Genetic Characterization of Maximilian Sunflower for the Development of a Locally Adapted Perennial Grain Oilseed
Bibliographic record
Abstract
Maximilian sunflower ( Helianthus maximiliani Schrad.), a crop wild relative of sunflower ( Helianthus annuus L.), has been identified as a species of interest for the development of a perennial oilseed crop. Knowledge of the diversity, the potential for crop development, and genomic resources of this crop wild relative is limited. To facilitate its use in breeding programs, a baseline characterization of locally adapted germplasm is required to develop informed breeding strategies. Individuals were collected from nine sites in southern Manitoba, Canada, and characterized for phenotypic and genotypic divergence to estimate traits of interest for the implementation of a breeding program in Maximilian sunflower. Genotype‐by‐sequencing was used to characterize population genetic parameters and identify candidate single nucleotide polymorphisms (SNPs) associated with phenotypic divergence and environmental differences between collection sites. Candidate SNPs associated with frost‐free period, temperature during the primary vegetative growth period, elevation, soil CaCO 3 equivalent, days to anthesis and capitulum size were identified and may be useful for the improvement of H. maximiliani and crop species related to cultivated sunflower. Associations between temperature, population structure, and overall plant size were also identified, suggesting phenotypic divergence across a local temperature gradient. The sampled Maximilian sunflower populations exhibited a high degree of polymorphism, low levels of inbreeding, and a highly heterozygous genome at the local scale, traits that favor the establishment of locally adapted germplasm pools. There appears to be sufficient variation to make selections for agronomic traits in local germplasm of Maximilian sunflower to support its development as a perennial oilseed.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".