ArticleBMC genomics2020
Effect of number of annual rings and tree ages on genomic predictive ability for solid wood properties of Norway spruce.
Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Genomic models for accurate estimation of breeding values in Sitka spruce (Picea sitchensis Bong. Carr).Heredity · 2026Article
- Artificial Intelligence Methods in Forest Biotechnology: Current Status and Future Prospects.International journal of molecular sciences · 2026Review
- Multivariate models improve accuracy of genomic prediction for spring frost tolerance in Norway spruce.The plant genome · 2025Article
- Cross-generational genomic prediction of Norway spruce (Picea abies) wood properties: an evaluation using independent validation.BMC genomics · 2025Article
- Achievements and Challenges of Genomics-Assisted Breeding in Forest Trees: From Marker-Assisted Selection to Genome Editing.International journal of molecular sciences · 2021Review
- Genomic Predictions With Nonadditive Effects Improved Estimates of Additive Effects and Predictions of Total Genetic Values inFrontiers in plant science · 2021Article
- Evaluation of the efficiency of genomic versus pedigree predictions for growth and wood quality traits in Scots pine.BMC genomics · 2020Article
- Genetic control of tracheid properties in Norway spruce wood.Scientific reports · 2020Article
- Modern Strategies to Assess and Breed Forest Tree Adaptation to Changing Climate.Frontiers in plant science · 2020Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundGenomic selection (GS) or genomic prediction is considered as a promising approach to accelerate tree breeding and increase genetic gain by shortening breeding cycle, but the efforts to develop routines for operational breeding are so far limited. We investigated the predictive ability (PA) of GS based on 484 progeny trees from 62 half-sib families in Norway spruce (Picea abies (L.) Karst.) for wood density, modulus of elasticity (MOE) and microfibril angle (MFA) measured with SilviScan, as well as for measurements on standing trees by Pilodyn and Hitman instruments.
resultsGS predictive abilities were comparable with those based on pedigree-based prediction. Marker-based PAs were generally 25-30% higher for traits density, MFA and MOE measured with SilviScan than for their respective standing tree-based method which measured with Pilodyn and Hitman. Prediction accuracy (PC) of the standing tree-based methods were similar or even higher than increment core-based method. 78-95% of the maximal PAs of density, MFA and MOE obtained from coring to the pith at high age were reached by using data possible to obtain by drilling 3-5 rings towards the pith at tree age 10-12.
conclusionsThis study indicates standing tree-based measurements is a cost-effective alternative method for GS. PA of GS methods were comparable with those pedigree-based prediction. The highest PAs were reached with at least 80-90% of the dataset used as training set. Selection for trait density could be conducted at an earlier age than for MFA and MOE. Operational breeding can also be optimized by training the model at an earlier age or using 3 to 5 outermost rings at tree age 10 to 12 years, thereby shortening the cycle and reducing the impact on the tree.
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