Yield Stability and Correlation Among Stability Parameters in Faba Bean (<i>Vicia faba</i> L.) Yield Trial in Ethiopia

Gebeyaw Achenef Haile; Gizachew Yilma

doi:doi:10.11648/j.cbb.20210902.12

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Yield Stability and Correlation Among Stability Parameters in Faba Bean (Vicia faba L.) Yield Trial in Ethiopia

Gebeyaw Achenef Haile, Gizachew Yilma

Published in Computational Biology and Bioinformatics (Volume 9, Issue 2)

Received: 16 July 2021 Accepted: 26 July 2021 Published: 2 August 2021

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Abstract

The relationship between the adaptableness and stability estimates of different models is revealing of whether one or more estimates should be obtained for consistent forecasts of cultivar behavior, and also helps the breeder to select the best adjusted and most informative stability parameter(s). Twelve faba bean genotypes were assessed in 2018/2019 cropping season across seven environments in Ethiopia using randomized complete block design with four replications. The objectives were to identify stable faba bean genotypes across the target environments and determine the relationship among univariate stability parameters. The yield stability was estimated using various stability parameters. Using Eberhart and Russell’s model the regression coefficient (bi) values ranged from 0.85 (G5) to 1.08 (G3). The regression coefficient of G1 (bi = 0.99) and G11 (bi= 1.02) indicated average adaptable across environments. In contrast G2, G3, G4, and G8 have a regression coefficient bi value significantly greater than 1; this showed that genotypes are very sensitive when the environment is changed. To see the level of association among the parameters Spearman’s rank correlation was employed and the result showed highly significant positive rank correlation between cultivar mean performance Pi (r = 0.978) and mean seed yield. Shukula stability variance (ơ²) was significant positive rank correlated (r=1) with (ωi) indicating, the two stability parameters were similar for ranking purposes. Most of the univerate stability (ωi, ơ2, S²di, bi, ASV) parameters identified G8, G6 and G12 were stable and high yielder. Moreover, the experiment has to be repeated in multi locations to provide more reliable results and make recommendations for wide or specific adaptable genotypes in Ethiopia.

Published in	Computational Biology and Bioinformatics (Volume 9, Issue 2)
DOI	10.11648/j.cbb.20210902.12
Page(s)	39-44
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

Association, Environment, Faba Bean, Parameter, Rank, Stability

References

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[3]	Crossa J., Gauch H. G. Jr., and Zobel, R. W. 1990. Additive Main Effects and Multiplicative Interaction Analysis of Two International Maize Cultivar Trials. Crop science, (30): 493-500.
[4]	Dagnachew Lule, Kasahun Tesfaye and Girma Mengistu 2014. Genotype by environment interaction and grain yield stability analysis for advanced triticale (x. Triticosecale wittmack) genotypes in western Oromia, Ethiop. J. Sci., 37 (1): 63–68.
[5]	Eberhart S. A., and Russell W. A. 1966. Stability Parameters for Comparing Varieties. Iowa State University, Crop Sci. 6: 36-40.
[6]	Erdemci, 2018. Investigation of G x E interaction in Chickpea genotypes using AMMI and GGE biplot analysis. Turk J. Filed crops: 23 (1) 20-26.
[7]	Eyeberu Abere, 2017. Genotype by Environment interaction and yield stability of early maturing sorghum (Sorghum bicolor L.) Moench) varieties in Eastern Amhara, Ethiopia. MSc. Thesis Haramaya University, Ethiopia.
[8]	Fasahat P, Rajabi A, Mahmoudi SB, Noghabi MA, Rad JM (2015) An Overview on the Use of Stability Parameters in Plant Breeding. Biom Biostat Int J. 2: (5).
[9]	Gauch, Jr. 2006. Winning the Accuracy Game. Three statistical strategies replicating, blocking and modeling can help scientists improve accuracy and accelerate progress. American Scientist, 94: 133-141.
[10]	IBPGR and ICARDA (International Board of Plant Genetic Resources and International Crop research in dray area) 1985. Descriptors for faba bean (Vicia faba L.) Moench. IBPGR, Rome.
[11]	Lin, C. S., & Binns, M. R. (1988). A superiority measure of cultivar performance for cultivar× location data. Canadian journal of plant science, 68 (1), 193-198.
[12]	Muluken Bantayehu (2009). Analysis and correlation of stability parameters in malting barley. African Crop Science Journal, 17 (3).
[13]	Mussa Jarso and Yohans Degago, (1997). Genotype X Environment interaction and grain yield stability in faba bean: 16-25. In Proceedings of the eight annual conference of the crop science society of Ethiopia, Sebil (pp. 26-27).
[14]	Purchase L. J. 1997. Parametric analysis to describe genotype x environment interaction and yield stability in Winter Wheat. PhD. Thesis, Department of Agronomy, Faculty of Agricultre, University of the orange Free State, Bloemfontein, South Africa.
[15]	Scapim, C. A., Oliveira, V. R., Lucca, A. De, & Cruz, C. D. (2000). Yield stability in maize (Zea mays L.) and correlations among the parameters of the Eberhart and Russell, Lin and Binns and Huehn models, 393, 387–393.
[16]	Shukla, G. K. (1972). Some statistical aspects of partitioning genotype environmental components of variability. Heredity, 29 (2), 237-245.
[17]	Tamene Tollessa, Gemechu Keneni, Taddesse Sefera, Mussa Jarso, & Yeneneh Bekele, (2013). Genotype× environment interaction and performance stability for grain yield in field pea (Pisum sativum L.) genotypes. International Journal of plant breeding, 7 (2), 116-123.
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APA Style

