Agronomic Practices to Reduce the Effects of Environmental Stresses on Spring Canola (Brassica napus L.) Establishment and Yield in Ontario
Bibliographic record
Abstract
Establishing an adequate plant stand is one of the primary challenges in the production of canola (Brassica napus L.), and plant population strongly affects crop morphology. We tested the hypotheses that i) pre-plant application of liquid dairy manure (LDM) improves crop establishment more than a fertilizer with similar nutrients, and ii) plant morphological changes correlated with low-density plant stands enhance crop tolerance of mid-season water stress. In greenhouse studies both LDM and fertilizer treatments enhanced seedling vigour over the untreated control, but in some cases percent seedling emergence was higher with LDM than the fertilizer treatments. Enhanced seedling emergence with LDM was not found in field trials, even at sub-optimal seeding rates. In a high-yielding greenhouse trial, low plant density shifted much of the pod load from main racemes to branch racemes, but this morphological change did not significantly reduce yield loss under water stress.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".