Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model

A flexible and user-friendly spatial method called SpATS performed comparably to more elaborate and trial-specific spatial models in a series of sorghum breeding trials. Adjustment for spatial trends in plant breeding field trials is essential for efficient evaluation and selection of genotypes. Cur...

Descripción completa

Detalles Bibliográficos
Autores: Velazco, Julio Gabriel, Rodríguez-Álvarez, María Xosé, Boer, Martin P., Jordan, David R., Eilers, Paul H. C., Malosetti, Marcos, Van Eeuwijk, Fred A.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2017
País:Argentina
Institución:Instituto Nacional de Tecnología Agropecuaria
Repositorio:INTA Digital (INTA)
Idioma:inglés
OAI Identifier:oai:localhost:20.500.12123/8287
Acceso en línea:http://hdl.handle.net/20.500.12123/8287
https://link.springer.com/article/10.1007/s00122-017-2894-4
https://doi.org/10.1007/s00122-017-2894-4
Access Level:acceso abierto
Palabra clave:Sorgo
Sorghum
Espaciamiento
Manejo del Cultivo
Ensayo
Forrajes
Spacing
Crop Management
Testing
Forage
id AR_0cf330e1dd5372016351cdfdbca10e01
oai_identifier_str oai:localhost:20.500.12123/8287
network_acronym_str AR
network_name_str Argentina
repository_id_str
spelling Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed modelVelazco, Julio GabrielRodríguez-Álvarez, María XoséBoer, Martin P.Jordan, David R.Eilers, Paul H. C.Malosetti, MarcosVan Eeuwijk, Fred A.SorgoSorghumEspaciamientoManejo del CultivoEnsayoForrajesSpacingCrop ManagementTestingForageA flexible and user-friendly spatial method called SpATS performed comparably to more elaborate and trial-specific spatial models in a series of sorghum breeding trials. Adjustment for spatial trends in plant breeding field trials is essential for efficient evaluation and selection of genotypes. Current mixed model methods of spatial analysis are based on a multi-step modelling process where global and local trends are fitted after trying several candidate spatial models. This paper reports the application of a novel spatial method that accounts for all types of continuous field variation in a single modelling step by fitting a smooth surface. The method uses two-dimensional P-splines with anisotropic smoothing formulated in the mixed model framework, referred to as SpATS model. We applied this methodology to a series of large and partially replicated sorghum breeding trials. The new model was assessed in comparison with the more elaborate standard spatial models that use autoregressive correlation of residuals. The improvements in precision and the predictions of genotypic values produced by the SpATS model were equivalent to those obtained using the best fitting standard spatial models for each trial. One advantage of the approach with SpATS is that all patterns of spatial trend and genetic effects were modelled simultaneously by fitting a single model. Furthermore, we used a flexible model to adequately adjust for field trends. This strategy reduces potential parameter identification problems and simplifies the model selection process. Therefore, the new method should be considered as an efficient and easy-to-use alternative for routine analyses of plant breeding trials.EEA PergaminoFil: Velazco, Julio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Sección Forrajeras; Argentina. Wageningen University and Research . Biometris – Mathematical and Statistical Methods; HolandaFil: Rodríguez-Álvarez, María Xosé. Basque Center for Applied Mathematics(BCAM); España. IKERBASQUE. Basque Foundation for Science. EspañaFil: Boer, Martin P. Wageningen University and Research . Biometris – Mathematical and Statistical Methods; HolandaFil: Jordan, David R. The University of Queensland. Hermitage Research Facility. Queensland Alliance for Agriculture and Food Innovation; AustraliaFil: Eilers, Paul H. C. Erasmus University Medical Centre; HolandaFil: Malosetti, Marcos. Wageningen University and Research . Biometris – Mathematical and Statistical Methods; HolandaFil: van Eeuwijk, Fred A. Wageningen University and Research . Biometris – Mathematical and Statistical Methods; HolandaSpringer2020-11-18T16:49:21Z2020-11-18T16:49:21Z2017-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/8287https://link.springer.com/article/10.1007/s00122-017-2894-40040-57521432-2242 (online)https://doi.org/10.1007/s00122-017-2894-4Theoretical and Applied Genetics 130 (7) : 1375-1392 (July 2017)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2024-05-15T12:24:43Zoai:localhost:20.500.12123/8287instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2024-05-15 12:24:43.598INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model
title Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model
spellingShingle Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model
Velazco, Julio Gabriel
Sorgo
Sorghum
Espaciamiento
Manejo del Cultivo
Ensayo
Forrajes
Spacing
Crop Management
Testing
Forage
title_short Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model
title_full Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model
title_fullStr Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model
title_full_unstemmed Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model
title_sort Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model
dc.creator.none.fl_str_mv Velazco, Julio Gabriel
Rodríguez-Álvarez, María Xosé
Boer, Martin P.
Jordan, David R.
Eilers, Paul H. C.
Malosetti, Marcos
Van Eeuwijk, Fred A.
author Velazco, Julio Gabriel
author_facet Velazco, Julio Gabriel
Rodríguez-Álvarez, María Xosé
Boer, Martin P.
Jordan, David R.
Eilers, Paul H. C.
Malosetti, Marcos
Van Eeuwijk, Fred A.
author_role author
author2 Rodríguez-Álvarez, María Xosé
Boer, Martin P.
Jordan, David R.
Eilers, Paul H. C.
Malosetti, Marcos
Van Eeuwijk, Fred A.
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Sorgo
Sorghum
Espaciamiento
Manejo del Cultivo
Ensayo
Forrajes
Spacing
Crop Management
Testing
Forage
topic Sorgo
Sorghum
Espaciamiento
Manejo del Cultivo
Ensayo
Forrajes
Spacing
Crop Management
Testing
Forage
description A flexible and user-friendly spatial method called SpATS performed comparably to more elaborate and trial-specific spatial models in a series of sorghum breeding trials. Adjustment for spatial trends in plant breeding field trials is essential for efficient evaluation and selection of genotypes. Current mixed model methods of spatial analysis are based on a multi-step modelling process where global and local trends are fitted after trying several candidate spatial models. This paper reports the application of a novel spatial method that accounts for all types of continuous field variation in a single modelling step by fitting a smooth surface. The method uses two-dimensional P-splines with anisotropic smoothing formulated in the mixed model framework, referred to as SpATS model. We applied this methodology to a series of large and partially replicated sorghum breeding trials. The new model was assessed in comparison with the more elaborate standard spatial models that use autoregressive correlation of residuals. The improvements in precision and the predictions of genotypic values produced by the SpATS model were equivalent to those obtained using the best fitting standard spatial models for each trial. One advantage of the approach with SpATS is that all patterns of spatial trend and genetic effects were modelled simultaneously by fitting a single model. Furthermore, we used a flexible model to adequately adjust for field trends. This strategy reduces potential parameter identification problems and simplifies the model selection process. Therefore, the new method should be considered as an efficient and easy-to-use alternative for routine analyses of plant breeding trials.
publishDate 2017
dc.date.none.fl_str_mv 2017-04
2020-11-18T16:49:21Z
2020-11-18T16:49:21Z
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12123/8287
https://link.springer.com/article/10.1007/s00122-017-2894-4
0040-5752
1432-2242 (online)
https://doi.org/10.1007/s00122-017-2894-4
url http://hdl.handle.net/20.500.12123/8287
https://link.springer.com/article/10.1007/s00122-017-2894-4
https://doi.org/10.1007/s00122-017-2894-4
identifier_str_mv 0040-5752
1432-2242 (online)
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv Theoretical and Applied Genetics 130 (7) : 1375-1392 (July 2017)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
instname_str Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
_version_ 1799197068145721344
score 15,811543

Similares en LA Referencia