Al-Qadisiyah Journal For Agriculture Sciences

Stability Analysis and Selection of Maize (Zea mays L.) Genotypes Using AMMI and GGE Biplot

Document Type : Research Paper

Authors

Gemechu Asefa 1
Temesgen Chibsa 1
Desalegn Chalchisa 1
Beyene Abebebe 1
Tolera Keno 1
Sara Oli 1
Lemi Yadesa 1
Bitew Tilahun 1
Belay Garoma 1
Yaregal Damtie 2
Yednikachew Marid 3
Mamud Aman 3
Megersa Mengesha 4
Zenebech Teshome 5
Bedilu Goben 6

1 Maize Breeder, Bako National Maize Research Center, EIAR

2 Maize Breeder, Pawe Agricultural Research Center,EIAR

3 Maize Breeder, Hawassa Agricultural Research Center, EIAR

4 Maize Agronomist, Asosa Agricultural Research Center, EIAR

5 Maize Breeder, Jimma Agricultural Research Centerr, EIAR

6 Maize Breeder, Bako National Maize Research Center,EIAR

https://doi.org/10.33794/qjas.2024.154105.1188
Abstract
Genotype evaluation for stability and high yielding in maize is an important factor for boosting productivity and sustainability of maize production. A total of 25 maize genotypes were evaluated over six environments namely Bako (BK), Asosa (AS), Hawasa (HW), Pawe (PW), Jimma (JM) and Arsi-Negele (AN) using randomized complete block design with three replications during 2022 for the objective to identify superior and stable maize genotypes through stability analysis. Combined ANOVA revealed highly significant (p<0.01) difference among genotypes, environments, and genotype by environment interaction (GEI) for studied traits including grain yield (GY). The environment and GEI were found to be the most significant causes of the grain yield (GY) accounted 60.3% and 21.4 % of overall variation, respectively. The sum of the first two principal components of AMMI and GGE biplot explained the GEI variation for GY 74.5% and 78.1%, respectively. The AMMI and GGE biplot analysis depicted some genotypes G20, G25,G2, G17, G21, G13, G9 and G16 gave GY above the mean and less affected by GEI. The polygon view of the GGE biplot showed that the first mega-environment contains four environments BK, PW, AS, and HW with G20, the second and third environment contains JM and AN with G11 and G13 as winner genotypes (vertex), respectively. Environments AS, PW and BK identified as best environments based on its yield, discriminating and representativeness which were close to ideal environments. Genotypes G20 (3XM2110426) identified as ideal and G25 (BH520), G2 (3XM2110423), G17 (BH549), G21 (3XM2110422), G9 (3XM1900467) and G18 (3XM2110424) considered as desirable genotypes based on proximity to ideal genotypes. Therefore, G20 (3XM2110426) and G2 (3XM2110423) are recommended for verification and release after confirming the reliable performance of these genotypes through conducting multiyear evaluation and determining mega-environments for maize production in similar agro-ecologies of Ethiopia.

