Quantitative trait loci associated with lettuce seed germination under different temperature and light environments
Bibliographic record
Abstract
Temperature and light are primary environmental cues affecting seed germination. To elucidate the genetic architecture underlying lettuce (Lactuca sativa L.) seed germination under different environmental conditions, an F8 recombinant inbred line population consisting of 131 families was phenotyped for final germination and germination rate. Seeds were imbibed in water at 20 degrees C under continuous red light (20-Rc), 20 degrees C continuous dark (20-Dc), 31.5 degrees C continuous red light (31.5-Rc), 31.5 degrees C continuous dark (31.5-Dc), or 20 degrees C far-red light for 24 h followed by continuous dark (20-FRc-Dc). Thirty-eight quantitative trait loci (QTL) were identified from two seed maturation environments: 10 for final germination and 28 for germination rate. The amount of variation attributed to an individual QTL ranged from 9.3% to 17.2% and from 5.6% to 26.2% for final germination and germination rate, respectively. Path analysis indicated that factors affecting germination under 31.5-Rc or 31.5-Dc are largely the same, and these appear to differ from those employed under 20-FRc-Dc. QTL and path analysis support the notion of common and unique factors for germination under diverse temperature and light regimes. A highly significant effect of the seed maturation environment on subsequent germination capacity under environmental stress was observed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".