Norway spruce is a boreal forest tree species of significant ecological and economic importance. Hence there is a strong imperative to dissect the genetics controlling important wood quality traits in the species. We performed a functional Genome-Wide Association Mapping (GWAS) and a Genomic Selection (GS) cross-validation study. GWAS was conducted for 17 wood traits in Norway spruce using 178101 single-nucleotide polymorphisms (SNPs) generated from exome genotyping of 517 mother trees. The wood traits were defined using functional modelling of wood properties across annual growth rings. We applied a LASSO based association mapping method using a functional multi-locus mapping approach that utilizes latent traits, with a stability selection probability method as the hypothesis testing approach to determine significant Quantitative Trait Loci (QTLs). The same SNP collection were applied in a GS cross-validation was conducted in 60 half-sib families for solid wood properties collected with Silviscan technology from pith to bark and indirect methods. The study allowed the design of a cost-effective protocol for the implementation of wood solid into conifer breeding.