Mapping of Quantitative Trait Loci Conferring Blast Field Resistance in the Japanese Upland Rice Variety Kahei.
Bibliographic record
Abstract
Many upland rice cultivars show higher levels of blast field resistance than do lowland cultivars. In this study, we performed a linkage mapping of quantitative trait loci (QTLs) for blast field resistance using F2 plants/F3 progenies derived from a cross between the upland variety Kahei (high level of resistance) and the lowland variety Koshihikari (susceptible). We mapped two putative QTLs on chromosome 4. qBFR4-1 was mapped in the vicinity of restriction fragment length polymorphism (RFLP) marker G264 on chromosome 4. This QTL explained about 62% of the total phenotypic variation in F3 lines. Another QTL, qBFR4-2, was also found near the RFLP marker G271 on chromosome 4. These two QTLs on chromosome 4 explained about 71% of total phenotypic variation based on the analysis of a multiple-QTL model. Alleles of Kahei increased the level of resistance in these two QTLs. The high level of resistance to blast in Kahei is mainly explained by these two QTLs. Applications of newly found QTL for breeding rice with blast field resistance is discussed.
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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 | 0.000 | 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".