Identification of two QTLs for web blotch resistance in peanut (Arachis hypogaea L.) based on BSA-seq
Bibliographic record
Abstract
BACKGROUND: Peanut (Arachis hypogaea L.) is a globally important oilseed and cash crop. Web blotch is one of the most important peanut foliar diseases, causing severe yield losses worldwide. RESULTS: population was used to identify quantitative trait loci (QTLs) for peanut web blotch resistance, based on bulked segregant analysis (BSA). Kompetitive Allele-Specific PCR (KASP) markers were developed and used to further narrow QTL intervals and detect candidate genes. Two major QTLs, qWBRA05 and qWBRA08 were identified, spanning physical intervals of 465.75 Kb and 434.83 Kb, and explaining percentages of phenotypic variation (PVE) of 8.79% and 15.09%, respectively. Moreover, two KASP markers were developed within the QTL interval effectively distinguished between web blotch resistance and web blotch susceptible materials. CONCLUSIONS: The QTLs identified and two molecular markers closely linked to web blotch resistance were developed within the QTL interval, which are potentially valuable in peanut breeding.
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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 | 0.001 | 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) | 0.000 | 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".