Quantitative Trait Loci Affecting Oil Content, Oil Composition, and Other Agronomically Important Traits in Oat
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Groat oil content and composition are important determinants of oat ( Avena sativa L.) quality. We investigated these traits in a population of 146 recombinant inbred lines from a cross between ‘Dal’ (high oil) and ‘Exeter’ (low oil). A linkage map consisting of 475 Diversity Arrays Technology (DArT) markers spanning 1271.8 cM across 40 linkage groups was constructed. Quantitative trait locus (QTL) analysis for groat oil content and composition was conducted using grain samples grown at Aberdeen, ID, in 1997. Quantitative trait locus analysis for multiple agronomic traits was also conducted using data collected from hill plots and field plots in Ottawa, ON, in 2010. Using simple and composite interval mapping methods, QTLs for oil content, palmitic acid (16:0), stearic acid (18:0), oleic acid (18:1), linoleic acid (18:2), and linolenic acid (18:3) were identified. Two of the loci associated with oil content were associated with all of the fatty acids examined in this study, and most oil‐related QTL showed similar patterns of effect on the fatty acid profile. These results suggest the presence of pleiotropic effects on oil‐related traits through influences at specific nodes of the oil synthesis pathway. In addition, 12 QTL‐associated markers (likely representing nine unique regions) were associated with plant height, heading date, lodging, and protein content.
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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 it