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Genetic Variability of Soybean (Glycine Max (L) Merrill) Genotypes Under Moisture Stress Areas of Ethiopia

Received: 17 November 2021    Accepted: 9 December 2021    Published: 24 December 2021
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Abstract

Characterization and evaluation soybean genotypes for different traits of interest is important to facilitate the breeding program. The study was conducted using 25 early maturing soybean genotypes at Mehoni, Humera, Jinka, Tiro-afeta, and Gofa, Ethiopia during 2018 main cropping seasons. The objective of the experiment was to estimate genetic variability of these breeding materials. The genotypes were planted using 5x5 simple lattice design and managed as per the soybean recommended agronomic production practices. Data on important traits like days flowering (DTF), days to maturity (DTM), plant height (PH), number of pod per plant (NPP), number of seed per plant (NSP), hundred seed weight (HSW) and yield per hectare (YLD) was recorded. The pooled analysis of variance revealed highly significant difference among locations (L) and genotypes (G). The maximum yield was recorded from genotype; JIM-ALM/CRFD-15-SA (2.30 t/ha) followed by PI417129B (2.27 t/ha), with the yield advantage of (27% and 37%) and (25% and 36%) relative to the checks varieties; Gazale (1.81t/ha) and Nova (1.67t/ha), respectively. Based on earliness of the genotypes, all the tested genotypes were found early with the rage of 86 to 105 days. High phenotypic (PCV) and high genotypic coefficients of variation (GCV) were recorded for DTF (148.38% and 142.29%), PH (97.64% and 95.13%), NPP (56.68% and 47.63%), NSP (136.52% and 111.43%), HSW (55.92% and 45.45%) and YLD (133.80% and 92.09%), respectively. While, high PCV (20.78%) with moderate GCV (15.90%) was recorded from DTM. However, the difference between PCV with the corresponding GCV values was relatively higher for NSP and YLD, suggesting high influence of the environment on these traits. High heritability estimates was recorded for DTF (91.95%), NPP (70.62%), NSP (66.62%), and HSW (66.07%), while the remaining showed moderate heritability. High genetic advance as percent of mean (GAM) was found for all the traits studied. Whereas, combined high GCV, high heritability and high GAM were recorded for DTF (142.29%, 91.95% and 281.48%), PH (95.23%, 95.23% and 191.62%), NPP (47.63%, 70.62% and 82.57%), NSP (111.43%, 66.43% and 187.63%) and HSW (45.45%, 66.07% and 76.21%), respectively, which means these traits are controlled more of by additive genes. Generally, the existences of sufficient variability among the evaluated materials create immense opportunity to bring considerable improvement through selection and cross breeding in soybean breeding program.

Published in Journal of Plant Sciences (Volume 9, Issue 6)
DOI 10.11648/j.jps.20210906.17
Page(s) 316-322
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), 2021. Published by Science Publishing Group

