Mapping quantitative trait loci controlling agronomic traits in the spring wheat cross RL4452 × 'AC Domain'
Bibliographic record
Abstract
Relatively little is known about the genetic control of agronomic traits in common wheat (Triticum aestivum L.) compared with traits that follow Mendelian segregation patterns. A doubled-haploid population was generated from the cross RL4452x'AC Domain' to study the inheritance of the agronomic traits: plant height, time to maturity, lodging, grain yield, test weight, and 1000-grain weight. This cross includes the genetics of 2 western Canadian wheat marketing classes. Composite interval mapping was conducted with a microsatellite linkage map, incorporating 369 loci, and phenotypic data from multiple Manitoba environments. The plant height quantitative trait loci (QTLs), QHt.crc-4B and QHt.crc-4D, mapped to the expected locations of Rht-B1 and Rht-D1. These QTLs were responsible for most of the variation in plant height and were associated with other agronomic traits. An additional 25 agronomic QTLs were detected in the RL4452x'AC Domain' population beyond those associated with QHt.crc-4B and QHt.crc-4D. 'AC Domain' contributed 4 alleles for early maturity, including a major time to maturity QTL on 7D. RL4452 contributed 2 major alleles for increased grain yield at QYld.crc-2B and QYld.crc-4A, which are potential targets for marker-assisted selection. A key test weight QTL was detected on 3B and prominent 1000-grain weight QTLs were identified on 3D and 4A.
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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".