Journal
JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS
Volume 25, Issue 4, Pages 699-718Publisher
SPRINGER
DOI: 10.1007/s13253-020-00396-1
Keywords
Gaussian random field; Genomic prediction; Spatial effects; Subpopulation effects
Funding
- Iowa State University Plant Sciences Institute Scholars Program
- USDA/NIFA [IOW03617]
- State of Iowa funds [IOW03617]
- Shanghai Sailing Program [19YF1402800]
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This paper investigates the problem of adjusting for spatial effects in genomic prediction. Despite being seldomly considered in genomic prediction, spatial effects often affect phenotypic measurements of plants. We consider a Gaussian random field model with an additive covariance structure that incorporates genotype effects, spatial effects and subpopulation effects. An empirical study shows the existence of spatial effects and heterogeneity across different subpopulation families, while simulations illustrate the improvement in selecting genotypically superior plants by adjusting for spatial effects in genomic prediction.
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