Forest tree breeding has been successful at delivering genetically improved material for
multiple traits based on recurrent cycles of selection, mating, and testing. However, long …

Background Genomic selection (GS) in forestry can substantially reduce the length of
breeding cycle and increase gain per unit time through early selection and greater selection …

Maximization of genetic gain in forest tree breeding programs is contingent on the accuracy
of the predicted breeding values and precision of the estimated genetic parameters. We …

The open-pollinated (OP) family testing combines the simplest known progeny evaluation
and quantitative genetics analyses as candidates’ offspring are assumed to represent …

Background Genomic selection (GS) can offer unprecedented gains, in terms of cost efficiency
and generation turnover, to forest tree selective breeding; especially for late expressing …

Here, we perform cross-generational GS analysis on coastal Douglas-fir (Pseudotsuga
menziesii), reflecting trans-generational selective breeding application. A total of 1321 trees, …

Background The presupposition of genomic selection (GS) is that predictive accuracies should
be based on population-wide linkage disequilibrium (LD). However, in species with large, …

Tree improvement programs often focus on improving productivity-related traits; however,
under present climate change scenarios, climate change-related (adaptive) traits should also …

Background Genomic prediction (GP) and genome-wide association (GWA) analyses are
currently being employed to accelerate breeding cycles and to identify alleles or genomic …

Since their initiation in the 1950s, worldwide selective tree breeding programs followed the
recurrent selection scheme of repeated cycles of selection, breeding (mating), and testing …