Gebeyaw Achenef Haile, Gizachew Yilma. (2021). Yield Stability and Correlation Among Stability Parameters in Faba Bean (Vicia faba L.) Yield Trial in Ethiopia. Computational Biology and Bioinformatics, 9(2), 39-44. https://doi.org/10.11648/j.cbb.20210902.12

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ACS Style

Gebeyaw Achenef Haile; Gizachew Yilma. Yield Stability and Correlation Among Stability Parameters in Faba Bean (Vicia faba L.) Yield Trial in Ethiopia. Comput. Biol. Bioinform. 2021, 9(2), 39-44. doi: 10.11648/j.cbb.20210902.12

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AMA Style

Gebeyaw Achenef Haile, Gizachew Yilma. Yield Stability and Correlation Among Stability Parameters in Faba Bean (Vicia faba L.) Yield Trial in Ethiopia. Comput Biol Bioinform. 2021;9(2):39-44. doi: 10.11648/j.cbb.20210902.12

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@article{10.11648/j.cbb.20210902.12,
  author = {Gebeyaw Achenef Haile and Gizachew Yilma},
  title = {Yield Stability and Correlation Among Stability Parameters in Faba Bean (Vicia faba L.) Yield Trial in Ethiopia},
  journal = {Computational Biology and Bioinformatics},
  volume = {9},
  number = {2},
  pages = {39-44},
  doi = {10.11648/j.cbb.20210902.12},
  url = {https://doi.org/10.11648/j.cbb.20210902.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cbb.20210902.12},
  abstract = {The relationship between the adaptableness and stability estimates of different models is revealing of whether one or more estimates should be obtained for consistent forecasts of cultivar behavior, and also helps the breeder to select the best adjusted and most informative stability parameter(s). Twelve faba bean genotypes were assessed in 2018/2019 cropping season across seven environments in Ethiopia using randomized complete block design with four replications. The objectives were to identify stable faba bean genotypes across the target environments and determine the relationship among univariate stability parameters. The yield stability was estimated using various stability parameters. Using Eberhart and Russell’s model the regression coefficient (bi) values ranged from 0.85 (G5) to 1.08 (G3). The regression coefficient of G1 (bi = 0.99) and G11 (bi= 1.02) indicated average adaptable across environments. In contrast G2, G3, G4, and G8 have a regression coefficient bi value significantly greater than 1; this showed that genotypes are very sensitive when the environment is changed. To see the level of association among the parameters Spearman’s rank correlation was employed and the result showed highly significant positive rank correlation between cultivar mean performance Pi (r = 0.978) and mean seed yield. Shukula stability variance (ơ2) was significant positive rank correlated (r=1) with (ωi) indicating, the two stability parameters were similar for ranking purposes. Most of the univerate stability (ωi, ơ2, S2di, bi, ASV) parameters identified G8, G6 and G12 were stable and high yielder. Moreover, the experiment has to be repeated in multi locations to provide more reliable results and make recommendations for wide or specific adaptable genotypes in Ethiopia.},
 year = {2021}
}

