Molecular mapping of soybean seed tocopherols in the cross ‘<scp>OAC</scp> Bayfield’ × ‘<scp>OAC</scp> Shire’
Bibliographic record
Abstract
Abstract Soybean (Glycine max [L.] Merr.) is cultivated primarily for its protein and oil in the seed. In addition, soybean seeds contain nutraceutical compounds such as tocopherols (vitamin E), which are powerful antioxidants with health benefits. The objective of this study was to identify molecular markers linked to quantitative trait loci (QTL) that affect accumulation of soybean seed tocopherols. A recombinant inbred line (RIL) population derived from the cross ‘OAC Bayfield’ × ‘OAC Shire’ was grown in three locations over 2 years. A total of 151 SSR markers were polymorphic of which a one‐way analysis of variance identified 42 markers whereas composite interval mapping identified 26 markers linked to tocopherol QTL across 17 chromosomes. Individual QTL explained from 7% to 42% of the total phenotypic variation. Significant two‐locus epistatic interactions were identified for a total of 122 combinations in 2009 and 152 in 2010. The multiple‐locus models explained 18.4–72.2% of the total phenotypic variation. The reported QTL may be used in marker‐assisted selection (MAS) to develop high tocopherol soybean cultivars.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".