Keywords

Soybean, Physiological Maturity, Moister Stress, Heritability, Genetic Advance

References
[1] SoyStats (2019) International: World Oilseed Production. http://soystats.com/international-world-oilseed production. Accessed 12 May 2020.
[2] Wilson RF (2004) Seed composition. In: Boerma RH, Specht JE (eds) Soybeans: improvement, production, and uses, 3rd edn. American Society of Agronomy, Madison, pp 621–669.
[3] Singh, P., Kumar, R., Sabapathy, S. N. & Bawa, A. S. 2008. Functional and edible uses of soyprotein products. Reviews in Food Science and Food Safety, 7: 14–28.
[4] Fekadu Gurmu, Hussein Mohammed and Getnet Alemaw, 2009. Genotype X environment interactions and stability of soybean for grain yield and nutrition quality. African Crop Science Journal 17: 87-99.
[5] Fehr WR, Caviness CE (1977) Stages of soybean development. Iowa State University of Science and Technology, Ames, pp 1–11.
[6] Ganesan K, Xu B., 2017. A critical review on polyphenols and health benefits of black soybeans. Nutrients. 9 (5): 455. doi: 10.3390/nu9050455.
[7] Clarke E. J. and J. Wiseman, 2000. Developments in plant breeding for improved nutritionalquality of soybeans. Protein and amino acid content. Journal of Agricultural Science, 134: 111-124.
[8] Selle PH, de Paula Dorigam JC, Lemme A, Chrystal PV, Liu SY, 2020. Synthetic and crystalline amino acids: alternatives to soybean meal in chicken-meat production. Animal 10: 729–738.
[9] Graham, P. H. and C. P. Vance, 2003. Legumes: importance and constraints to greater use. Plant Physiology, 131: 872–877.
[10] FAOSTAT, 2019. Food and Agriculture Organization of the United Nations. http://Faostat.fao.org. Accessed 14 May 2020.
[11] Cornelius, M. and P. Goldsmith, 2019. The State of Soybean in Africa: Soybean Yield in Africa., Department of Agricultural and Consumer Economics, University of Illinois at Urbana Champaign. farmdoc daily 9: 221.
[12] Asrat Feleke, 1965. Progress Report on Cereals, Pulses and Oilseeds Research, Branch Experiment Station DebreZeit Ethiopia.
[13] Ministry of Agriculture (MoA), 2018. Plant variety release, protection and seed quality control directorate. Crop variety registration. Addis Ababa, Ethiopia, Issue No. 21.
[14] Birhanu, Yalew M., and Adam B., 2018. “Analysis of Cost and Return of Soybean Production under Small holder Farmers in Pawe District, North Western Ethiopia at Ethiopian Institute of Agricultural Research”.
[15] CSA (Central Statistical Authority of Ethiopia), 2020. Area and production of major crops, Central Statistics Agency (CSA), Addis Ababa, Ethiopia.
[16] Levitt, J. 1980. Stress terminology. See Ref. 80. pp. 437-39.
[17] Boyer. J. S., 1982. Plant productivity and environment. Science 218: 443-48.
[18] Johnson, H. W, R. F. Robinson and R. F. Comstock, 1955. Estimates of genetic and environmental variability in Soya bean. Agron. J. 47: 314-318.
[19] Allard, R. W., 1960. Principles of Plant Breeding. John Wileyand Sons. Inc. New York.
[20] Abush Tesfaye, M. Githiri, J. Derera and Tolessa Debele., 2017. Genetic Variability in Soybean (Glycine max L.) for Low Soil Phosphorus Tolerance. Ethiop. J. Agric. Sci. 27: 1-15.
[21] Mesfin Hailemariam, 2018. Path analysis, Genetic variability and Correlation studies for Soybean (Glycine max (L.) Merill) for grain yield and Secondary traits at Asosa, Western Ethiopia. Greener Journal of Plant Breeding and Crop Science 6: 35-46.
[22] Abady, S. F. Merkeb and Z. Dilnesaw, 2013. Heritability and path-coefficient analysis in soybean [Glycine max (L.) Merrill.] genotypes at Pawe, North Western Ethiopia. Journal of Environmental Science and Water Resources 2: 270-276.
[23] Yechalew S., Andargachew G., Abush T., 2019. Contribution of Morphological Traits to the Total Variability in Soybean (Glycine max (L.) Merr.) Genotypes in Western Parts of Ethiopia. Acad. Res. J. Agri. Sci. Res. 7 (7): 408-413.
[24] Neelima, G., S. P. Mehtre and G. W. Narkhede, 2018. Genetic Variability, Heritability and Genetic Advance in Soybean. Int. J. Pure App. Biosci. 6: 1011-1017.
[25] Deshmuk SN, Basu MS, Reddy PS (1986). Genetic variability, character association and path coefficient analysis of quantitative traits in viginia bunch varieties of groundnut. Indian J. Agric. Sci. 56: 515-518.
[26] Akinwale, M. G., G. Gregorio, F. Nwilene, B. O. Akinyele, S. A. Ogunbayo, and A. C. Odiyi, 2011. Heritability and correlation coefficient analysis for yield and its components in rice (Oryza sativa L.). African Journal of plant science 5: 207-212.
[27] Aditya, J. P., P. Bhartiya and A. Bhartiya. 2011. Genetic variability, heritability and character association for yield and component characters in soybean [Glycine max L. Merrill]. Journal of Central European Agriculture 12: 27.
[28] Panse, VG., 1957. Genetics of quantitative character in relation to plant breeding. Indian Journal of Genetics, 17: 317-28.
[29] Abate, A. and Mekbib, F., Fikre, A. and Ahmed, S., 2018. Genetic Variability and Heritability in Ethiopian Grasspea (lathyrussativus l.) Accessions. Ethiopian Journal of Crop Science, 6 (2). pp. 79-94. ISSN 2072- 8506.
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    Masreshaw Yirga, Yechalew Sileshi, Mesfin Hailemariam. (2021). Genetic Variability of Soybean (Glycine Max (L) Merrill) Genotypes Under Moisture Stress Areas of Ethiopia. Journal of Plant Sciences, 9(6), 316-322. https://doi.org/10.11648/j.jps.20210906.17

