Competitive traits and the stability of wheat cultivars in differing natural weed environments on the northern Canadian Prairies
Bibliographic record
Abstract
SUMMARY Nine spring wheat cultivars, selected on the basis of height, tillering capacity and maturity, were grown in differing levels of natural weed presence at three locations in Edmonton and New Norway, Alberta between 2003 and 2004. The objectives of the study were to (1) identify competitive traits in wheat cultivars, (2) determine whether traits associated with competitive ability differ under increasing weed pressure and (3) assess cultivar stability in and adaptation to environments differing in yield potential and weed competition. Eight experimental environments (including conventionally and organically managed fields with and without common oats sown as a weed analogue) were grouped into low, medium and high weed pressure levels, based on mean total weed biomass. Tallness and early heading and maturity were related to increased grain yield at the highest weed level. Greater spikes/m2, tallness and early heading were associated with reduced weed biomass, depending on weed level. Principal component analysis (PCA) revealed that height accounted for a small amount of variation in low weed environments, yet was more important as weed pressure increased. Finlay–Wilkinson (Finlay & Wilkinson 1963) stability analysis demonstrated that cultivars responded differently in environments differing in yield potential and in weed pressure. Older wheat cultivars were generally more yield-stable across environments, while modern semidwarf cultivars were more sensitive to changes in weed level. The cultivar Park (released in 1963) was the most yield- and weed-stable cultivar, coupled with relatively high yields and average weed biomass accumulation, and may therefore be well adapted to low yielding or high weed environments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".