Adventitious Presence: Volunteer Flax (<i>Linum usitatissimum</i>) in Herbicide-Resistant Canola (<i>Brassica napus</i>)
Bibliographic record
Abstract
Flax is in the process of development as a crop for bio-industrial and nutraceutical products predicated on the use of genetic modification. Before genetically modified (GM) flax is commercially released, effective management practices should be developed to minimize adventitious presence (AP) of GM volunteer flax in subsequent crops. Field research was conducted at four locations during 2007 and 2008 in central Alberta to quantify and mitigate AP of volunteer flax in glufosinate-resistant (GR) and imidazolinone-resistant (IR) canola. A single preplant application of glyphosate at 1,250 g ae ha−1in GR canola reduced volunteer flax density from 54 to 3 plants m−2and seed production from 5,963 to 233 seeds m−2. Similarly, the recommended rate of POST glufosinate (600 g ai ha−1) alone effectively controlled volunteer flax and reduced flax seed viability to < 8% and AP to 0.2%. A combination of preplant (glyphosate) and POST (glufosinate) at recommended rates reduced volunteer flax seed production, yield, and AP to near zero in GR canola. Glyphosate applied preplant was equally effective in IR canola, reducing volunteer flax density from 56 to 2 plants m−2, and seed production from 5,571 to 472 seeds m−2. Imazamox + imazethapyr applied POST at all the rates poorly controlled volunteer flax and, even in combination with preplant glyphosate, cannot be recommended for control of flax volunteers in IR canola.
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".