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    Masreshaw Yirga; Yechalew Sileshi; Mesfin Hailemariam. Genetic Variability of Soybean (Glycine Max (L) Merrill) Genotypes Under Moisture Stress Areas of Ethiopia. J. Plant Sci. 2021, 9(6), 316-322. doi: 10.11648/j.jps.20210906.17

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    AMA Style

    Masreshaw Yirga, Yechalew Sileshi, Mesfin Hailemariam. Genetic Variability of Soybean (Glycine Max (L) Merrill) Genotypes Under Moisture Stress Areas of Ethiopia. J Plant Sci. 2021;9(6):316-322. doi: 10.11648/j.jps.20210906.17

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  • @article{10.11648/j.jps.20210906.17,
      author = {Masreshaw Yirga and Yechalew Sileshi and Mesfin Hailemariam},
      title = {Genetic Variability of Soybean (Glycine Max (L) Merrill) Genotypes Under Moisture Stress Areas of Ethiopia},
      journal = {Journal of Plant Sciences},
      volume = {9},
      number = {6},
      pages = {316-322},
      doi = {10.11648/j.jps.20210906.17},
      url = {https://doi.org/10.11648/j.jps.20210906.17},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jps.20210906.17},
      abstract = {Characterization and evaluation soybean genotypes for different traits of interest is important to facilitate the breeding program. The study was conducted using 25 early maturing soybean genotypes at Mehoni, Humera, Jinka, Tiro-afeta, and Gofa, Ethiopia during 2018 main cropping seasons. The objective of the experiment was to estimate genetic variability of these breeding materials. The genotypes were planted using 5x5 simple lattice design and managed as per the soybean recommended agronomic production practices. Data on important traits like days flowering (DTF), days to maturity (DTM), plant height (PH), number of pod per plant (NPP), number of seed per plant (NSP), hundred seed weight (HSW) and yield per hectare (YLD) was recorded. The pooled analysis of variance revealed highly significant difference among locations (L) and genotypes (G). The maximum yield was recorded from genotype; JIM-ALM/CRFD-15-SA (2.30 t/ha) followed by PI417129B (2.27 t/ha), with the yield advantage of (27% and 37%) and (25% and 36%) relative to the checks varieties; Gazale (1.81t/ha) and Nova (1.67t/ha), respectively. Based on earliness of the genotypes, all the tested genotypes were found early with the rage of 86 to 105 days. High phenotypic (PCV) and high genotypic coefficients of variation (GCV) were recorded for DTF (148.38% and 142.29%), PH (97.64% and 95.13%), NPP (56.68% and 47.63%), NSP (136.52% and 111.43%), HSW (55.92% and 45.45%) and YLD (133.80% and 92.09%), respectively. While, high PCV (20.78%) with moderate GCV (15.90%) was recorded from DTM. However, the difference between PCV with the corresponding GCV values was relatively higher for NSP and YLD, suggesting high influence of the environment on these traits. High heritability estimates was recorded for DTF (91.95%), NPP (70.62%), NSP (66.62%), and HSW (66.07%), while the remaining showed moderate heritability. High genetic advance as percent of mean (GAM) was found for all the traits studied. Whereas, combined high GCV, high heritability and high GAM were recorded for DTF (142.29%, 91.95% and 281.48%), PH (95.23%, 95.23% and 191.62%), NPP (47.63%, 70.62% and 82.57%), NSP (111.43%, 66.43% and 187.63%) and HSW (45.45%, 66.07% and 76.21%), respectively, which means these traits are controlled more of by additive genes. Generally, the existences of sufficient variability among the evaluated materials create immense opportunity to bring considerable improvement through selection and cross breeding in soybean breeding program.},
     year = {2021}
    }
    

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  • TY  - JOUR
    T1  - Genetic Variability of Soybean (Glycine Max (L) Merrill) Genotypes Under Moisture Stress Areas of Ethiopia
    AU  - Masreshaw Yirga
    AU  - Yechalew Sileshi
    AU  - Mesfin Hailemariam
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    PY  - 2021
    N1  - https://doi.org/10.11648/j.jps.20210906.17
    DO  - 10.11648/j.jps.20210906.17
    T2  - Journal of Plant Sciences
    JF  - Journal of Plant Sciences
    JO  - Journal of Plant Sciences
    SP  - 316
    EP  - 322
    PB  - Science Publishing Group
    SN  - 2331-0731
    UR  - https://doi.org/10.11648/j.jps.20210906.17
    AB  - Characterization and evaluation soybean genotypes for different traits of interest is important to facilitate the breeding program. The study was conducted using 25 early maturing soybean genotypes at Mehoni, Humera, Jinka, Tiro-afeta, and Gofa, Ethiopia during 2018 main cropping seasons. The objective of the experiment was to estimate genetic variability of these breeding materials. The genotypes were planted using 5x5 simple lattice design and managed as per the soybean recommended agronomic production practices. Data on important traits like days flowering (DTF), days to maturity (DTM), plant height (PH), number of pod per plant (NPP), number of seed per plant (NSP), hundred seed weight (HSW) and yield per hectare (YLD) was recorded. The pooled analysis of variance revealed highly significant difference among locations (L) and genotypes (G). The maximum yield was recorded from genotype; JIM-ALM/CRFD-15-SA (2.30 t/ha) followed by PI417129B (2.27 t/ha), with the yield advantage of (27% and 37%) and (25% and 36%) relative to the checks varieties; Gazale (1.81t/ha) and Nova (1.67t/ha), respectively. Based on earliness of the genotypes, all the tested genotypes were found early with the rage of 86 to 105 days. High phenotypic (PCV) and high genotypic coefficients of variation (GCV) were recorded for DTF (148.38% and 142.29%), PH (97.64% and 95.13%), NPP (56.68% and 47.63%), NSP (136.52% and 111.43%), HSW (55.92% and 45.45%) and YLD (133.80% and 92.09%), respectively. While, high PCV (20.78%) with moderate GCV (15.90%) was recorded from DTM. However, the difference between PCV with the corresponding GCV values was relatively higher for NSP and YLD, suggesting high influence of the environment on these traits. High heritability estimates was recorded for DTF (91.95%), NPP (70.62%), NSP (66.62%), and HSW (66.07%), while the remaining showed moderate heritability. High genetic advance as percent of mean (GAM) was found for all the traits studied. Whereas, combined high GCV, high heritability and high GAM were recorded for DTF (142.29%, 91.95% and 281.48%), PH (95.23%, 95.23% and 191.62%), NPP (47.63%, 70.62% and 82.57%), NSP (111.43%, 66.43% and 187.63%) and HSW (45.45%, 66.07% and 76.21%), respectively, which means these traits are controlled more of by additive genes. Generally, the existences of sufficient variability among the evaluated materials create immense opportunity to bring considerable improvement through selection and cross breeding in soybean breeding program.
    VL  - 9
    IS  - 6
    ER  - 

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Author Information
  • Ethiopian Institutes of Agricultural Research, Jimma Agricultural Research Center, Jimma, Ethiopia

  • Ethiopian Institutes of Agricultural Research, Jimma Agricultural Research Center, Jimma, Ethiopia

  • Ethiopian Institutes of Agricultural Research, Jimma Agricultural Research Center, Jimma, Ethiopia

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