Keywords

Discriminative
Environment
Genotypes
Selection
Stability
Subjects
  1. Piperno DR, Flannery KV (2001) The earliest archaeological maize (Zea mays L.) from highland Mexico: new accelerator mass spectrometry dates and their implications Proceedings of the National Academy of Sciences.98(4):2101-3. https://doi.org/10.1073/pnas.98.4.2101
  2. FAO, editor. World Food and Agriculture - Statistical Year Book Rome2022.
  3. Agricultural Sample Survey 2021/22 Report On Farm Management Practicies (Private Peasant Holdings, Meher season). : Statistical Bulletin Practices; 2022. 509 p.
  4. Bernardo R. Breeding for quantitative traits in plants: Stemma press Woodbury, MN; 2002.
  5. De Leon N, Jannink JL, Edwards JW, Kaeppler SM (2016) Introduction to a special issue on genotype by environment interaction Crop Science.56(5):2081-9. https://doi.org/10.2135/cropsci2016.07.0002in
  6. Badu-Apraku B, Abubakar AM, Adu GB, Yacoubou AM, Adewale S, Adejumobi, II (2023) Enhancing Genetic Gains in Grain Yield and Efficiency of Testing Sites of Early-Maturing Maize Hybrids under Contrasting Environments Genes (Basel).14(10). https://doi.org/10.3390/genes14101900
  7. Brankovic-Radojcic D, Babic V, Girek Z, Zivanovic T, Radojĉic A, Filipovic M, et al. (2018) Evaluation of maize grain yield and yield stability by AMMI analysis Genetika.50(3):1067-80. https://doi.org/10.2298/gensr1803067b
  8. Getachew G, Abebe B, Chelchisa D, Oli S, Chebsa T, Tefa Z, et al. (2021) Genotype by Environment Interaction by AMMI and GGE Bi-Plot Analysis for Maize (Zea Mays L.) for Transitional High Land Agroecology of Ethiopia Research square:1-15. https://doi.org/10.21203/rs.3.rs-589678/v1
  9. Hongyu K (2018) Adaptability, stability and genotype by environment interaction using the ammi model for multienvironment trials Biodiversidade.
  10. Mengesha W, Menkir A, Meseka S, Bossey B, Afolabi A, Burgueno J, et al. (2019) Factor analysis to investigate genotype and genotype × environment interaction effects on pro-vitamin A content and yield in maize synthetics Euphytica.215(11). https://doi.org/10.1007/s10681-019-2534-y
  11. Wolde L, Keno T, Abebe A, Abakemal D, Terefe W, Negera D (2019) Genotype x environment interaction and stability analysis of grain yield in QPM hybrid varieties Maydica.64(3).
  12. Ouédraogo N, Sawadogo N, Banhoro A, Kouraogo I, Boro O, Sawadogo AP, et al. (2023) Genotype x Environment Interactions and Stability of Grain Yield of Maize Hybrids across Sudanian and Sudano-Sahelian Agro-ecological Zones in Burkina Faso International Journal of Plant & Soil Science.35(18):2169-81. https://doi.org/10.9734/ijpss/2023/v35i183508
  13. Gauch HG (2013) A Simple Protocol for AMMI Analysis of Yield Trials Crop Science.53(5):1860-9. https://doi.org/10.2135/cropsci2013.04.0241
  14. Yan W, Hunt LA, Sheng Q, Szlavnics Z (2000) Cultivar Evaluation and Mega-Environment Investigation Based on the GGE Biplot Crop Sci.40:597–605 https://doi.org/10.2135/cropsci2000.403597x
  15. Yan W, Hunt LA (2001) Interpretation of Genotype by Environment Interaction for Winter Wheat Yield in Ontario Crop Sci.41:19-25. https://doi.org/10.2135/cropsci2001.41119x
  16. Yan W, Kang MS, Ma B, Woods S, Cornelius PL (2007) GGE Biplot vs. AMMI Analysis of Genotype‐by‐Environment Data Crop Science.47(2):643-53. https://doi.org/10.2135/cropsci2006.06.0374
  17. Olivoto T, Lúcio ADC, da Silva JAG, Sari BG, Diel MI (2019) Mean Performance and Stability in Multi‐Environment Trials II: Selection Based on Multiple Traits Agronomy Journal.111(6):2961-9. https://doi.org/10.2134/agronj2019.03.0221
  18. Yan W, Kang MS. GGE biplot analysis: A graphical tool for breeders, geneticists, and agronomists: CRC press; 2002. https://doi.org/10.1201/9781420040371-4
  19. Mebratu A, Wegary D, Mohammed W, Teklewold A, Tarekegne A (2019) Genotype× environment interaction of quality protein maize hybrids under contrasting management conditions in Eastern and Southern Africa Crop Science.59(4):1576-89. https://doi.org/10.2135/cropsci2018.12.0722
  20. Bocianowski J, Nowosad K, Tomkowiak A (2019) Genotype-environment interaction for seed yield of maize hybrids and lines using the AMMI model.
  21. Worku M, Makumbi D, Beyene Y, Das B, Mugo S, Pixley K, et al. (2016) Grain yield performance and flowering synchrony of CIMMYT’s tropical maize (Zea mays L.) parental inbred lines and single crosses Euphytica.211(3):395-409. https://doi.org/10.1007/s10681-016-1758-3
