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dc.contributor.authorSelle, Maria
dc.contributor.authorSteinsland, Ingelin
dc.contributor.authorGorjanc, Gregor
dc.contributor.authorHickey, John M.
dc.date.accessioned2019-12-02T09:08:30Z
dc.date.available2019-12-02T09:08:30Z
dc.date.created2019-10-21T13:40:17Z
dc.date.issued2019
dc.identifier.issn0040-5752
dc.identifier.urihttp://hdl.handle.net/11250/2631198
dc.description.abstractThe objective of this paper was to fit different established spatial models for analysing agricultural field trials using the open-source R package INLA. Spatial variation is common in field trials, and accounting for it increases the accuracy of estimated genetic effects. However, this is still hindered by the lack of available software implementations. We compare some established spatial models and show possibilities for flexible modelling with respect to field trial design and joint modelling over multiple years and locations. We use a Bayesian framework and for statistical inference the integrated nested Laplace approximations (INLA) implemented in the R package INLA. The spatial models we use are the well-known independent row and column effects, separable first-order autoregressive ( AR1⊗AR1 ) models and a Gaussian random field (Matérn) model that is approximated via the stochastic partial differential equation approach. The Matérn model can accommodate flexible field trial designs and yields interpretable parameters. We test the models in a simulation study imitating a wheat breeding programme with different levels of spatial variation, with and without genome-wide markers and with combining data over two locations, modelling spatial and genetic effects jointly. The results show comparable predictive performance for both the AR1⊗AR1 and the Matérn models. We also present an example of fitting the models to a real wheat breeding data and simulated tree breeding data with the Nelder wheel design to show the flexibility of the Matérn model and the R package INLA.nb_NO
dc.language.isoengnb_NO
dc.publisherSpringer Verlagnb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleFlexible modelling of spatial variation in agricultural field trials with the R package INLAnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.journalTheoretical and Applied Geneticsnb_NO
dc.identifier.doi10.1007/s00122-019-03424-y
dc.identifier.cristin1739065
dc.description.localcode© The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.nb_NO
cristin.unitcode194,63,15,0
cristin.unitnameInstitutt for matematiske fag
cristin.ispublishedtrue
cristin.qualitycode2


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