Cargando…

Characterization of Groundnut (Arachis hypogaea L.) Test Locations Using Representative Testing Environments With Farmer-Preferred Traits

In this study, the differential rankings of 36 groundnut genotypes under varying environmental conditions were studied at various levels of phenotype. Locations that are generally accepted by the crop- and soil-based research community to represent the entire Guinea and Sudan Savanna agro-ecological...

Descripción completa

Detalles Bibliográficos
Autores principales: Oteng-Frimpong, Richard, Kassim, Yussif Baba, Puozaa, Doris Kanvenaa, Nboyine, Jerry Asalma, Issah, Abdul-Rashid, Rasheed, Masawudu Abdul, Adjebeng-Danquah, Joseph, Kusi, Francis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8006269/
https://www.ncbi.nlm.nih.gov/pubmed/33790928
http://dx.doi.org/10.3389/fpls.2021.637860
_version_ 1783672279089020928
author Oteng-Frimpong, Richard
Kassim, Yussif Baba
Puozaa, Doris Kanvenaa
Nboyine, Jerry Asalma
Issah, Abdul-Rashid
Rasheed, Masawudu Abdul
Adjebeng-Danquah, Joseph
Kusi, Francis
author_facet Oteng-Frimpong, Richard
Kassim, Yussif Baba
Puozaa, Doris Kanvenaa
Nboyine, Jerry Asalma
Issah, Abdul-Rashid
Rasheed, Masawudu Abdul
Adjebeng-Danquah, Joseph
Kusi, Francis
author_sort Oteng-Frimpong, Richard
collection PubMed
description In this study, the differential rankings of 36 groundnut genotypes under varying environmental conditions were studied at various levels of phenotype. Locations that are generally accepted by the crop- and soil-based research community to represent the entire Guinea and Sudan Savanna agro-ecological zones in Ghana were characterized, this time using a crop. The characterization was done based on four farmer-preferred traits (early and late leaf spot disease ratings, and haulm and pod yields) using three models (i.e., AMMI, GGE, and Finlay–Wilkinson regression). These models were used to capture specific levels of phenotype, namely, genotype-by-environment interaction (GE), genotype main effect plus GE (G+GE), and environment and genotype main effects plus GE (E+G+GE), respectively. The effect of three major environmental covariables was also determined using factorial regression. Location main effect was found to be highly significant (p < 0.001), confirming its importance in cultivar placement. However, unlike genotypes where the best is usually adjudged through statistical ranking, locations are judged against a benchmark, particularly when phenotyping for disease severity. It was also found that the locations represent one complex mega-environment, justifying the need to test new technologies, including genotypes in all of them before they can be approved for adoption nationally. Again, depending on the phenotypic level considered, genotypic rankings may change, causing environmental groupings to change. For instance, all locations clustered to form one group in 2017 for early and late leaf spot diseases and pod yield when GE was considered, but the groupings changed when G+GE was considered for the same traits in the same year. As a result, assessing genotypic performance at the various levels to arrive at a consensus decision is suggested. Genotypes ICGV-IS 141120 and ICGV-IS 13937 were found to be the best performing.
format Online
Article
Text
id pubmed-8006269
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-80062692021-03-30 Characterization of Groundnut (Arachis hypogaea L.) Test Locations Using Representative Testing Environments With Farmer-Preferred Traits Oteng-Frimpong, Richard Kassim, Yussif Baba Puozaa, Doris Kanvenaa Nboyine, Jerry Asalma Issah, Abdul-Rashid Rasheed, Masawudu Abdul Adjebeng-Danquah, Joseph Kusi, Francis Front Plant Sci Plant Science In this study, the differential rankings of 36 groundnut genotypes under varying environmental conditions were studied at various levels of phenotype. Locations that are generally accepted by the crop- and soil-based research community to represent the entire Guinea and Sudan Savanna agro-ecological zones in Ghana were characterized, this time using a crop. The characterization was done based on four farmer-preferred traits (early and late leaf spot disease ratings, and haulm and pod yields) using three