  22. Gemechu Asefa (2022) GGE biplot analysis of genotype by environment interaction and yield stability analysis of Arabica coffee (Coffea arabica L.) diallel genotypes in south western Ethiopia GSJ.10(3):1082-100. https://doi.org/10.11648/j.ajbio.20210903.16
  23. Gauch HG, Piepho HP, Annicchiarico P (2008) Statistical Analysis of Yield Trials by AMMI and GGE: Further Considerations Crop Science.48(3):866-89. https://doi.org/10.2135/cropsci2007.09.0513
  24. Crossa J (1990) Statistical analyses of multilocation trials Advances in agronomy.44:55-85. https://doi.org/10.1016/s0065-2113(08)60818-4
  25. Wolde L, Keno T, Tadesse B, Bogale G, Abebe B (2018) Mega-environment targeting of maize varieties using Ammi and GGE bi-plot analysis in Ethiopia Ethiopian Journal of Agricultural Sciences.28(2):65-84.
  26. Vargas-Hernández M, Crossa J (2000) The AMMI analysis and graphing the biplot.
  27. Purchase JL. Parametric analysis to describe genotype x environment interaction and yield stability in winter wheat (1997). University of the Free State.Page
  28. Akter A, Jamil H, Umma K, Islam M, Hossain K, Mamunur R (2014) AMMI biplot analysis for stability of grain yield in hybrid rice (Oryza sativa L.) J Rice Res.2(2):126. https://doi.org/10.4172/jrr.1000126
  29. Miranda GV, Souza LVd, Guimarães LJM, Namorato H, Oliveira LR, Soares MO (2009) Multivariate analyses of genotype x environment interaction of popcorn Pesquisa Agropecuária Brasileira.44:45-50. https://doi.org/10.1590/s0100-204x2009000100007
  30. Silveira LCId, Kist V, Paula TOMd, Barbosa MHP, Peternelli LA, Daros E (2013) AMMI analysis to evaluate the adaptability and phenotypic stability of sugarcane genotypes Scientia Agricola.70:27-32. https://doi.org/10.1590/s0103-90162013000100005
  31. Osiru M, Olanya O, Adipala E, Kapinga R, Lemaga B (2009) Yield Stability Analysis of'Ipomoea batatus' L. Cultivars in Diverse Environments Australian Journal of Crop Science.3(4):213-20. https://doi.org/10.1111/j.1439-0434.2008.01457.x
  32. Gauch Jr HG, Zobel RW (1997) Identifying mega‐environments and targeting genotypes Crop science.37(2):311-26. https://doi.org/10.2135/cropsci1997.0011183x003700020002x
  33. Oladosu Y, Rafii MY, Abdullah N, Magaji U, Miah G, Hussin G, et al. (2017) Genotype× Environment interaction and stability analyses of yield and yield components of established and mutant rice genotypes tested in multiple locations in Malaysia Acta Agriculturae Scandinavica, Section B—Soil & Plant Science.67(7):590-606. https://doi.org/10.1080/09064710.2017.1321138
  34. Yan W, Tinker NA (2006) Biplot analysis of multi-environment trial data: Principles and applications Canadian journal of plant science.86(3):623-45. https://doi.org/10.4141/p05-169
  35. 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):325-37. https://doi.org/10.47115/bsagriculture.1069462
  36. Farshadfar E, Mohammadi R, Aghaee M, Vaisi Z (2012) GGE biplot analysis of genotype x environment interaction in wheat-barley disomic addition lines Australian Journal of Crop Science.6(6):1074-9. https://doi.org/10.1556/aagr.61.2013.4.2
  37. Yan W, Kang M (2002) GGE biplot analysis: A graphical tool for breeders, geneticists, and agronomists. https://doi.org/10.1201/9781420040371
  38. Mafouasson HNA, Gracen V, Yeboah MA, Ntsomboh-Ntsefong G, Tandzi LN, Mutengwa CS (2018) Genotype-by-Environment Interaction and Yield Stability of Maize Single Cross Hybrids Developed from Tropical Inbred Lines Agronomy.8(5). https://doi.org/10.3390/agronomy8050062
  39. Mushayi M, Shimelis H, Derera J, Shayanowako AIT, Mathew I (2020) Multi-environmental evaluation of maize hybrids developed from tropical and temperate lines Euphytica.216(5). https://doi.org/10.1007/s10681-020-02618-6
  40. Ram K, Munjal R, Kesh H, Resh S, Kumari A (2020) AMMI and GGE biplot analysis for yield stability of wheat genotypes under drought and high temperature stress International Journal of Current Microbiology and Applied Sciences.9(5):377-89. https://doi.org/10.20546/ijcmas.2020.905.043
Al-Qadisiyah Journal For Agriculture Sciences
Volume 14, Issue 2
December 2024
Page 44-58

  • Receive Date 03 October 2024
  • Accept Date 05 December 2024