Identification and validation of fusarium head blight and<i>Fusarium</i>-damaged kernel QTL in a Frontana/Remus DH mapping population
Bibliographic record
Abstract
Fusarium head blight (FHB) is a devastating disease of wheat (Triticum aestivum L.). This study investigated a ‘Frontana/Remus’ doubled haploid population (n = 210 lines) to map and validate the ‘Frontana’ resistance quantitative trait loci (QTL) focusing on Fusarium-damaged kernels (FDK). The plant material was evaluated in six epidemic situations for Fusarium resistance in inoculated field experiments, with either Fusarium graminearum or F. culmorum. Other studies have focused on FHB QTL, but it is important to evaluate how far these QTL determine FDK values. The data show that the genetic regulation of FHB resistance is more complex than earlier proposed. FHB resistance QTL were identified on chromosomes 3A, 4A and 6B. Markers showed association with FDK resistance on chromosomes 3D and at the marker Xs12m15_4. QTL on 2B, 4B, 5A and 7B chromosomes were responsible for both FHB and FDK resistance; in this case, the same QTL influenced both traits and possibly other traits during disease development. These QTL are very important, because they can be considered to be real Fusarium resistance QTL. The use of markers in breeding programmes, which are associated only with FHB or FDK resistance may be questionable and require further research. Heading date QTL were detected on chromosomes 1A, 2D and 7B overlapping with neither FHB nor FDK resistance QTL. The QTL identified in the ‘Frontana/Remus’ population were in good agreement with earlier results from the literature.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".