Common ragweed (<i>Ambrosia artemisiifolia</i>) seed shattering in wheat, corn, and soybean
Bibliographic record
Abstract
Abstract Before any late-season weed control operations are planned to manage herbicide-resistant weeds, it is essential to evaluate the plants’ maturity and shattering potential. Our goal was to assess the seed-shattering phenology of common ragweed ( Ambrosia artemisiifolia L.) using pollination bags as seed traps. A secondary goal was to evaluate the efficiency of these traps. Trials were conducted from 2014 to 2017 at two locations in eastern Canada (Saint-Jean-sur-Richelieu, QC, and Harrow, ON). At each location, three adjacent fields were seeded with spring wheat ( Triticum aestivum L.), soybean [ Glycine max (L.) Merr.], or corn ( Zea mays L.). Each field was divided into four replicate blocks that included two treatment plots with 5 weeds m −2 planted on the same date as the crop or when crop plants had two leaves (early or late emergence). To evaluate shattering in time, the experiment included up to 12 weekly collection dates (subplots). In each subplot, weeds were individually bagged at flowering (using mesh bags) until collection, when the number and viability of shattered and retained seeds per plant was recorded. Weather data as well as crop and weed stages were recorded. The effect of the pollen bags on seed retrieval and viability was evaluated by installing open and closed bags in corn and uncropped (bare) plots at a single location. Ambrosia artemisiifolia seed biomass was equivalent or higher in closed bags, and seed viability was equivalent or slightly reduced. No seeds were produced before harvest in spring wheat, as dispersal started in September. The percentage of seeds retained on the plant decreased linearly (1 site-year) or followed a logistic equation (4 site-years) with day of year or growing degree days. Dispersal in time was similar between early- and late-emerging weeds and similar in both corn and soybean. On average, more than 50% of A. artemisiifolia seeds were dispersed before harvest in corn and soybean.
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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 | 0.001 |
| 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".