Competitive fitness of bird rape mustard ( <i>Brassica rapa</i> L.) that integrated transgenes conferring glyphosate resistance in commercial fields
Bibliographic record
Abstract
Abstract Ten years after the introduction of genetically engineered canola ( Brassica napus L.), bird rape mustard ( Brassica rapa L.) with transgenes conferring glyphosate resistance was reported where the crop and the weed were sympatric. Another decade later, populations of these weeds were reported on farms located beyond this initial region of sympatry. To determine if populations with introgressed transgenes have the potential to persist in field borders where wild types and crop plants can be found, the competitive fitness of two of these populations was compared to that of two naturalised wild Brassica rapa populations, a B. rapa cultivar and a B. napus cultivar, in a greenhouse study. Single plants of each of these six Brassica lines (referred to as types) were grown surrounded by four to eight contour plants (1:4 or 1:8) of each type, for a total of 36 combinations, at two densities. The experiment included four replicates and was repeated twice with one trial ending at flowering and the second continuing to plant maturity. Analyses evaluated the effect of Brassica type and density on phenology, total aboveground biomass and seed production as well as gains or losses in these latter fitness components by centre plants compared to contour plants. Results demonstrate that the bird rape mustard populations with transgenes from haphazard crosses with glyphosate‐tolerant B. napus crop plants were not always as fit as other, wild B. rapa populations. Their early development was slower than wild types and their biomass was generally reduced when grown surrounded by dissimilar plant types. Nevertheless, observed differences were unlikely to limit the persistence of these biotypes in the absence of glyphosate application.
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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 | 0.000 | 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".