Multivariate genomic analysis and optimal contribution selection predicts high genetic gains in cooking time, iron, zinc and grain yield in common beans in East Africadoi:10.7910/DVN/TSEZVGHarvard Dataverse2022-01-061Mukankusi, Clare, 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]Multivariate genomic analysis and optimal contribution selection predicts high genetic gains in cooking time, iron, zinc and grain yield in common beans in East Africadoi:10.7910/DVN/TSEZVGMukankusi, ClareThe Alliance of Bioversity International and CIATCROP/2018/132Harvard DataverseAlliance Data ManagementCruz Arias, Paola Andrea2021-12-212021-10-28Agricultural Sciencesgenomicsoptimal contribution selectionAfricaCrops for nutrition and healthCommon Bean/PABRACGIAR Research Program on Grain Legumes and Dryland Cerealscrop improvementPhenotypic 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 ACIAR2015201820152018East AfricaExperimental DataPhenomic DataGenomic DataMethodology: Phenotypic data were obtained from 898 germplasm entries of bush and climbing types of common bean evaluated in 33 field trials of common bean grown in different years (2015 to 2018) and different locations in East Africa. The locations were Kawanda (0° 25’ N, 32° 31’ E, elevation 1190 m above sea level) and Kachwekano (1° 15′ S, 29° 57′ E, elevation 2200 m above sea level) in Uganda, and Kagera (2° 08' S, 33° 26' E, elevation 1320 m above sea level) in Tanzania. From the 33 field trials, GY (kg ha-1) was available from 32 trials, with laboratory evaluation of Fe and Zn (mg kg-1) from 29 trials and CKT (min) from 14 trials. The genotypic data include two panels: Panel 1 with 94 genotypes was a 770 SNP array (Raatz et al., 2019); Panel 2 was more than 20,000 SNPs with 298 genotypes based on Diversity Array Technology analysed by the Integrated Genotyping Service and Support platform (IGSS), a genotyping service facility based in Nairobi, Kenya (as used by Nkhata et al. 2020).<P><a rel="license" href="http://creativecommons.org/licenses/by/4.0/" target="_blank"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br /> These data and documents are licensed under a <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank"> Creative Commons Attribution 4.0 International license.</a> You may copy, distribute and transmit the data as long as you acknowledge the source through proper <a href="http://best-practices.dataverse.org/data-citation/" target="_blank">data citation</a>.</P>Multivariate genomic analysis and optimal 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