GGE Biplot Analysis of Genotype x Environment Interaction on Bread Wheat (<i>Triticum aestivum</i> L.) Genotypes in Southern Oromia

Aliyi Kedir; Hussein Mohammed; Tesfaye Letta

doi:doi:10.11648/j.jcebe.20220601.11

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GGE Biplot Analysis of Genotype x Environment Interaction on Bread Wheat (Triticum aestivum L.) Genotypes in Southern Oromia

Aliyi Kedir, Hussein Mohammed, Tesfaye Letta

Published in Journal of Chemical, Environmental and Biological Engineering (Volume 6, Issue 1)

Received: 29 January 2022 Accepted: 22 February 2022 Published: 3 March 2022

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Abstract

Today, wheat is among the most important crops grown in Ethiopia, both as a source of food for consumers and as a source of income for farmers. Since Ethiopia is known for its diverse agro-ecology the performance of genotypes differs within and across environments and cultivars or genotypes respond differently to diverse environments. Therefore, studies on Genotype by Environment (GxE) interaction may help to determine whether or not a genotype is stable in performance over a range of environments. Therefore, this study was conducted to identify the best performing stable bread wheat genotype for selected areas and analysis of the environment by GGE biplot. In this experiment, 20 bread wheat genotypes were evaluated using RCBD with three replications at five different locations in southern Oromia. The combined analysis of variance revealed that, there were highly significant differences among environments and among genotypes (p<0.001) for grain yield and yield components and for growth parameters except for days to emergence which was non-significant, indicating the presence of variability in genotypes as well as diversity of growing conditions at different locations. The GxE interaction was highly significant (p<0.001) for all traits except spike length reflecting the differential response of genotypes in various environments. Environments explained 59.1%, genotypes 19.1% and GxE 14.8% of the variability in grin yield. Bore (E1) was the most discriminating environment while Adola (E3) and Liben (E4) were the least discriminating environments. GGE-II explained 89.62% of G+GEI and the angle between pair of all locations was lower than 90°; performance of genotypes at all environments was almost similar, but Bore (E1) was separated from the remaining four environments. The bi-plot had six vertex genotypes, viz. Wane (G2), PBW-343 (G20), Galama (G13), Kakaba (G10), Hawi (G3) and ETBW8420 (G18). Hidase (G7) and Tuse (G8) gave relatively high grain yield and found to be stable, so can be recommended for wide adaptation. Wane (G2) and PBW-343 (G20) were unstable but were predicted to give the highest grain yield at all environments. Dashen (G6) and ETBW8420 (G18) can be recommended for all environments except for the high land environment, Bore (E1), while Lemu (G1) can be recommended for only Bore (E1). Lole Farm (E5) was the ideal environment while Wane (G2) was the ideal genotype. Advanced line ETBW420 (G18) is recommended to be included in variety verification trials for release as new varieties or to be included crossing program.

Published in	Journal of Chemical, Environmental and Biological Engineering (Volume 6, Issue 1)
DOI	10.11648/j.jcebe.20220601.11
Page(s)	1-9
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), 2022. Published by Science Publishing Group

