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Dive into the research topics where Heidi Dungey is active.

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Featured researches published by Heidi Dungey.


Tree Genetics & Genomes | 2009

Comparisons of genetic parameters and clonal value predictions from clonal trials and seedling base population trials of radiata pine

Brian S. Baltunis; Harry X. Wu; Heidi Dungey; T. J. “Tim” Mullin; Jeremy T. Brawner

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 (


PLOS ONE | 2015

Parentage Reconstruction in Eucalyptus nitens Using SNPs and Microsatellite Markers: A Comparative Analysis of Marker Data Power and Robustness.

Emily Telfer; Grahame T. Stovold; Yongjun Li; Orzenil Bonfim Silva-Junior; Dario Grattapaglia; Heidi Dungey


Silvae Genetica | 2007

Deterministic Simulation of Gains for Seedling and Cloned Main and Elite Breeding Populations of Pinus radiata and Implications for Strategy

C. J. A. Shelbourne; Satish Kumar; R. D. Burdon; L.D. Gea; Heidi Dungey

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Tree Genetics & Genomes | 2017

Genotype by environment interactions in forest tree breeding: review of methodology and perspectives on research and application

Yongjun Li; Mari Suontama; R. D. Burdon; Heidi Dungey


Silvae Genetica | 2012

Developing breeding and deployment options for Douglas-fir in New Zealand: breeding for future forest conditions

Heidi Dungey; C. B. Low; J. Lee; M. A. Miller; K. Fleet; A. D. Yanchuk

) and broad-sense (


PLOS ONE | 2017

Exploration of genetic architecture through sib-ship reconstruction in advanced breeding population of Eucalyptus nitens

Jaroslav Klápště; Mari Suontama; Emily Telfer; Natalie Graham; Charlie Low; Toby Stovold; Russel McKinley; Heidi Dungey


Silvae Genetica | 2011

Eucalyptus fastigata: its current status in New Zealand and breeding objectives for the future

S. K. Kennedy; Heidi Dungey; A. D. Yanchuk; C. B. Low

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New Zealand journal of forestry science | 2017

Genotype × site × silviculture interactions in radiata pine: knowledge, working hypotheses and pointers for research§

R. D. Burdon; Yongjun Li; Mari Suontama; Heidi Dungey


New Zealand journal of forestry science | 2013

Comparative performance of Eucalyptus bicostata, E. globulus, E. maidenii and E. pseudoglobulus on three northern New Zealand sites

Desmond J Stackpole; Ruth M McConnochie; Heidi Dungey; Charlie B. Low; R. D. Burdon; Stuart G Kennedy

) 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.


PLOS ONE | 2017

Improvement of non-key traits in radiata pine breeding programme when long-term economic importance is uncertain

Yongjun Li; Heidi Dungey; Alvin D. Yanchuk; Luis A. Apiolaza

Pedigree reconstruction using molecular markers enables efficient management of inbreeding in open-pollinated breeding strategies, replacing expensive and time-consuming controlled pollination. This is particularly useful in preferentially outcrossed, insect pollinated Eucalypts known to suffer considerable inbreeding depression from related matings. A single nucleotide polymorphism (SNP) marker panel consisting of 106 markers was selected for pedigree reconstruction from the recently developed high-density Eucalyptus Infinium SNP chip (EuCHIP60K). The performance of this SNP panel for pedigree reconstruction in open-pollinated progenies of two Eucalyptus nitens seed orchards was compared with that of two microsatellite panels with 13 and 16 markers respectively. The SNP marker panel out-performed one of the microsatellite panels in the resolution power to reconstruct pedigrees and out-performed both panels with respect to data quality. Parentage of all but one offspring in each clonal seed orchard was correctly matched to the expected seed parent using the SNP marker panel, whereas parentage assignment to less than a third of the expected seed parents were supported using the 13-microsatellite panel. The 16-microsatellite panel supported all but one of the recorded seed parents, one better than the SNP panel, although there was still a considerable level of missing and inconsistent data. SNP marker data was considerably superior to microsatellite data in accuracy, reproducibility and robustness. Although microsatellites and SNPs data provide equivalent resolution for pedigree reconstruction, microsatellite analysis requires more time and experience to deal with the uncertainties of allele calling and faces challenges for data transferability across labs and over time. While microsatellite analysis will continue to be useful for some breeding tasks due to the high information content, existing infrastructure and low operating costs, the multi-species SNP resource available with the EuCHIP60k, opens a whole new array of opportunities for high-throughput, genome-wide or targeted genotyping in species of Eucalyptus.

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Mari Suontama

Forest Research Institute

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Emily Telfer

Forest Research Institute

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Natalie Graham

Forest Research Institute

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R. D. Burdon

Forest Research Institute

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Jaroslav Klápště

Czech University of Life Sciences Prague

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Toby Stovold

Forest Research Institute

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