Multivariate genomic analysis and optimal contribution selection predicts high genetic gains in cooking time, iron, zinc and grain yield in common beans in East Africa

Phenotypic and Genotypic data based on 358 genotypes used to estimate genomic estimated breeding values (GEBV’s) for cooking time (CKT) Seed iron content (SeedFe), Seed Zin content (SeedZn) and Grain yield (GY). The data was used to select parents for the Rapid bean cooking project (RCBP) supported...

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Autor principal: Mukankusi, Clare
Formato: Conjunto de datos
Lenguaje:Inglés
Publicado: 2022
Materias:
Acceso en línea:https://hdl.handle.net/10568/118434
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author Mukankusi, Clare
author_browse Mukankusi, Clare
author_facet Mukankusi, Clare
author_sort Mukankusi, Clare
collection Repository of Agricultural Research Outputs (CGSpace)
description Phenotypic and Genotypic data based on 358 genotypes used to estimate genomic estimated breeding values (GEBV’s) for cooking time (CKT) Seed iron content (SeedFe), Seed Zin content (SeedZn) and Grain yield (GY). The data was used to select parents for the Rapid bean cooking project (RCBP) supported by the ACIAR
format Conjunto de datos
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institution CGIAR Consortium
language Inglés
publishDate 2022
publishDateRange 2022
publishDateSort 2022
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spelling CGSpace1184342024-04-25T06:01:14Z Multivariate genomic analysis and optimal contribution selection predicts high genetic gains in cooking time, iron, zinc and grain yield in common beans in East Africa Mukankusi, Clare genomics breeding value cooking methods genómica valor genético Phenotypic and Genotypic data based on 358 genotypes used to estimate genomic estimated breeding values (GEBV’s) for cooking time (CKT) Seed iron content (SeedFe), Seed Zin content (SeedZn) and Grain yield (GY). The data was used to select parents for the Rapid bean cooking project (RCBP) supported by the ACIAR 2022-01-06 2022-03-22T09:51:19Z 2022-03-22T09:51:19Z Dataset https://hdl.handle.net/10568/118434 en Open Access Mukankusi, C. (2022) "Multivariate genomic analysis and optimal contribution selection predicts high genetic gains in cooking time, iron, zinc and grain yield in common beans in East Africa", https://doi.org/10.7910/DVN/TSEZVG, Harvard Dataverse, V1, UNF:6:XGZWlNTH5nd5eCPjcbvwAw== [fileUNF]
spellingShingle genomics
breeding value
cooking methods
genómica
valor genético
Mukankusi, Clare
Multivariate genomic analysis and optimal contribution selection predicts high genetic gains in cooking time, iron, zinc and grain yield in common beans in East Africa
title Multivariate genomic analysis and optimal contribution selection predicts high genetic gains in cooking time, iron, zinc and grain yield in common beans in East Africa
title_full Multivariate genomic analysis and optimal contribution selection predicts high genetic gains in cooking time, iron, zinc and grain yield in common beans in East Africa
title_fullStr Multivariate genomic analysis and optimal contribution selection predicts high genetic gains in cooking time, iron, zinc and grain yield in common beans in East Africa
title_full_unstemmed Multivariate genomic analysis and optimal contribution selection predicts high genetic gains in cooking time, iron, zinc and grain yield in common beans in East Africa
title_short Multivariate genomic analysis and optimal contribution selection predicts high genetic gains in cooking time, iron, zinc and grain yield in common beans in East Africa
title_sort multivariate genomic analysis and optimal contribution selection predicts high genetic gains in cooking time iron zinc and grain yield in common beans in east africa
topic genomics
breeding value
cooking methods
genómica
valor genético
url https://hdl.handle.net/10568/118434
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