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Adaptation Study of Improved Soya Bean (Glycine max (L.) Varieties in East Shewa Zone, Oramia, Ethiopia

Received: 9 August 2022    Accepted: 13 September 2022    Published: 28 September 2022
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Abstract

The experiment was conducted at Adami Tulu Agricultural Research Center (ATARC), Lume and Dugda Districts during 2019 and 2020 main cropping seasons with the objective to identify adaptable and high yielder soyabean variety/ies for East Shewa Zone and similar agro ecologies. Ten released soyabean varieties were used as a planting material. The experiment was laid down in Randomized Complete Block Design (RCBD) with three replications. The plot size was 3m × 3 m (9 m2) having 5 rows and a spacing of 0.60 m between rows and 0.50 m between replications, 1 m between blocks. The genotype and environment main effects and genotype x environment interaction effect were significant on soyabean varieties. AMMI model shows that environment accounted 47.68%, GXE 20.56%, genotype 15.22% of the total variation. The high percentage of environment is an indication that the major factor that influence yield performance of soybean is the environment. The first two IPCAs are the most accurate model that could be predicted the stability of the genotype and explained by IPCA-I (30.34%) and IPCA-II (25.83%) of GEI. According, to stability parameters (ASV, and GGE- Biplot) and mean yield results revealed that Gozella and Davis varieties are the most stable varieties across test locations. Therefore, Gozella and Davis were recommended for the study area and similar agro-ecologies.

Published in Science Research (Volume 10, Issue 5)
DOI 10.11648/j.sr.20221005.11
Page(s) 108-113
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Soyabean, Genotype by Environment Interaction, Stability, AMMI, GGE-Biplot

References
[1] Arega A, Dabessa A, Tola M, Dabala Ch. 2018. Genotype and genotype by environment interaction and grain yield stability of medium maturity groups of soybean [Glycine max (L.) Merrill] varieties in Western Oromia, Ethiopia. Afr. J. Plant Sci. DOI: 10.5897/AJPS2018.1674.
[2] Asrat Feleke, 1965. Progress Report on Cereals, Pulses and Oilseeds Research, Branch Experiment Station Debre Zeit Ethiopia.
[3] Dabessa A, Alemu B, Abebe Z, Lule D 2016. Genotype by Environment Interaction and Kernel Yield Stability of Groundnut (Arachis hypogaea L.) Varieties in Western Oromia, Ethiopia. Journal of Agriculture and Crops 2 (11): 113-120.
[4] Dugje, I. Y., Omoigui, L. O., Ekeleme, F., Bandyopaolhyay, Lava Kumar, R. P. and Kamara, A. Y. 2009. Guide to soybean production in northern Nigeria. IITA, Ibadan. 21pp.
[5] Farshadfar, E. 2008. Incorporation of AMMI stability value and grain yield in a single nonparametric index (GSI) in bread wheat. Pak J Biol Sci, 11 (4): 1791-1796.
[6] Farshadfar, E., Mohammadi, R., Aghaee, M. and Vaisi, Z. 2012. GGE biplot analysis of genotype × environment interaction in wheat-barley disomic addition lines. Australia Journal of Crop Sciences 6: 1074-1079.
[7] Gabriel, K. R. 1971. The biplot graphic display of matrices with application to principal component analysis. Biometrika, 58, 453–467. doi: 10.1093/biomet58.3.453.
[8] Gauch HG, Zobel RW, 1992. AMMI analysis of yield trials. In: Genotype by environment interaction. pp. 85-122 (Kang, M. and Gauch, H. eds.). Boca Raton. CRC press, New York.
[9] Gauch, H. G. 2006. Statistical analysis of yield trials by AMMI and GGE. Crop Sciences. 46: 1488-1500.
[10] Kaya, Y., Akcura, M. and Taner, S. 2006. GGE-bi-plot analysis of multi- environment yield trials in bread wheat Turkish Journal of Agriculture 30: 325-337.
[11] Purchase, J. L., Hatting H., and Vandenventer, C. S. 1997. Genotype x environment interaction of winter wheat in South Africa: II. Stability analysis of yield performance. South Afr J Plant Soil, 17: 101-107.
[12] Tolessa TT, Gela TS 2014. Sites regression GGE biplot analysis of haricot bean (Phaseolus vulgaris L.) genotypes in three contrasting environments. World Journal of Agricultural Research 2: 228-236.
[13] Worku, M. and Astatkie, T., 2011. Row and plant spacing effects on yield and yield components of soya bean varieties under hot humid tropical environment of Ethiopia. Journal of Agronomy and Crop Science, 197 (1), pp. 67-74.
[14] Yan W and Hunt LA. 2001. Interpretation of genotype x environment interaction for winter wheat yield in Ontario. Crop Sci 41: 19-25.
[15] Yan, W., Hunt, L. A., Sheng, Q. and Szlavnics, Z. 2000. Cultivar evaluation and mega environment investigation based on the GGE biplot. Crop Science, 40: 597-605.
[16] Yazici N, Bilir N 2017. Aspectual Fertility Variation and Its Effect on Gene Diversity of Seeds in Natural Stands of Taurus Cedar (Cedrus libani A. Rich.). International Journal of genomics 2960624: 1-5.
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  • APA Style