Keywords

GEI, Stable, Grain Yield, Adapted, Bread Wheat, Southern Ethiopia

References

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[2]	Babarmanzoor, A., M. S. Tariq, A. Ghulam, & A. Muhammad. 2009. Genotype × environment interaction for seed yield in Kabuli Chickpea (Cicer arietinum L.) genotypes developed through mutation breeding. Paki. J. of Botany 41: 1883-1890.
[3]	Becker, H. C. and Léon, J., 1988. Stability analysis in plant breeding. Plant Breeding 101: 1-23.
[4]	Bridges. W. C. 1989. Analysis of plant breeding experiment with heterogeneous.
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[6]	Desalegn Regasa, 2012. Genotype-Environment interaction and disease severity in bread wheat (Triticum aestivum L.) varieties in Borena and Guji Zone southern Ethiopia. An MSc Thesis Presented to the School of Graduate Studies of Haramaya University, Ethiopia.
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[9]	Fiseha Baraki, Yemane Tsehaye, and FetienAbay. 2015. AMMI analysis of Genotype x Environment interaction and stability analysis of sesame genotypes in northern Ethiopia. Asian J. Plant Sci, 13 (4-8): 178-183.
[10]	Gauch HG, Zobel RW (1997) Identifying mega-environments and targeting genotypes. Crop Sci 37: 311-326.
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[16]	Mohamed, N. E. (2013). Genotype by environment interactions for grain yield in bread wheat (Triticum aestivum L.). Journal of Plant Breeding and Crop Science, 7 (5), 150-157.
[17]	Mohammadi. R, Mozaffar RM, Yousef A, Mostafa A & Amri. A. 2010b. Relationships of phenotypic stability measures for genotypes of three cereal crops. Canadian J. of Plant Sci. 90. 819-830.
[18]	Olayiwola, M. O. and Ariyo, O. J. 2013. Relative discriminatory ability of GGE bi-plot and SYi in the analysis of Genotype x Environment Interaction in okra (Abelmoschus esculentus). International journal of plant breeding and genetics, 7 (3): 146-158.
[19]	Purchase, J. L., 1997. Parametric analysis to describe Genotype x Environment interaction and yield stability in winter wheat. Ph.D. Thesis, Department of Agronomy, Faculty of Agriculture, University of the Free State, Bloemfontein, South Africa.
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Aliyi Kedir, Hussein Mohammed, Tesfaye Letta. (2022). GGE Biplot Analysis of Genotype x Environment Interaction on Bread Wheat (Triticum aestivum L.) Genotypes in Southern Oromia. Journal of Chemical, Environmental and Biological Engineering, 6(1), 1-9. https://doi.org/10.11648/j.jcebe.20220601.11

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ACS Style

Aliyi Kedir; Hussein Mohammed; Tesfaye Letta. GGE Biplot Analysis of Genotype x Environment Interaction on Bread Wheat (Triticum aestivum L.) Genotypes in Southern Oromia. J. Chem. Environ. Biol. Eng. 2022, 6(1), 1-9. doi: 10.11648/j.jcebe.20220601.11

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AMA Style

Aliyi Kedir, Hussein Mohammed, Tesfaye Letta. GGE Biplot Analysis of Genotype x Environment Interaction on Bread Wheat (Triticum aestivum L.) Genotypes in Southern Oromia. J Chem Environ Biol Eng. 2022;6(1):1-9. doi: 10.11648/j.jcebe.20220601.11

