Emergence timing of volunteer canola in spring wheat fields in Manitoba
Bibliographic record
Abstract
Observational studies of weed emergence provide essential data for the creation and testing of predictive emergence models, with data ideally being collected from a wide range of sites representing a range of environments under which the seedlings of a given species emerge. The spring emergence of genetically engineered glyphosate-resistant volunteer canola was monitored in 20 farmers' commercial wheat fields over 2 yr, 2003 and 2004, in the southwestern region of Manitoba, Canada. Three different tillage systems, low-disturbance direct-seeded, high-disturbance direct-seeded, and conventionally tilled fields, were represented in this sample. Tillage system did not significantly influence the emergence periodicity of volunteer canola, but did influence total densities observed. Total volunteer canola densities in the surveyed fields were variable and ranged from 6 to 2,015 seedlings m−2. Conventionally tilled fields had the lowest densities of volunteer canola seedlings, and high-disturbance direct-seeded fields (no autumn tillage) had the highest densities. Volunteer canola is a relatively early spring emerging plant species requiring minimal accumulated growing degree days for emergence (calculated using a base temperature of 5 C). Emergence curves were steep, with a short window of volunteer canola emergence either prior to or within a spring-seeded wheat crop. To determine what proportion of autumn-broadcast canola seed (simulated harvest losses) would recruit the following spring and the influence of fall or spring tillage on this recruitment, a small plot experiment also was conducted at three sites. The following spring the percentage of canola seedlings that emerged ranged from 1.3 to 9.4% of the seed broadcast, depending upon the tillage treatment. The effect of tillage treatment on canola densities in the small plot experiment was similar to the field survey results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".