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Evaluation of Food Barley (Hordeum vulgare L.) Varieties at Highlands of Southwestern Part of Ethiopia Using AMMI and GGE Biplot Stability Models

Received: 13 November 2023    Accepted: 30 November 2023    Published: 8 December 2023
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Abstract

A multi location trial was conducted across the highlands of Southwestern (SW) Ethiopia from 2020 to 2022 during main cropping seasons to evaluate grain yield and yield related traits of food barley varieties across the different locations to identify and recommend high yielding and stable food barley varieties to farmers for large scale planting using AMMI and GGE biplot models. A total of eight food barley varieties were obtained from the Sinana Agricultural Research Center (SARC) for use in this study. Varieties were evaluated in three environments, over three growing seasons. The experiments were conducted at Dedo, Yem and Gechi districts of SW part of Ethiopia during the main cropping seasons. The experiment was laid out in RCBD with three replications. The experimental plot for each variety consisted of six rows of 2.5m length and rows were spaced 20cm apart. Spacing between rows, plots and replications 25cm, 30cm and 1m respectively. Data for all relevant agronomic traits were collected, but only plot yield data converted to t/ha was subjected to statistical analysis. The combined ANOVA showed highly significant differences (P<0.001) among E, G and GEI for grain yield. The environmental variance was more accountable (68.2%) to the total variance as compared to the genetic variance (3.16%) and the interaction variance (19.13%) for grain yield. Dedo 2022 was the highest yielding (4.1 t/ha) while Gechi 2022 was the lowest yielding (1.5 t/ha) environment. The mean grain yield of the varieties across eight environments was 3 t/ha. The GGE biplot identified two barley growing mega-environments. The first mega environment consisted of environments E5, E8, E1 with a vertex genotype T4. E6, E4, E3, E2 and E7 were found in the second mega environment with the winning genotype of T8. It was also noted that no mega-environments fell into sectors where genotype T2 and T7 were the vertex genotypes, did not fit in any of the mega-environments. According to both AMMI and GGE biplot analysis, food barley varieties T3, T7 and T5 were found to be benchmarks/ideal genotypes and could be used as checks to evaluate the performance of other genotypes and also can be recommended for wider cultivation in the highland environments of Southwestern Ethiopia.

Published in International Journal of Genetics and Genomics (Volume 11, Issue 4)
DOI 10.11648/j.ijgg.20231104.13
Page(s) 126-132
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

AMMI, Food Barley Varieties, GGE Biplot, Southwestern, Stability

References
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[5] Berhane L., Hailu G. and Fekadu A., 1996. Barley Production and Research. pp 1-8. In: Hailu Gebre and Joob Van luer (eds). Barley Research in Ethiopia: Past work and Future Prospects. Proceedings of the First Barley Research Review Workshop 16-19,
[6] Gauch, H. G., Jr., and Zobel, R. W. 1996. AMMI analysis of yield trials. In “Genotype-by-environment interaction” (M. S. Kang and H. G. Gauch, Jr., eds.), pp. 85-122. CRC Press, Boca Raton, FL.
[7] Becker, H. C. 1981. Correlations among some Statistical Measures of Phenotypic Stability. Euphytica, 30, 835-840.
[8] Gauch, H. G. 1998. MATMODEL Version 2.1: AMMI and related analyses for two-way data matrices. Microcomputer Power, Ith- aca, NY.
[9] Yan, W., L. A. Hunt, Q. Sheng and Z. Szlavnics, 2000. Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Sci., 40: 597-605.
[10] Gauch HG. 1992. Statistical analysis of regional trials. AMMI analysis of factorial design. 1st edn. Elsevier, New York.
[11] Yan, W. and N. A. Tinker, 2006. Biplot analysis of multi-environment trial data: Principles and applications. Can. J. Plant Sci., 86: 623-645.
[12] Farshadfar E. and Sutka J. 2003. Locating QTLs controlling adaptation in wheat using AMMI model. Cereal Res Commun 31: 249-254.
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[19] Gadissa. A, Alemu D, Tafesse S. Negash G, Abebe D., Ruth D, Demeke Z., Habtemariam Z., Dawit A., Bayissa and Abebe G. 2020. Performance Evaluation and yield stability of Advanced Bread wheat genotypes in Ethiopia. Results of crop improvement and management research for 2019/20.
[20] Amare, K. and Tamado, T. 2014. Genotype by Environment interaction and stability of pod yield of elite breeding lines of groundnut (Arachis hypogaea L.) in Eastern Ethiopia. Star Journal, 3 (1): 43-46.
[21] Temesgen B, Sintayew A & Zerihun T. 2015. Genotype X environment interaction and yield stability of bread wheat (Triticum Eastivum L.) genotype in Ethiopia using the AMMI Analysis. J. Bio, Agri and Healthcare, 5 (11): 129-139.
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[23] 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: 1074-1079.
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    Belete, T. (2023). Evaluation of Food Barley (Hordeum vulgare L.) Varieties at Highlands of Southwestern Part of Ethiopia Using AMMI and GGE Biplot Stability Models. International Journal of Genetics and Genomics, 11(4), 126-132. https://doi.org/10.11648/j.ijgg.20231104.13

