Productivity and quality of canola and mustard cultivars under weed competition
Bibliographic record
Abstract
Competitive crops or cultivars can be an important component of integrated weed management systems. A study was conducted from 2003 to 2006 at four sites across semiarid prairie ecoregions in Saskatchewan and Alberta to investigate the productivity and quality of canola (Brassica napusL.) and mustard cultivars under weed competition. Four open-pollinated canola cultivars, four hybrid canola cultivars, two canola-quality mustard and two oriental mustard cultivars [Brassica juncea (L.) Czern. & Coss.], and two yellow mustard (Sinapis alba L.) cultivars were grown under weedy and weed-free conditions. When combined across site-years, crop aboveground biomass at maturity and seed yield were reduced by weed interference, except for yellow and oriental mustard. However, seed oil and protein content of cultivars were not affected by weed competition. Among crop types, yellow and oriental mustard were best able to maintain biomass and seed yield under weed interference, followed in decreasing order of competitiveness by hybrid and open-pollinated canola, then canola-quality mustard. Key words: Brassica napus, Brassica juncea, Sinapis alba, weed competition
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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 | 0.001 | 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".