Genetic mapping of agronomic traits in false flax (Camelina sativa subsp.<i>sativa</i>)
Bibliographic record
Abstract
The crucifer oilseed plant false flax (Camelina sativa subsp. sativa) possesses numerous valuable agronomic attributes that make it attractive as an alternative spring-sown crop for tight crop rotations. The oil of false flax is particularly rich in polyunsaturated C18-fatty acids, making it a valuable renewable feedstock for the oleochemical industry. Because of the minimal interest in the crop throughout the 20th century, breeding efforts have been limited. In this study, a genetic map for C. sativa was constructed, using amplified fragment length polymorphism (AFLP) markers, in a population of recombinant inbred lines that were developed, through single-seed descent, from a cross between 'Lindo' and 'Licalla', 2 phenotypically distinct parental varieties. Three Brassica simple sequence repeat (SSR) markers were also integrated into the map, and 1 of these shows linkage to oil-content loci in both C. sativa and Brassica napus. Fifty-five other SSR primer combinations showed monomorphic amplification products, indicating partial genome homoeology with the Brassica species. Using data from field trials with different fertilization treatments (0 and 80 kg N/ha) at multiple locations over 3 years, the map was used to localize quantitative trait loci (QTLs) for seed yield, oil content, 1000-seed mass, and plant height. Some yield QTLs were found only with the N0 treatment, and might represent loci contributing to the competitiveness of false flax in low-nutrient soils. The results represent a starting point for future marker-assisted breeding.
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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 | 0.000 |
| 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".