/10.1016/j.heliyon.2022.e09013

Achenef G., Yilma G., Yimam K. Assessment of phenotypic stability and adaptability of elite field pea (Pisum sativum L) genotypes in Arsi zone. Ethiopia J. Agric. Food Res. 2024. Vol. 18(1). 101427. https://doi.org/10.1016/j.jafr.2024.101427

Daba S. D., Kiszonas A. M., McGee R. J. Selecting high-performing and stable pea genotypes in multi-environmental trial (MET): applying AMMI, GGE-biplot, and BLUP procedures. Plants. 2023. Vol. 12. 2343. https://doi.org/10.3390/plants12122343

Haile GA, Tesfaye D. Response of field pea (Pisum sativum L.) genotypes for grain yield in a multi-environment trial in Southeastern Ethiopia. Heliyon. 2024. Vol. 10(15). e35233. https://doi.org/10.1016/j.heliyon.2024.e35233

Kebede G. Y., Eritro T. A., Gutu D. T. Genotypetimes environment interaction and stability analysis of advanced field pea (Pisum sativum L.) genotypes in Southeastern Ethiopia. Ecol. Genet. Genom. 2024. Vol. 33. 100302. https://doi.org/10.1016/j.egg.2024.100302Get

Rao P. J. M, Sandhyakishore N., Sandeep S., Neelima G., Rao P. M., Das D. M., Saritha A. Evaluation of performance and yield stability analysis based on AMMI and GGE-biplot in promising pigeonpea [Cajanus cajan (L.) Millspaugh] genotypes. Legum Res. 2022. Vol. 45(11). P. 1414–1420. https://doi.org/10.18805/LR-4299

Pourmohammad A., Vaezi B., Jozeyan A., Hassanpouraghdam M. B. GGE biplot analysis of genotype× environment interaction and forage yield stability in grass pea (Lathyrus sativus) genotypes. Genetika. 2024. Vol. 56(1). P. 75–87. https://doi.org/10.2298/GENSR2401075P

Wondaferew D., Mullualem D., Bitewlgn W., Kassa Z. 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 Biol. 2024. Vol. 24(1). 1108. https://doi.org/10.1186/s12870-024-05829-4

Sharma A., Yadav R., Sheoran R., Kumar P. Evaluation of genotype × environment interactions for seed yield in field pea (Pisum sativum L.) genotypes using multivariate analysis model. Euphytica 2025, 221:58. https://doi.org/10.1007/s10681-025-03507-6

Yan W., Tinker N.A. Biplot analysis of multi-environment trial data: principles and applications Can. J. Plant Sci. 2006.Vol. 86(3). :P. 623-645. https://doi.org/10.4141/P05-169,

Yan W., Holland J. B. A heritability-adjusted GGE biplot for test environment evaluation. Euphytica. 2010. Vol. 171 (3). P. 355-369. https://doi.org/10.1007/s10681-009-0030-5

Frutos E., Galindo M. P., Leiva V. An interactive biplot implementation in R for modeling genotype-by-environment interaction Stoch. Environ. Res. Risk Assess. 2014. Vol. 28(7). P. 1629-1641. https://doi.org/10.1007/s00477-013-0821-z

Downloads

Published

2025-06-27

Issue

Section

ORIGINAL ARTICLES