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@article{10.11648/j.jcebe.20220601.11,
  author = {Aliyi Kedir and Hussein Mohammed and Tesfaye Letta},
  title = {GGE Biplot Analysis of Genotype x Environment Interaction on Bread Wheat (Triticum aestivum L.) Genotypes in Southern Oromia},
  journal = {Journal of Chemical, Environmental and Biological Engineering},
  volume = {6},
  number = {1},
  pages = {1-9},
  doi = {10.11648/j.jcebe.20220601.11},
  url = {https://doi.org/10.11648/j.jcebe.20220601.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jcebe.20220601.11},
  abstract = {Today, wheat is among the most important crops grown in Ethiopia, both as a source of food for consumers and as a source of income for farmers. Since Ethiopia is known for its diverse agro-ecology the performance of genotypes differs within and across environments and cultivars or genotypes respond differently to diverse environments. Therefore, studies on Genotype by Environment (GxE) interaction may help to determine whether or not a genotype is stable in performance over a range of environments. Therefore, this study was conducted to identify the best performing stable bread wheat genotype for selected areas and analysis of the environment by GGE biplot. In this experiment, 20 bread wheat genotypes were evaluated using RCBD with three replications at five different locations in southern Oromia. The combined analysis of variance revealed that, there were highly significant differences among environments and among genotypes (p<0.001) for grain yield and yield components and for growth parameters except for days to emergence which was non-significant, indicating the presence of variability in genotypes as well as diversity of growing conditions at different locations. The GxE interaction was highly significant (p<0.001) for all traits except spike length reflecting the differential response of genotypes in various environments. Environments explained 59.1%, genotypes 19.1% and GxE 14.8% of the variability in grin yield. Bore (E1) was the most discriminating environment while Adola (E3) and Liben (E4) were the least discriminating environments. GGE-II explained 89.62% of G+GEI and the angle between pair of all locations was lower than 90°; performance of genotypes at all environments was almost similar, but Bore (E1) was separated from the remaining four environments. The bi-plot had six vertex genotypes, viz. Wane (G2), PBW-343 (G20), Galama (G13), Kakaba (G10), Hawi (G3) and ETBW8420 (G18). Hidase (G7) and Tuse (G8) gave relatively high grain yield and found to be stable, so can be recommended for wide adaptation. Wane (G2) and PBW-343 (G20) were unstable but were predicted to give the highest grain yield at all environments. Dashen (G6) and ETBW8420 (G18) can be recommended for all environments except for the high land environment, Bore (E1), while Lemu (G1) can be recommended for only Bore (E1). Lole Farm (E5) was the ideal environment while Wane (G2) was the ideal genotype. Advanced line ETBW420 (G18) is recommended to be included in variety verification trials for release as new varieties or to be included crossing program.},
 year = {2022}
}

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TY  - JOUR
T1  - GGE Biplot Analysis of Genotype x Environment Interaction on Bread Wheat (Triticum aestivum L.) Genotypes in Southern Oromia
AU  - Aliyi Kedir
AU  - Hussein Mohammed
AU  - Tesfaye Letta
Y1  - 2022/03/03
PY  - 2022
N1  - https://doi.org/10.11648/j.jcebe.20220601.11
DO  - 10.11648/j.jcebe.20220601.11
T2  - Journal of Chemical, Environmental and Biological Engineering
JF  - Journal of Chemical, Environmental and Biological Engineering
JO  - Journal of Chemical, Environmental and Biological Engineering
SP  - 1
EP  - 9
PB  - Science Publishing Group
SN  - 2640-267X
UR  - https://doi.org/10.11648/j.jcebe.20220601.11
AB  - Today, wheat is among the most important crops grown in Ethiopia, both as a source of food for consumers and as a source of income for farmers. Since Ethiopia is known for its diverse agro-ecology the performance of genotypes differs within and across environments and cultivars or genotypes respond differently to diverse environments. Therefore, studies on Genotype by Environment (GxE) interaction may help to determine whether or not a genotype is stable in performance over a range of environments. Therefore, this study was conducted to identify the best performing stable bread wheat genotype for selected areas and analysis of the environment by GGE biplot. In this experiment, 20 bread wheat genotypes were evaluated using RCBD with three replications at five different locations in southern Oromia. The combined analysis of variance revealed that, there were highly significant differences among environments and among genotypes (p<0.001) for grain yield and yield components and for growth parameters except for days to emergence which was non-significant, indicating the presence of variability in genotypes as well as diversity of growing conditions at different locations. The GxE interaction was highly significant (p<0.001) for all traits except spike length reflecting the differential response of genotypes in various environments. Environments explained 59.1%, genotypes 19.1% and GxE 14.8% of the variability in grin yield. Bore (E1) was the most discriminating environment while Adola (E3) and Liben (E4) were the least discriminating environments. GGE-II explained 89.62% of G+GEI and the angle between pair of all locations was lower than 90°; performance of genotypes at all environments was almost similar, but Bore (E1) was separated from the remaining four environments. The bi-plot had six vertex genotypes, viz. Wane (G2), PBW-343 (G20), Galama (G13), Kakaba (G10), Hawi (G3) and ETBW8420 (G18). Hidase (G7) and Tuse (G8) gave relatively high grain yield and found to be stable, so can be recommended for wide adaptation. Wane (G2) and PBW-343 (G20) were unstable but were predicted to give the highest grain yield at all environments. Dashen (G6) and ETBW8420 (G18) can be recommended for all environments except for the high land environment, Bore (E1), while Lemu (G1) can be recommended for only Bore (E1). Lole Farm (E5) was the ideal environment while Wane (G2) was the ideal genotype. Advanced line ETBW420 (G18) is recommended to be included in variety verification trials for release as new varieties or to be included crossing program.
VL  - 6
IS  - 1
ER  -

