Quantitative trait loci analysis of flowering time related traits identified in recombinant inbred lines of cowpea (<i>Vigna unguiculata</i>)
Bibliographic record
Abstract
Flowering time is a major adaptive trait in plants and an important selection criterion in the breeding for genetic improvement of crop species. QTLs for the time of flower opening and days to flower were identified in a cross between a short duration domesticated cowpea (Vigna unguiculata (L.) Walp.) variety, 524B, and a relatively long duration wild accession, 219-01. A set of 159 F7 lines was grown under greenhouse conditions and scored for the flowering time associated phenotypes of time of flower opening and days to flower. Using a LOD threshold of 2.0, putative QTLs were identified and placed on a linkage map consisting of 202 SSR markers and four morphological loci. A total of five QTLs related to the time of flower opening were identified, accounting for 8.8%-29.8% of the phenotypic variation. Three QTLs for days to flower were detected, accounting for 5.7%-18.5% of the phenotypic variation. The major QTL of days to flower and time of flower opening were both mapped on linkage group 1. The QTLs identified in this study provide a strong foundation for further validation and fine mapping for developing an efficient way to restrain the gene flow between the cultivated and wild plants.
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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".