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dc.contributorAbdalla, Abdelwahaben_US
dc.contributorCeccarelli, Salvatoreen_US
dc.contributorGrando, Stefaniaen_US
dc.contributorSingh, Murarien_US
dc.creatorOmer, Siraj Osmanen_US
dc.date2014-01-28en_US
dc.date.accessioned2017-07-24T01:06:16Z
dc.date.available2017-07-24T01:06:16Z
dc.identifierhttps://www.researchgate.net/publication/282184264_Bayesian_estimation_of_heritability_and_genetic_gain_for_subsets_of_genotypes_evaluated_in_a_larger_set_of_genotypes_in_a_block_designen_US
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/iY9KkQILen_US
dc.identifier.citationSiraj Osman Omer, Abdelwahab Abdalla, Salvatore Ceccarelli, Stefania Grando, Murari Singh. (28/1/2014). Bayesian estimation of heritability and genetic gain for subsets of genotypes evaluated in a larger set of genotypes in a block design. European journal of experimental biology, 4 (3), pp. 566-575.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/7302
dc.description.abstractThere are situations in which a number of inbred lines are found grouped into classes, depending on their origin and phenology. Interest in such situations lies in the estimation of genotypic variations between the genotypes from individual groups, whereas all genotypes are evaluated in a single trial conducted in a randomized complete block design (RCBD) or an incomplete block design (IBD). The objective of this study was to apply a Bayesian approach to estimate genotypic variation, heritability, and genetic advances within individual groups of groups of genotypes. A set of 360 barley genotypes were evaluated in a two replicate alpha-design with blocks of 10 plots each. The standard frequentist method to estimate variance components was carried out by the restricted maximum likelihood method on the days to flower data from the IBD as well as by an RCBD by ignoring the incomplete blocks. The Bayesian approach with selection of best priors was implemented for the estimation. We noticed a substantial difference in the estimates of the various genetic parameters across the groups. The estimation of variations between the genotypes from individual groups (RCBD or IBD) is needed as the basis of many agricultural research or plant breeding/agronomy trials. The Bayesian approach uses broader inference framework to integrate the prior information on parameters with the likelihood of the current data. Therefore, the Bayesian approach presented here for estimation of heritability and genetic gain for subsets of genotypes evaluated in a larger set of genotypes in the block design is recommended for use in similar situations.en_US
dc.formatDOCXen_US
dc.languageenen_US
dc.publisherPelagia Research Libraryen_US
dc.rightsCC-BY-NC-4.0en_US
dc.sourceEuropean journal of experimental biology;4,(2014) Pagination 566,575en_US
dc.subjectbayesian estimationen_US
dc.subjectgenotypic varianceen_US
dc.titleBayesian estimation of heritability and genetic gain for subsets of genotypes evaluated in a larger set of genotypes in a block designen_US
dc.typeJournal Articleen_US
cg.creator.idSingh, Murari: 0000-0001-5450-0949en_US
cg.creator.ID-typeORCIDen_US
cg.subject.agrovocgenetic advanceen_US
cg.subject.agrovoccollective actionen_US
cg.subject.agrovocheritabilityen_US
cg.contributor.centerAgricultural Research Corporation - ARC Sudanen_US
cg.contributor.centerUniversity of Khartoum - UofKen_US
cg.contributor.centerRete Semi Ruralien_US
cg.contributor.centerInternational Crops Research Institute for the Semi-Arid Tropics - ICRISATen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.crpCGIAR Research Program on Dryland Systems - DSen_US
cg.contributor.funderInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.projectCommunication and Documentation Information Services (CODIS)en_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.regionSouthern Asiaen_US
cg.coverage.countryINen_US
cg.contactM.SINGH@CGIAR.ORGen_US
dc.identifier.statusOpen accessen_US


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