Parametric and Non-parametric Procedures for Identifying Stable and Adapted Tropical Maize Genotypes in NLB Disease Infested Environments

Akinlolu O. Ohunakin; Odiyi Alex C.; Akinyele Benjamin O.; Fayeun Lawrence Stephen; Alake Gideon Collins

doi:doi:10.11648/j.ajbio.20210906.15

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Parametric and Non-parametric Procedures for Identifying Stable and Adapted Tropical Maize Genotypes in NLB Disease Infested Environments

Akinlolu O. Ohunakin, Odiyi Alex C., Akinyele Benjamin O., Fayeun Lawrence Stephen, Alake Gideon Collins

Published in American Journal of BioScience (Volume 9, Issue 6)

Received: 28 October 2021 Accepted: 13 November 2021 Published: 29 December 2021

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Abstract

Multi-locational trials are critical for establishing stable and adaptable genotypes across different geographic areas prior to considering commercial release. The stability and adaptation of 20 tropical maize hybrids in environments infected with Northern leaf blight disease were assessed using 12 parametric and 14 nonparametric parameters across five environments. The purpose of this research is to estimate the genotype-environment interaction (GEI) for grain yield in selected maize genotypes and to identify associated stability factors to aid in the rationalization of stability analysis in Multi-Environment Trial (MET) data used in breeding programs. Except for De Kroon and Van der Laan (1981), both the combined ANOVA and nonparametric tests of GEI showed significant differences across hybrids, as well as significant crossover and non-crossover interactions. This suggests differential genotypes responses to the test environments. Spearman correlation analysis revealed significant differences between many nonparametric and parametric parameters, indicating that the two may be utilized interchangeably. Additionally, the correlation matrix and principal component analysis results from parametric and nonparametric parameters demonstrated their potential to assess the responses of maize genotypes to changing environments. G13 and G20 appeared most phenotypically stable with associated high mean yield based on the high values expressed by most parametric and nonparametric parameters.

Published in	American Journal of BioScience (Volume 9, Issue 6)
DOI	10.11648/j.ajbio.20210906.15
Page(s)	199-209
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

Maize, Parametric, Non-Parametric, Genotypes, Environment, Multi-Environment Trial, Spearman Correlation, Principal Component Analysis

References

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APA Style

Akinlolu O. Ohunakin, Odiyi Alex C., Akinyele Benjamin O., Fayeun Lawrence Stephen, Alake Gideon Collins. (2021). Parametric and Non-parametric Procedures for Identifying Stable and Adapted Tropical Maize Genotypes in NLB Disease Infested Environments. American Journal of BioScience, 9(6), 199-209. https://doi.org/10.11648/j.ajbio.20210906.15

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ACS Style

Akinlolu O. Ohunakin; Odiyi Alex C.; Akinyele Benjamin O.; Fayeun Lawrence Stephen; Alake Gideon Collins. Parametric and Non-parametric Procedures for Identifying Stable and Adapted Tropical Maize Genotypes in NLB Disease Infested Environments. Am. J. BioScience 2021, 9(6), 199-209. doi: 10.11648/j.ajbio.20210906.15

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AMA Style

Akinlolu O. Ohunakin, Odiyi Alex C., Akinyele Benjamin O., Fayeun Lawrence Stephen, Alake Gideon Collins. Parametric and Non-parametric Procedures for Identifying Stable and Adapted Tropical Maize Genotypes in NLB Disease Infested Environments. Am J BioScience. 2021;9(6):199-209. doi: 10.11648/j.ajbio.20210906.15

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@article{10.11648/j.ajbio.20210906.15,
  author = {Akinlolu O. Ohunakin and Odiyi Alex C. and Akinyele Benjamin O. and Fayeun Lawrence Stephen and Alake Gideon Collins},
  title = {Parametric and Non-parametric Procedures for Identifying Stable and Adapted Tropical Maize Genotypes in NLB Disease Infested Environments},
  journal = {American Journal of BioScience},
  volume = {9},
  number = {6},
  pages = {199-209},
  doi = {10.11648/j.ajbio.20210906.15},
  url = {https://doi.org/10.11648/j.ajbio.20210906.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajbio.20210906.15},
  abstract = {Multi-locational trials are critical for establishing stable and adaptable genotypes across different geographic areas prior to considering commercial release. The stability and adaptation of 20 tropical maize hybrids in environments infected with Northern leaf blight disease were assessed using 12 parametric and 14 nonparametric parameters across five environments. The purpose of this research is to estimate the genotype-environment interaction (GEI) for grain yield in selected maize genotypes and to identify associated stability factors to aid in the rationalization of stability analysis in Multi-Environment Trial (MET) data used in breeding programs. Except for De Kroon and Van der Laan (1981), both the combined ANOVA and nonparametric tests of GEI showed significant differences across hybrids, as well as significant crossover and non-crossover interactions. This suggests differential genotypes responses to the test environments. Spearman correlation analysis revealed significant differences between many nonparametric and parametric parameters, indicating that the two may be utilized interchangeably. Additionally, the correlation matrix and principal component analysis results from parametric and nonparametric parameters demonstrated their potential to assess the responses of maize genotypes to changing environments. G13 and G20 appeared most phenotypically stable with associated high mean yield based on the high values expressed by most parametric and nonparametric parameters.},
 year = {2021}
}