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TY  - JOUR
T1  - Yield Stability and Correlation Among Stability Parameters in Faba Bean (Vicia faba L.) Yield Trial in Ethiopia
AU  - Gebeyaw Achenef Haile
AU  - Gizachew Yilma
Y1  - 2021/08/02
PY  - 2021
N1  - https://doi.org/10.11648/j.cbb.20210902.12
DO  - 10.11648/j.cbb.20210902.12
T2  - Computational Biology and Bioinformatics
JF  - Computational Biology and Bioinformatics
JO  - Computational Biology and Bioinformatics
SP  - 39
EP  - 44
PB  - Science Publishing Group
SN  - 2330-8281
UR  - https://doi.org/10.11648/j.cbb.20210902.12
AB  - The relationship between the adaptableness and stability estimates of different models is revealing of whether one or more estimates should be obtained for consistent forecasts of cultivar behavior, and also helps the breeder to select the best adjusted and most informative stability parameter(s). Twelve faba bean genotypes were assessed in 2018/2019 cropping season across seven environments in Ethiopia using randomized complete block design with four replications. The objectives were to identify stable faba bean genotypes across the target environments and determine the relationship among univariate stability parameters. The yield stability was estimated using various stability parameters. Using Eberhart and Russell’s model the regression coefficient (bi) values ranged from 0.85 (G5) to 1.08 (G3). The regression coefficient of G1 (bi = 0.99) and G11 (bi= 1.02) indicated average adaptable across environments. In contrast G2, G3, G4, and G8 have a regression coefficient bi value significantly greater than 1; this showed that genotypes are very sensitive when the environment is changed. To see the level of association among the parameters Spearman’s rank correlation was employed and the result showed highly significant positive rank correlation between cultivar mean performance Pi (r = 0.978) and mean seed yield. Shukula stability variance (ơ2) was significant positive rank correlated (r=1) with (ωi) indicating, the two stability parameters were similar for ranking purposes. Most of the univerate stability (ωi, ơ2, S2di, bi, ASV) parameters identified G8, G6 and G12 were stable and high yielder. Moreover, the experiment has to be repeated in multi locations to provide more reliable results and make recommendations for wide or specific adaptable genotypes in Ethiopia.
VL  - 9
IS  - 2
ER  -

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Author Information

Gebeyaw Achenef Haile

Ethiopian Institute of Agricultural Research (EIAR), Kulumsa Agricultural Research Centre, Assela, Ethiopia
Gizachew Yilma

Ethiopian Institute of Agricultural Research (EIAR), Kulumsa Agricultural Research Centre, Assela, Ethiopia

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APA Style

Gebeyaw Achenef Haile, Gizachew Yilma. (2021). Yield Stability and Correlation Among Stability Parameters in Faba Bean (Vicia faba L.) Yield Trial in Ethiopia. Computational Biology and Bioinformatics, 9(2), 39-44. https://doi.org/10.11648/j.cbb.20210902.12

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ACS Style

Gebeyaw Achenef Haile; Gizachew Yilma. Yield Stability and Correlation Among Stability Parameters in Faba Bean (Vicia faba L.) Yield Trial in Ethiopia. Comput. Biol. Bioinform. 2021, 9(2), 39-44. doi: 10.11648/j.cbb.20210902.12

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AMA Style

Gebeyaw Achenef Haile, Gizachew Yilma. Yield Stability and Correlation Among Stability Parameters in Faba Bean (Vicia faba L.) Yield Trial in Ethiopia. Comput Biol Bioinform. 2021;9(2):39-44. doi: 10.11648/j.cbb.20210902.12

