Quantitative genetic analysis of flowering time in tomato
Bibliographic record
Abstract
Artificial selection of cultivated tomato (Solanum lycopersicum L.) has resulted in the generation of early-flowering, day-length-insensitive cultivars, despite its close relationship to other Solanum species that need more time and specific photoperiods to flower. To investigate the genetic mechanisms controlling flowering time in tomato and related species, we performed a quantitative trait locus (QTL) analysis for flowering time in an F2 mapping population derived from S. lycopersicum and its late-flowering wild relative S. chmielewskii. Flowering time was scored as the number of days from sowing to the opening of the first flower (days to flowering), and as the number of leaves under the first inflorescence (leaf number). QTL analyses detected 2 QTLs affecting days to flowering, which explained 55.3% of the total phenotypic variance, and 6 QTLs for leaf number, accounting for 66.7% of the corresponding phenotypic variance. Four of the leaf number QTLs had not previously been detected for this trait in tomato. Colocation of some QTLs with flowering-time genes included in the genetic map suggests PHYB2, FALSIFLORA, and a tomato FLC-like sequence as candidate genes that might have been targets of selection during the domestication of tomato.
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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 | 0.000 |
| 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 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".