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TY - JOUR
T1 - Parametric and Non-parametric Procedures for Identifying Stable and Adapted Tropical Maize Genotypes in NLB Disease Infested Environments
AU - Akinlolu O. Ohunakin
AU - Odiyi Alex C.
AU - Akinyele Benjamin O.
AU - Fayeun Lawrence Stephen
AU - Alake Gideon Collins
Y1 - 2021/12/29
PY - 2021
N1 - https://doi.org/10.11648/j.ajbio.20210906.15
DO - 10.11648/j.ajbio.20210906.15
T2 - American Journal of BioScience
JF - American Journal of BioScience
JO - American Journal of BioScience
SP - 199
EP - 209
PB - Science Publishing Group
SN - 2330-0167
UR - https://doi.org/10.11648/j.ajbio.20210906.15
AB - Multi-locational trials are critical for establishing stable and adaptable genotypes across different geographic areas prior to considering commercial release. The stability and adaptation of 20 tropical maize hybrids in environments infected with Northern leaf blight disease were assessed using 12 parametric and 14 nonparametric parameters across five environments. The purpose of this research is to estimate the genotype-environment interaction (GEI) for grain yield in selected maize genotypes and to identify associated stability factors to aid in the rationalization of stability analysis in Multi-Environment Trial (MET) data used in breeding programs. Except for De Kroon and Van der Laan (1981), both the combined ANOVA and nonparametric tests of GEI showed significant differences across hybrids, as well as significant crossover and non-crossover interactions. This suggests differential genotypes responses to the test environments. Spearman correlation analysis revealed significant differences between many nonparametric and parametric parameters, indicating that the two may be utilized interchangeably. Additionally, the correlation matrix and principal component analysis results from parametric and nonparametric parameters demonstrated their potential to assess the responses of maize genotypes to changing environments. G13 and G20 appeared most phenotypically stable with associated high mean yield based on the high values expressed by most parametric and nonparametric parameters.
VL - 9
IS - 6
ER -

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Author Information

Akinlolu O. Ohunakin

Department of Crop Soil and Pest Management, Federal University of Technology, Akure, Nigeria
Odiyi Alex C.

Department of Crop Soil and Pest Management, Federal University of Technology, Akure, Nigeria
Akinyele Benjamin O.

Department of Crop Soil and Pest Management, Federal University of Technology, Akure, Nigeria
Fayeun Lawrence Stephen

Department of Crop Soil and Pest Management, Federal University of Technology, Akure, Nigeria
Alake Gideon Collins

Department of Entomology and Nematology, University of Florida, Gainesville, USA

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APA Style

Akinlolu O. Ohunakin, Odiyi Alex C., Akinyele Benjamin O., Fayeun Lawrence Stephen, Alake Gideon Collins. (2021). Parametric and Non-parametric Procedures for Identifying Stable and Adapted Tropical Maize Genotypes in NLB Disease Infested Environments. American Journal of BioScience, 9(6), 199-209. https://doi.org/10.11648/j.ajbio.20210906.15

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Akinlolu O. Ohunakin; Odiyi Alex C.; Akinyele Benjamin O.; Fayeun Lawrence Stephen; Alake Gideon Collins. Parametric and Non-parametric Procedures for Identifying Stable and Adapted Tropical Maize Genotypes in NLB Disease Infested Environments. Am. J. BioScience 2021, 9(6), 199-209. doi: 10.11648/j.ajbio.20210906.15

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AMA Style

Akinlolu O. Ohunakin, Odiyi Alex C., Akinyele Benjamin O., Fayeun Lawrence Stephen, Alake Gideon Collins. Parametric and Non-parametric Procedures for Identifying Stable and Adapted Tropical Maize Genotypes in NLB Disease Infested Environments. Am J BioScience. 2021;9(6):199-209. doi: 10.11648/j.ajbio.20210906.15

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@article{10.11648/j.ajbio.20210906.15,
  author = {Akinlolu O. Ohunakin and Odiyi Alex C. and Akinyele Benjamin O. and Fayeun Lawrence Stephen and Alake Gideon Collins},
  title = {Parametric and Non-parametric Procedures for Identifying Stable and Adapted Tropical Maize Genotypes in NLB Disease Infested Environments},
  journal = {American Journal of BioScience},
  volume = {9},
  number = {6},
  pages = {199-209},
  doi = {10.11648/j.ajbio.20210906.15},
  url = {https://doi.org/10.11648/j.ajbio.20210906.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajbio.20210906.15},
  abstract = {Multi-locational trials are critical for establishing stable and adaptable genotypes across different geographic areas prior to considering commercial release. The stability and adaptation of 20 tropical maize hybrids in environments infected with Northern leaf blight disease were assessed using 12 parametric and 14 nonparametric parameters across five environments. The purpose of this research is to estimate the genotype-environment interaction (GEI) for grain yield in selected maize genotypes and to identify associated stability factors to aid in the rationalization of stability analysis in Multi-Environment Trial (MET) data used in breeding programs. Except for De Kroon and Van der Laan (1981), both the combined ANOVA and nonparametric tests of GEI showed significant differences across hybrids, as well as significant crossover and non-crossover interactions. This suggests differential genotypes responses to the test environments. Spearman correlation analysis revealed significant differences between many nonparametric and parametric parameters, indicating that the two may be utilized interchangeably. Additionally, the correlation matrix and principal component analysis results from parametric and nonparametric parameters demonstrated their potential to assess the responses of maize genotypes to changing environments. G13 and G20 appeared most phenotypically stable with associated high mean yield based on the high values expressed by most parametric and nonparametric parameters.},
 year = {2021}
}

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