title: Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model.
abstract: 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.
authors.affiliation: Biometris, Wageningen University and Research, P.O. Box 16, 6700 AA, Wageningen, The Netherlands.|Department of Plant Breeding, National Institute of Agricultural Technology (INTA), B2700WAA, EEA Pergamino, Buenos Aires, Argentina.
authors.forename: Julio G
authors.identifier: http://orcid.org/0000-0001-6061-9997
authors.initials: JG
authors.lastname: Velazco
authors.affiliation: BCAM, Basque Center for Applied Mathematics, Bilbao, Spain.|IKERBASQUE, Basque Foundation for Science, Bilbao, Spain.
authors.forename: María Xosé
authors.initials: MX
authors.lastname: Rodríguez-Álvarez
authors.affiliation: Biometris, Wageningen University and Research, P.O. Box 16, 6700 AA, Wageningen, The Netherlands.
authors.forename: Martin P
authors.initials: MP
authors.lastname: Boer
authors.affiliation: Queensland Alliance for Agriculture and Food Innovation, Hermitage Research Facility, The University of Queensland, Warwick, QLD, 4370, Australia.
authors.forename: David R
authors.initials: DR
authors.lastname: Jordan
authors.affiliation: Erasmus University Medical Centre, Rotterdam, The Netherlands.
authors.forename: Paul H C
authors.initials: PHC
authors.lastname: Eilers
authors.affiliation: Biometris, Wageningen University and Research, P.O. Box 16, 6700 AA, Wageningen, The Netherlands.
authors.forename: Marcos
authors.initials: M
authors.lastname: Malosetti
authors.affiliation: Biometris, Wageningen University and Research, P.O. Box 16, 6700 AA, Wageningen, The Netherlands. fred.vaneeuwijk@wur.nl.
authors.forename: Fred A
authors.initials: FA
authors.lastname: van Eeuwijk
mesh_terms: D000465:Algorithms; D005838:Genotype; D008957:Models, Genetic; D000069600:Plant Breeding / Q000379:methods*; D045868:Sorghum / Q000235:genetics*; D062206:Spatial Analysis