Landscape genomics and domestication status of Maximilian sunflower (Helianthus maximiliani Schrad.).
Bibliographic record
Abstract
The Canadian prairies are a highly productive agricultural zone with a short growing season and a high proportion of land devoted to production of annual grains. Perennial grains and oilseeds are capable of extending the growing season while providing grain, forage, or biomass. Candidate species for perennial grains and oilseeds lack basic agronomic and genetic characterization to support breeding efforts, limiting the ability to develop perennial grain cropping systems. The purpose of this thesis was to characterize the candidate perennial oilseed species Maximilian sunflower (Helianthus maximiliani Schrad.) for the development of a locally adapted perennial oilseed crop for the Canadian prairies. This work consisted of three primary studies examining the phenotypic characteristics of Maximilian sunflower and related perennial Helianthus species, the adaptation of germplasm to its environment of origin, and the development of genomic resources for breeding Maximilian sunflower. Local environmental clines influenced population structure and phenotypic differentiation in Maximilian sunflower, including important adaptive characteristics such as timing of anthesis. Genomic analysis revealed a highly heterozygous genome and low levels of population structure. The first reported genetic map of Maximilian sunflower was developed. Variation in important domestication syndrome traits such as branching architecture and capitulum size were observed in wild sampled and experimental mapping populations. Association and QTL analysis revealed candidate SNPs for multiple agronomic traits and adaptation to local environmental clines to support the neo-domestication of Maximilian sunflower as a perennial oilseed crop. The research contained in this thesis identified variation in key traits in Maximilian sunflower indicating advancement under selection for domestication is possible.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".