Cross-generational genomic prediction of Norway spruce (Picea abies) wood properties: an evaluation using independent validation.

ABSTRACT:

Background

The evaluation of genomic selection (GS) efficiency in forestry has primarily relied on cross-validation schemes that split the same population within a single generation for both training and validation. While useful, this approach may not be reliable for multigenerational breeding. To our knowledge, this is the first study to assess genomic prediction in Norway spruce using a large dataset spanning two generations in two environments. We trained pedigree-based (ABLUP) and marker-based (GBLUP) prediction models under three approaches: forward prediction, backward prediction, and across-environment prediction. The models were evaluated for ring-width, solid-wood and tracheid characteristics, using ~ 6,000 phenotyped and ~ 2,500 genotyped individual. Predictive ability (P

SUBMITTER: Hayatgheibi H 

PROVIDER: S-EPMC12278512 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature