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RGB-image method enables indirect selection for leaf spot resistance and yield estimation in a groundnut breeding program in Western Africa
Early Leaf Spot (ELS) caused by the fungus Passalora arachidicola and Late Leaf Spot (LLS) also caused by the fungus Nothopassalora personata, are the two major groundnut (Arachis hypogaea L.) destructive diseases in Ghana. Accurate phenotyping and genotyping to develop groundnut genotypes resistant...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9387199/ https://www.ncbi.nlm.nih.gov/pubmed/35991399 http://dx.doi.org/10.3389/fpls.2022.957061 |
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author | Sie, Emmanuel Kofi Oteng-Frimpong, Richard Kassim, Yussif Baba Puozaa, Doris Kanvenaa Adjebeng-Danquah, Joseph Masawudu, Abdul Rasheed Ofori, Kwadwo Danquah, Agyemang Cazenave, Alexandre Brice Hoisington, David Rhoads, James Balota, Maria |
author_facet | Sie, Emmanuel Kofi Oteng-Frimpong, Richard Kassim, Yussif Baba Puozaa, Doris Kanvenaa Adjebeng-Danquah, Joseph Masawudu, Abdul Rasheed Ofori, Kwadwo Danquah, Agyemang Cazenave, Alexandre Brice Hoisington, David Rhoads, James Balota, Maria |
author_sort | Sie, Emmanuel Kofi |
collection | PubMed |
description | Early Leaf Spot (ELS) caused by the fungus Passalora arachidicola and Late Leaf Spot (LLS) also caused by the fungus Nothopassalora personata, are the two major groundnut (Arachis hypogaea L.) destructive diseases in Ghana. Accurate phenotyping and genotyping to develop groundnut genotypes resistant to Leaf Spot Diseases (LSD) and to increase groundnut production is critically important in Western Africa. Two experiments were conducted at the Council for Scientific and Industrial Research-Savanna Agricultural Research Institute located in Nyankpala, Ghana to explore the effectiveness of using RGB-image method as a high-throughput phenotyping tool to assess groundnut LSD and to estimate yield components. Replicated plots arranged in a rectangular alpha lattice design were conducted during the 2020 growing season using a set of 60 genotypes as the training population and 192 genotypes for validation. Indirect selection models were developed using Red-Green-Blue (RGB) color space indices. Data was collected on conventional LSD ratings, RGB imaging, pod weight per plant and number of pods per plant. Data was analyzed using a mixed linear model with R statistical software version 4.0.2. The results showed differences among the genotypes for the traits evaluated. The RGB-image method traits exhibited comparable or better broad sense heritability to the conventionally measured traits. Significant correlation existed between the RGB-image method traits and the conventionally measured traits. Genotypes 73–33, Gha-GAF 1723, Zam-ICGV-SM 07599, and Oug-ICGV 90099 were among the most resistant genotypes to ELS and LLS, and they represent suitable sources of resistance to LSD for the groundnut breeding programs in Western Africa. |
format | Online Article Text |
id | pubmed-9387199 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93871992022-08-19 RGB-image method enables indirect selection for leaf spot resistance and yield estimation in a groundnut breeding program in Western Africa Sie, Emmanuel Kofi Oteng-Frimpong, Richard Kassim, Yussif Baba Puozaa, Doris Kanvenaa Adjebeng-Danquah, Joseph Masawudu, Abdul Rasheed Ofori, Kwadwo Danquah, Agyemang Cazenave, Alexandre Brice Hoisington, David Rhoads, James Balota, Maria Front Plant Sci Plant Science Early Leaf Spot (ELS) caused by the fungus Passalora arachidicola and Late Leaf Spot (LLS) also caused by the fungus Nothopassalora personata, are the two major groundnut (Arachis hypogaea L.) destructive diseases in Ghana. Accurate phenotyping and genotyping to develop groundnut genotypes resistant to Leaf Spot Diseases (LSD) and to increase groundnut production is critically important in Western Africa. Two experiments were conducted at the Council for Scientific and Industrial Research-Savanna Agricultural Research Institute located in Nyankpala, Ghana to explore the effectiveness of using RGB-image method as a high-throughput phenotyping tool to assess groundnut LSD and to estimate yield components. Replicated plots arranged in a rectangular alpha lattice design were conducted during the 2020 growing season using a set of 60 genotypes as the training population and 192 genotypes for validation. Indirect selection models were developed using Red-Green-Blue (RGB) color space indices. Data was collected on conventional LSD ratings, RGB imaging, pod weight per plant and number of pods per plant. Data was analyzed using a mixed linear model with R statistical software version 4.0.2. The results showed differences among the genotypes for the traits evaluated. The RGB-image method traits exhibited comparable or better broad sense heritability to the conventionally measured traits. Significant correlation existed between the RGB-image method traits and the conventionally measured traits. Genotypes 73–33, Gha-GAF 1723, Zam-ICGV-SM 07599, and Oug-ICGV 90099 were among the most resistant genotypes to ELS and LLS, and they represent suitable sources of resistance to LSD for the groundnut breeding programs in Western Africa. Frontiers Media S.A. 2022-08-04 /pmc/articles/PMC9387199/ /pubmed/35991399 http://dx.doi.org/10.3389/fpls.2022.957061 Text en Copyright © 2022 Sie, Oteng-Frimpong, Kassim, Puozaa, Adjebeng-Danquah, Masawudu, Ofori, Danquah, Cazenave, Hoisington, Rhoads and Balota. https://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 Sie, Emmanuel Kofi Oteng-Frimpong, Richard Kassim, Yussif Baba Puozaa, Doris Kanvenaa Adjebeng-Danquah, Joseph Masawudu, Abdul Rasheed Ofori, Kwadwo Danquah, Agyemang Cazenave, Alexandre Brice Hoisington, David Rhoads, James Balota, Maria RGB-image method enables indirect selection for leaf spot resistance and yield estimation in a groundnut breeding program in Western Africa |
title | RGB-image method enables indirect selection for leaf spot resistance and yield estimation in a groundnut breeding program in Western Africa |
title_full | RGB-image method enables indirect selection for leaf spot resistance and yield estimation in a groundnut breeding program in Western Africa |
title_fullStr | RGB-image method enables indirect selection for leaf spot resistance and yield estimation in a groundnut breeding program in Western Africa |
title_full_unstemmed | RGB-image method enables indirect selection for leaf spot resistance and yield estimation in a groundnut breeding program in Western Africa |
title_short | RGB-image method enables indirect selection for leaf spot resistance and yield estimation in a groundnut breeding program in Western Africa |
title_sort | rgb-image method enables indirect selection for leaf spot resistance and yield estimation in a groundnut breeding program in western africa |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9387199/ https://www.ncbi.nlm.nih.gov/pubmed/35991399 http://dx.doi.org/10.3389/fpls.2022.957061 |
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