Sparse multi-trait genomic prediction under balanced incomplete block design

dc.creatorMontesinos-Lopez, O.A.
dc.creatorMosqueda-Gonzalez, B.A.
dc.creatorSalinas-Ruiz, J.
dc.creatorMontesinos-Lopez, A.
dc.creatorCrossa, J.
dc.date2023-03-10T20:10:12Z
dc.date2023-03-10T20:10:12Z
dc.date2023
dc.date.accessioned2023-07-17T20:10:28Z
dc.date.available2023-07-17T20:10:28Z
dc.identifierhttps://hdl.handle.net/10883/22536
dc.identifier10.1002/tpg2.20305
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7514279
dc.descriptionSparse testing is essential to increase the efficiency of the genomic selection methodology, as the same efficiency (in this case prediction power) can be obtained while using less genotypes evaluated in the fields. For this reason, it is important to evaluate the existing methods for performing the allocation of lines to environments. With this goal, four methods (M1–M4) to allocate lines to environments were evaluated under the context of a multi-trait genomic prediction problem: M1 denotes the allocation of a fraction (subset) of lines in all locations, M2 denotes the allocation of a fraction of lines with some shared lines in locations but not arranged based on the balanced incomplete block design (BIBD) principle, M3 denotes the random allocation of a subset of lines to locations, and M4 denotes the allocation of a subset of lines to locations using the BIBD principle. The evaluation was done using seven real multi-environment data sets common in plant breeding programs. We found that the best method was M4 and the worst was M1, while no important differences were found between M3 and M4. We concluded that M4 and M3 are efficient in the context of sparse testing for multi-trait prediction.
dc.languageEnglish
dc.publisherWiley
dc.rightsCIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose
dc.rightsOpen Access
dc.sourceIn press
dc.source1940-3372
dc.sourcePlant Genome
dc.subjectAGRICULTURAL SCIENCES AND BIOTECHNOLOGY
dc.subjectSparse Testing
dc.subjectAllocation of Lines
dc.subjectBalanced Incomplete Block Design
dc.subjectGENOMICS
dc.subjectPLANT BREEDING
dc.subjectMARKER-ASSISTED SELECTION
dc.subjectBREEDING PROGRAMMES
dc.subjectGenetic Resources
dc.titleSparse multi-trait genomic prediction under balanced incomplete block design
dc.typeArticle
dc.typePublished Version
dc.coverageUSA


Este ítem pertenece a la siguiente institución