    Temesgen Dinsa, Urgaya Balcha. (2022). Adaptation Study of Improved Soya Bean (Glycine max (L.) Varieties in East Shewa Zone, Oramia, Ethiopia. Science Research, 10(5), 108-113. https://doi.org/10.11648/j.sr.20221005.11

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    ACS Style

    Temesgen Dinsa; Urgaya Balcha. Adaptation Study of Improved Soya Bean (Glycine max (L.) Varieties in East Shewa Zone, Oramia, Ethiopia. Sci. Res. 2022, 10(5), 108-113. doi: 10.11648/j.sr.20221005.11

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    AMA Style

    Temesgen Dinsa, Urgaya Balcha. Adaptation Study of Improved Soya Bean (Glycine max (L.) Varieties in East Shewa Zone, Oramia, Ethiopia. Sci Res. 2022;10(5):108-113. doi: 10.11648/j.sr.20221005.11

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  • @article{10.11648/j.sr.20221005.11,
      author = {Temesgen Dinsa and Urgaya Balcha},
      title = {Adaptation Study of Improved Soya Bean (Glycine max (L.) Varieties in East Shewa Zone, Oramia, Ethiopia},
      journal = {Science Research},
      volume = {10},
      number = {5},
      pages = {108-113},
      doi = {10.11648/j.sr.20221005.11},
      url = {https://doi.org/10.11648/j.sr.20221005.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sr.20221005.11},
      abstract = {The experiment was conducted at Adami Tulu Agricultural Research Center (ATARC), Lume and Dugda Districts during 2019 and 2020 main cropping seasons with the objective to identify adaptable and high yielder soyabean variety/ies for East Shewa Zone and similar agro ecologies. Ten released soyabean varieties were used as a planting material. The experiment was laid down in Randomized Complete Block Design (RCBD) with three replications. The plot size was 3m × 3 m (9 m2) having 5 rows and a spacing of 0.60 m between rows and 0.50 m between replications, 1 m between blocks. The genotype and environment main effects and genotype x environment interaction effect were significant on soyabean varieties. AMMI model shows that environment accounted 47.68%, GXE 20.56%, genotype 15.22% of the total variation. The high percentage of environment is an indication that the major factor that influence yield performance of soybean is the environment. The first two IPCAs are the most accurate model that could be predicted the stability of the genotype and explained by IPCA-I (30.34%) and IPCA-II (25.83%) of GEI. According, to stability parameters (ASV, and GGE- Biplot) and mean yield results revealed that Gozella and Davis varieties are the most stable varieties across test locations. Therefore, Gozella and Davis were recommended for the study area and similar agro-ecologies.},
     year = {2022}
    }
    

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  • TY  - JOUR
    T1  - Adaptation Study of Improved Soya Bean (Glycine max (L.) Varieties in East Shewa Zone, Oramia, Ethiopia
    AU  - Temesgen Dinsa
    AU  - Urgaya Balcha
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    SN  - 2329-0927
    UR  - https://doi.org/10.11648/j.sr.20221005.11
    AB  - The experiment was conducted at Adami Tulu Agricultural Research Center (ATARC), Lume and Dugda Districts during 2019 and 2020 main cropping seasons with the objective to identify adaptable and high yielder soyabean variety/ies for East Shewa Zone and similar agro ecologies. Ten released soyabean varieties were used as a planting material. The experiment was laid down in Randomized Complete Block Design (RCBD) with three replications. The plot size was 3m × 3 m (9 m2) having 5 rows and a spacing of 0.60 m between rows and 0.50 m between replications, 1 m between blocks. The genotype and environment main effects and genotype x environment interaction effect were significant on soyabean varieties. AMMI model shows that environment accounted 47.68%, GXE 20.56%, genotype 15.22% of the total variation. The high percentage of environment is an indication that the major factor that influence yield performance of soybean is the environment. The first two IPCAs are the most accurate model that could be predicted the stability of the genotype and explained by IPCA-I (30.34%) and IPCA-II (25.83%) of GEI. According, to stability parameters (ASV, and GGE- Biplot) and mean yield results revealed that Gozella and Davis varieties are the most stable varieties across test locations. Therefore, Gozella and Davis were recommended for the study area and similar agro-ecologies.
    VL  - 10
    IS  - 5
    ER  - 

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Author Information
  • Adami Tulu Agricultural Research Center, Batu, Ethiopia

  • Adami Tulu Agricultural Research Center, Batu, Ethiopia

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