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Author Information

Aliyi Kedir

Cereal Crop Breeding, Bore Agricultural Research Center, Bore, Ethiopia
Hussein Mohammed

College of Agriculture, Hawassa University, Hawassa, Ethiopia
Tesfaye Letta

Wheat Breeding and Genetics, Oromia Agricultural Research Institute, Addis Ababa, Ethiopia

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Plain Text BibTeX RIS

APA Style

Aliyi Kedir, Hussein Mohammed, Tesfaye Letta. (2022). GGE Biplot Analysis of Genotype x Environment Interaction on Bread Wheat (Triticum aestivum L.) Genotypes in Southern Oromia. Journal of Chemical, Environmental and Biological Engineering, 6(1), 1-9. https://doi.org/10.11648/j.jcebe.20220601.11

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ACS Style

Aliyi Kedir; Hussein Mohammed; Tesfaye Letta. GGE Biplot Analysis of Genotype x Environment Interaction on Bread Wheat (Triticum aestivum L.) Genotypes in Southern Oromia. J. Chem. Environ. Biol. Eng. 2022, 6(1), 1-9. doi: 10.11648/j.jcebe.20220601.11

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AMA Style

Aliyi Kedir, Hussein Mohammed, Tesfaye Letta. GGE Biplot Analysis of Genotype x Environment Interaction on Bread Wheat (Triticum aestivum L.) Genotypes in Southern Oromia. J Chem Environ Biol Eng. 2022;6(1):1-9. doi: 10.11648/j.jcebe.20220601.11