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    ACS Style

    Belete, T. Evaluation of Food Barley (Hordeum vulgare L.) Varieties at Highlands of Southwestern Part of Ethiopia Using AMMI and GGE Biplot Stability Models. Int. J. Genet. Genomics 2023, 11(4), 126-132. doi: 10.11648/j.ijgg.20231104.13

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    AMA Style

    Belete T. Evaluation of Food Barley (Hordeum vulgare L.) Varieties at Highlands of Southwestern Part of Ethiopia Using AMMI and GGE Biplot Stability Models. Int J Genet Genomics. 2023;11(4):126-132. doi: 10.11648/j.ijgg.20231104.13

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  • @article{10.11648/j.ijgg.20231104.13,
      author = {Tegegn Belete},
      title = {Evaluation of Food Barley (Hordeum vulgare L.) Varieties at Highlands of Southwestern Part of Ethiopia Using AMMI and GGE Biplot Stability Models},
      journal = {International Journal of Genetics and Genomics},
      volume = {11},
      number = {4},
      pages = {126-132},
      doi = {10.11648/j.ijgg.20231104.13},
      url = {https://doi.org/10.11648/j.ijgg.20231104.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijgg.20231104.13},
      abstract = {A multi location trial was conducted across the highlands of Southwestern (SW) Ethiopia from 2020 to 2022 during main cropping seasons to evaluate grain yield and yield related traits of food barley varieties across the different locations to identify and recommend high yielding and stable food barley varieties to farmers for large scale planting using AMMI and GGE biplot models. A total of eight food barley varieties were obtained from the Sinana Agricultural Research Center (SARC) for use in this study. Varieties were evaluated in three environments, over three growing seasons. The experiments were conducted at Dedo, Yem and Gechi districts of SW part of Ethiopia during the main cropping seasons. The experiment was laid out in RCBD with three replications. The experimental plot for each variety consisted of six rows of 2.5m length and rows were spaced 20cm apart. Spacing between rows, plots and replications 25cm, 30cm and 1m respectively. Data for all relevant agronomic traits were collected, but only plot yield data converted to t/ha was subjected to statistical analysis. The combined ANOVA showed highly significant differences (P<0.001) among E, G and GEI for grain yield. The environmental variance was more accountable (68.2%) to the total variance as compared to the genetic variance (3.16%) and the interaction variance (19.13%) for grain yield. Dedo 2022 was the highest yielding (4.1 t/ha) while Gechi 2022 was the lowest yielding (1.5 t/ha) environment. The mean grain yield of the varieties across eight environments was 3 t/ha. The GGE biplot identified two barley growing mega-environments. The first mega environment consisted of environments E5, E8, E1 with a vertex genotype T4. E6, E4, E3, E2 and E7 were found in the second mega environment with the winning genotype of T8. It was also noted that no mega-environments fell into sectors where genotype T2 and T7 were the vertex genotypes, did not fit in any of the mega-environments. According to both AMMI and GGE biplot analysis, food barley varieties T3, T7 and T5 were found to be benchmarks/ideal genotypes and could be used as checks to evaluate the performance of other genotypes and also can be recommended for wider cultivation in the highland environments of Southwestern Ethiopia.
    },
     year = {2023}
    }
    

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    AB  - A multi location trial was conducted across the highlands of Southwestern (SW) Ethiopia from 2020 to 2022 during main cropping seasons to evaluate grain yield and yield related traits of food barley varieties across the different locations to identify and recommend high yielding and stable food barley varieties to farmers for large scale planting using AMMI and GGE biplot models. A total of eight food barley varieties were obtained from the Sinana Agricultural Research Center (SARC) for use in this study. Varieties were evaluated in three environments, over three growing seasons. The experiments were conducted at Dedo, Yem and Gechi districts of SW part of Ethiopia during the main cropping seasons. The experiment was laid out in RCBD with three replications. The experimental plot for each variety consisted of six rows of 2.5m length and rows were spaced 20cm apart. Spacing between rows, plots and replications 25cm, 30cm and 1m respectively. Data for all relevant agronomic traits were collected, but only plot yield data converted to t/ha was subjected to statistical analysis. The combined ANOVA showed highly significant differences (P<0.001) among E, G and GEI for grain yield. The environmental variance was more accountable (68.2%) to the total variance as compared to the genetic variance (3.16%) and the interaction variance (19.13%) for grain yield. Dedo 2022 was the highest yielding (4.1 t/ha) while Gechi 2022 was the lowest yielding (1.5 t/ha) environment. The mean grain yield of the varieties across eight environments was 3 t/ha. The GGE biplot identified two barley growing mega-environments. The first mega environment consisted of environments E5, E8, E1 with a vertex genotype T4. E6, E4, E3, E2 and E7 were found in the second mega environment with the winning genotype of T8. It was also noted that no mega-environments fell into sectors where genotype T2 and T7 were the vertex genotypes, did not fit in any of the mega-environments. According to both AMMI and GGE biplot analysis, food barley varieties T3, T7 and T5 were found to be benchmarks/ideal genotypes and could be used as checks to evaluate the performance of other genotypes and also can be recommended for wider cultivation in the highland environments of Southwestern Ethiopia.
    
    VL  - 11
    IS  - 4
    ER  - 

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

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