models (i.e., AMMI, GGE, and Finlay–Wilkinson regression). These models were used to capture specific levels of phenotype, namely, genotype-by-environment interaction (GE), genotype main effect plus GE (G+GE), and environment and genotype main effects plus GE (E+G+GE), respectively. The effect of three major environmental covariables was also determined using factorial regression. Location main effect was found to be highly significant (p < 0.001), confirming its importance in cultivar placement. However, unlike genotypes where the best is usually adjudged through statistical ranking, locations are judged against a benchmark, particularly when phenotyping for disease severity. It was also found that the locations represent one complex mega-environment, justifying the need to test new technologies, including genotypes in all of them before they can be approved for adoption nationally. Again, depending on the phenotypic level considered, genotypic rankings may change, causing environmental groupings to change. For instance, all locations clustered to form one group in 2017 for early and late leaf spot diseases and pod yield when GE was considered, but the groupings changed when G+GE was considered for the same traits in the same year. As a result, assessing genotypic performance at the various levels to arrive at a consensus decision is suggested. Genotypes ICGV-IS 141120 and ICGV-IS 13937 were found to be the best performing. Frontiers Media S.A. 2021-03-15 /pmc/articles/PMC8006269/ /pubmed/33790928 http://dx.doi.org/10.3389/fpls.2021.637860 Text en Copyright © 2021 Oteng-Frimpong, Kassim, Puozaa, Nboyine, Issah, Rasheed, Adjebeng-Danquah and Kusi. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Oteng-Frimpong, Richard
Kassim, Yussif Baba
Puozaa, Doris Kanvenaa
Nboyine, Jerry Asalma
Issah, Abdul-Rashid
Rasheed, Masawudu Abdul
Adjebeng-Danquah, Joseph
Kusi, Francis
Characterization of Groundnut (Arachis hypogaea L.) Test Locations Using Representative Testing Environments With Farmer-Preferred Traits
title Characterization of Groundnut (Arachis hypogaea L.) Test Locations Using Representative Testing Environments With Farmer-Preferred Traits
title_full Characterization of Groundnut (Arachis hypogaea L.) Test Locations Using Representative Testing Environments With Farmer-Preferred Traits
title_fullStr Characterization of Groundnut (Arachis hypogaea L.) Test Locations Using Representative Testing Environments With Farmer-Preferred Traits
title_full_unstemmed Characterization of Groundnut (Arachis hypogaea L.) Test Locations Using Representative Testing Environments With Farmer-Preferred Traits
title_short Characterization of Groundnut (Arachis hypogaea L.) Test Locations Using Representative Testing Environments With Farmer-Preferred Traits
title_sort characterization of groundnut (arachis hypogaea l.) test locations using representative testing environments with farmer-preferred traits
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8006269/
https://www.ncbi.nlm.nih.gov/pubmed/33790928
http://dx.doi.org/10.3389/fpls.2021.637860
work_keys_str_mv AT otengfrimpongrichard characterizationofgroundnutarachishypogaealtestlocationsusingrepresentativetestingenvironmentswithfarmerpreferredtraits
AT kassimyussifbaba characterizationofgroundnutarachishypogaealtestlocationsusingrepresentativetestingenvironmentswithfarmerpreferredtraits
AT puozaadoriskanvenaa characterizationofgroundnutarachishypogaealtestlocationsusingrepresentativetestingenvironmentswithfarmerpreferredtraits
AT nboyinejerryasalma characterizationofgroundnutarachishypogaealtestlocationsusingrepresentativetestingenvironmentswithfarmerpreferredtraits
AT issahabdulrashid characterizationofgroundnutarachishypogaealtestlocationsusingrepresentativetestingenvironmentswithfarmerpreferredtraits
AT rasheedmasawuduabdul characterizationofgroundnutarachishypogaealtestlocationsusingrepresentativetestingenvironmentswithfarmerpreferredtraits
AT adjebengdanquahjoseph characterizationofgroundnutarachishypogaealtestlocationsusingrepresentativetestingenvironmentswithfarmerpreferredtraits
AT kusifrancis characterizationofgroundnutarachishypogaealtestlocationsusingrepresentativetestingenvironmentswithfarmerpreferredtraits