Copy | Download

@article{10.11648/j.jcebe.20220601.11,
  author = {Aliyi Kedir and Hussein Mohammed and Tesfaye Letta},
  title = {GGE Biplot Analysis of Genotype x Environment Interaction on Bread Wheat (Triticum aestivum L.) Genotypes in Southern Oromia},
  journal = {Journal of Chemical, Environmental and Biological Engineering},
  volume = {6},
  number = {1},
  pages = {1-9},
  doi = {10.11648/j.jcebe.20220601.11},
  url = {https://doi.org/10.11648/j.jcebe.20220601.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jcebe.20220601.11},
  abstract = {Today, wheat is among the most important crops grown in Ethiopia, both as a source of food for consumers and as a source of income for farmers. Since Ethiopia is known for its diverse agro-ecology the performance of genotypes differs within and across environments and cultivars or genotypes respond differently to diverse environments. Therefore, studies on Genotype by Environment (GxE) interaction may help to determine whether or not a genotype is stable in performance over a range of environments. Therefore, this study was conducted to identify the best performing stable bread wheat genotype for selected areas and analysis of the environment by GGE biplot. In this experiment, 20 bread wheat genotypes were evaluated using RCBD with three replications at five different locations in southern Oromia. The combined analysis of variance revealed that, there were highly significant differences among environments and among genotypes (p<0.001) for grain yield and yield components and for growth parameters except for days to emergence which was non-significant, indicating the presence of variability in genotypes as well as diversity of growing conditions at different locations. The GxE interaction was highly significant (p<0.001) for all traits except spike length reflecting the differential response of genotypes in various environments. Environments explained 59.1%, genotypes 19.1% and GxE 14.8% of the variability in grin yield. Bore (E1) was the most discriminating environment while Adola (E3) and Liben (E4) were the least discriminating environments. GGE-II explained 89.62% of G+GEI and the angle between pair of all locations was lower than 90°; performance of genotypes at all environments was almost similar, but Bore (E1) was separated from the remaining four environments. The bi-plot had six vertex genotypes, viz. Wane (G2), PBW-343 (G20), Galama (G13), Kakaba (G10), Hawi (G3) and ETBW8420 (G18). Hidase (G7) and Tuse (G8) gave relatively high grain yield and found to be stable, so can be recommended for wide adaptation. Wane (G2) and PBW-343 (G20) were unstable but were predicted to give the highest grain yield at all environments. Dashen (G6) and ETBW8420 (G18) can be recommended for all environments except for the high land environment, Bore (E1), while Lemu (G1) can be recommended for only Bore (E1). Lole Farm (E5) was the ideal environment while Wane (G2) was the ideal genotype. Advanced line ETBW420 (G18) is recommended to be included in variety verification trials for release as new varieties or to be included crossing program.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - GGE Biplot Analysis of Genotype x Environment Interaction on Bread Wheat (Triticum aestivum L.) Genotypes in Southern Oromia
AU  - Aliyi Kedir
AU  - Hussein Mohammed
AU  - Tesfaye Letta
Y1  - 2022/03/03
PY  - 2022
N1  - https://doi.org/10.11648/j.jcebe.20220601.11
DO  - 10.11648/j.jcebe.20220601.11
T2  - Journal of Chemical, Environmental and Biological Engineering
JF  - Journal of Chemical, Environmental and Biological Engineering
JO  - Journal of Chemical, Environmental and Biological Engineering
SP  - 1
EP  - 9
PB  - Science Publishing Group
SN  - 2640-267X
UR  - https://doi.org/10.11648/j.jcebe.20220601.11
AB  - Today, wheat is among the most important crops grown in Ethiopia, both as a source of food for consumers and as a source of income for farmers. Since Ethiopia is known for its diverse agro-ecology the performance of genotypes differs within and across environments and cultivars or genotypes respond differently to diverse environments. Therefore, studies on Genotype by Environment (GxE) interaction may help to determine whether or not a genotype is stable in performance over a range of environments. Therefore, this study was conducted to identify the best performing stable bread wheat genotype for selected areas and analysis of the environment by GGE biplot. In this experiment, 20 bread wheat genotypes were evaluated using RCBD with three replications at five different locations in southern Oromia. The combined analysis of variance revealed that, there were highly significant differences among environments and among genotypes (p<0.001) for grain yield and yield components and for growth parameters except for days to emergence which was non-significant, indicating the presence of variability in genotypes as well as diversity of growing conditions at different locations. The GxE interaction was highly significant (p<0.001) for all traits except spike length reflecting the differential response of genotypes in various environments. Environments explained 59.1%, genotypes 19.1% and GxE 14.8% of the variability in grin yield. Bore (E1) was the most discriminating environment while Adola (E3) and Liben (E4) were the least discriminating environments. GGE-II explained 89.62% of G+GEI and the angle between pair of all locations was lower than 90°; performance of genotypes at all environments was almost similar, but Bore (E1) was separated from the remaining four environments. The bi-plot had six vertex genotypes, viz. Wane (G2), PBW-343 (G20), Galama (G13), Kakaba (G10), Hawi (G3) and ETBW8420 (G18). Hidase (G7) and Tuse (G8) gave relatively high grain yield and found to be stable, so can be recommended for wide adaptation. Wane (G2) and PBW-343 (G20) were unstable but were predicted to give the highest grain yield at all environments. Dashen (G6) and ETBW8420 (G18) can be recommended for all environments except for the high land environment, Bore (E1), while Lemu (G1) can be recommended for only Bore (E1). Lole Farm (E5) was the ideal environment while Wane (G2) was the ideal genotype. Advanced line ETBW420 (G18) is recommended to be included in variety verification trials for release as new varieties or to be included crossing program.
VL  - 6
IS  - 1
ER  -

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