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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| Formato: | Conjunto de datos |
| Lenguaje: | Inglés |
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2022
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| Acceso en línea: | https://hdl.handle.net/10568/118434 |
| _version_ | 1855530114129854464 |
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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 |
| id | CGSpace118434 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| record_format | dspace |
| 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 |
| work_keys_str_mv | AT mukankusiclare multivariategenomicanalysisandoptimalcontributionselectionpredictshighgeneticgainsincookingtimeironzincandgrainyieldincommonbeansineastafrica |