Abstract

Different methods for predicting clonal values were explored for diameter growth (diameter at breast height (DBH)) in a radiata pine clonal forestry program: (1) clones were analyzed with a full model in which the total genetic variation was partitioned into additive, dominance, and epistasis (Clone Only-Full Model); (2) clones were analyzed together with seedling base population data (Clone Plus Seedling (CPS)), and (3) clones were analyzed with a reduced model in which the only genetic term was the total genetic variance (Clone Only-Reduced Model). DBH was assessed at age 5 for clones and between ages 4 to 13 at the seedling trials. Significant additive, dominance, and epistatic genetic effects were estimated for DBH using the CPS model. Nonadditive genetic effects for DBH were 87% as large as additive genetic effects. Narrow-sense ((h) over cap (2)) and broad-sense ((H) over cap (2)) heritability estimates for DBH using the CPS model were 0.14 +/- 0.01 and 0.26 +/- 0.01, respectively. Accuracy of predicted clonal values increased 4% by combining the clone and seedling data over using clonal data alone, resulting in greater confidence in the predicted genetic performance of clones. Our results indicate that exploiting nonadditive genetic effects in clonal varieties will generate greater gains than that typically obtainable from conventional family-based forestry of radiata pine. The predicted genetic gain for DBH from deployment of the top 5% of clones was 24.0%-an improvement of more than 100% over family forestry at the same selection intensity. We conclude that it is best practice to predict clonal values by incorporating seedling base population data in the clonal analysis.

Keywords

Clonal forestry; Clonal value predictions; Radiata pine

Published in

Tree Genetics and Genomes
2009, Volume: 5, number: 1, pages: 269-278
Publisher: SPRINGER HEIDELBERG

UKÄ Subject classification

Forest Science


Publication identifier

DOI: https://doi.org/10.1007/s11295-008-0172-y

Permanent link to this page (URI)

https://res.slu.se/id/publ/88763