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@article{10.11648/j.cbb.20210902.12,
  author = {Gebeyaw Achenef Haile and Gizachew Yilma},
  title = {Yield Stability and Correlation Among Stability Parameters in Faba Bean (Vicia faba L.) Yield Trial in Ethiopia},
  journal = {Computational Biology and Bioinformatics},
  volume = {9},
  number = {2},
  pages = {39-44},
  doi = {10.11648/j.cbb.20210902.12},
  url = {https://doi.org/10.11648/j.cbb.20210902.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cbb.20210902.12},
  abstract = {The relationship between the adaptableness and stability estimates of different models is revealing of whether one or more estimates should be obtained for consistent forecasts of cultivar behavior, and also helps the breeder to select the best adjusted and most informative stability parameter(s). Twelve faba bean genotypes were assessed in 2018/2019 cropping season across seven environments in Ethiopia using randomized complete block design with four replications. The objectives were to identify stable faba bean genotypes across the target environments and determine the relationship among univariate stability parameters. The yield stability was estimated using various stability parameters. Using Eberhart and Russell’s model the regression coefficient (bi) values ranged from 0.85 (G5) to 1.08 (G3). The regression coefficient of G1 (bi = 0.99) and G11 (bi= 1.02) indicated average adaptable across environments. In contrast G2, G3, G4, and G8 have a regression coefficient bi value significantly greater than 1; this showed that genotypes are very sensitive when the environment is changed. To see the level of association among the parameters Spearman’s rank correlation was employed and the result showed highly significant positive rank correlation between cultivar mean performance Pi (r = 0.978) and mean seed yield. Shukula stability variance (ơ2) was significant positive rank correlated (r=1) with (ωi) indicating, the two stability parameters were similar for ranking purposes. Most of the univerate stability (ωi, ơ2, S2di, bi, ASV) parameters identified G8, G6 and G12 were stable and high yielder. Moreover, the experiment has to be repeated in multi locations to provide more reliable results and make recommendations for wide or specific adaptable genotypes in Ethiopia.},
 year = {2021}
}

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TY  - JOUR
T1  - Yield Stability and Correlation Among Stability Parameters in Faba Bean (Vicia faba L.) Yield Trial in Ethiopia
AU  - Gebeyaw Achenef Haile
AU  - Gizachew Yilma
Y1  - 2021/08/02
PY  - 2021
N1  - https://doi.org/10.11648/j.cbb.20210902.12
DO  - 10.11648/j.cbb.20210902.12
T2  - Computational Biology and Bioinformatics
JF  - Computational Biology and Bioinformatics
JO  - Computational Biology and Bioinformatics
SP  - 39
EP  - 44
PB  - Science Publishing Group
SN  - 2330-8281
UR  - https://doi.org/10.11648/j.cbb.20210902.12
AB  - The relationship between the adaptableness and stability estimates of different models is revealing of whether one or more estimates should be obtained for consistent forecasts of cultivar behavior, and also helps the breeder to select the best adjusted and most informative stability parameter(s). Twelve faba bean genotypes were assessed in 2018/2019 cropping season across seven environments in Ethiopia using randomized complete block design with four replications. The objectives were to identify stable faba bean genotypes across the target environments and determine the relationship among univariate stability parameters. The yield stability was estimated using various stability parameters. Using Eberhart and Russell’s model the regression coefficient (bi) values ranged from 0.85 (G5) to 1.08 (G3). The regression coefficient of G1 (bi = 0.99) and G11 (bi= 1.02) indicated average adaptable across environments. In contrast G2, G3, G4, and G8 have a regression coefficient bi value significantly greater than 1; this showed that genotypes are very sensitive when the environment is changed. To see the level of association among the parameters Spearman’s rank correlation was employed and the result showed highly significant positive rank correlation between cultivar mean performance Pi (r = 0.978) and mean seed yield. Shukula stability variance (ơ2) was significant positive rank correlated (r=1) with (ωi) indicating, the two stability parameters were similar for ranking purposes. Most of the univerate stability (ωi, ơ2, S2di, bi, ASV) parameters identified G8, G6 and G12 were stable and high yielder. Moreover, the experiment has to be repeated in multi locations to provide more reliable results and make recommendations for wide or specific adaptable genotypes in Ethiopia.
VL  - 9
IS  - 2
ER  -

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