A genetic analysis of weed competitive ability in spring wheat
Bibliographic record
Abstract
Competition with weeds decreases crop yields globally. Breeding for competitive ability against elevated weed pressure can be difficult because the selection for specific traits which contribute to competitive ability may result in yield losses. The widely studied International Triticeae Mapping Initiative (ITMI) population was used to study the genetics of traits associated with competitive ability in a high latitude (52-53ºN) wheat-growing environment in central Alberta, Canada. Grain yield without weed competition and under experimentally sown cultivated oat competition exhibited similar heritability. Grain yield was positively correlated with early season vigour, and negatively correlated with days to maturity in the competitive treatment only. In this study, similar heritability estimates between competition treatments suggest that selection in a weed free environment can lead to improvements in a weedy environment, but some high-yielding lines under competition would be eliminated during selection.Key words: Wheat, weed competition, competitive ability, International Triticeae Mapping Initiative, genetic correlation
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".