Exploring radiata pine breeding strategies using genomic tools.
| dc.contributor.author | McLean, Duncan | |
| dc.date.accessioned | 2024-12-13T03:24:11Z | |
| dc.date.available | 2024-12-13T03:24:11Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | Radiata pine (Pinus radiata D. Don) is economically the most important forestry species in New Zealand. The radiata pine breeding program has undergone numerous strategic changes over the past 70 years. Presently, the Radiata Pine Breeding Company (RPBC) is in the process of implementing genomic selection to shorten generation cycles and accelerate genetic progress. We used a stochastic simulation approach to confirm that genomic selection can double the annual genetic gain compared to traditional phenotypic selection cycles. This significant increase is primarily due to the shorter breeding cycle facilitated by GS. The study also found that prediction accuracy and genetic gain increase with larger training populations and clonal testing, but plateau after approximately 2,500 genotypes. In terms of genotype-by-environment interaction (GxE), while it exists, its magnitude does not justify regionalizing breeding zones within New Zealand’s North Island. The thesis further explores the impact of GS on the deployment of genetic gain to production forests, showing that GS significantly increases genetic gain across all scenarios, with clonal deployment via somatic embryogenesis yielding the highest increase. An optimal orchard scenario for control-pollinated (CP) deployment was identified as having low female turnover with high male turnover, balancing genetic gain, seed yield, and inbreeding rates. Lastly, a cost-benefit analysis revealed that open-pollinated (OP) orchards offer a higher return on investment over 20 deployment cycles, primarily due to lower production costs and higher seed yields. This research demonstrates the advantages of genomic selection in accelerating genetic gain and optimising breeding and deployment strategies for Radiata pine in New Zealand. | |
| dc.identifier.uri | https://hdl.handle.net/10092/107881 | |
| dc.identifier.uri | https://doi.org/10.26021/15591 | |
| dc.language | English | |
| dc.language.iso | en | |
| dc.rights | All Right Reserved | |
| dc.rights.uri | https://canterbury.libguides.com/rights/theses | |
| dc.title | Exploring radiata pine breeding strategies using genomic tools. | |
| dc.type | Theses / Dissertations | |
| thesis.degree.discipline | Forestry | |
| thesis.degree.grantor | University of Canterbury | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | Doctor of Philosophy | |
| uc.college | Faculty of Engineering |