Growth, productivity, and competitiveness of introgressed weedy <i>Brassica rapa</i> hybrids selected for the presence of Bt <i>cry1Ac</i> and <i>gfp</i> transgenes
Bibliographic record
Abstract
Concerns exist that transgenic crop x weed hybrid populations will be more vigorous and competitive with crops compared with the parental weed species. Hydroponic, glasshouse, and field experiments were performed to evaluate the effects of introgression of Bacillus thuringiensis (Bt) cry1Ac and green fluorescent protein (GFP) transgenes on hybrid productivity and competitiveness in four experimental Brassica rapa x transgenic Brassica napus hybrid generations (F1, BC1F1, BC2F1 and BC2F2). The average vegetative growth and nitrogen (N) use efficiency of transgenic hybrid generations grown under high N hydroponic conditions were lower than that of the weed parent (Brassica rapa, AA, 2n = 20), but similar to the transgenic crop parent, oilseed rape (Brassica napus, AACC, 2n = 38). No generational differences were detected under low N conditions. In two noncompetitive glasshouse experiments, both transgenic and nontransgenic BC2F2 hybrids had on average less vegetative growth and seed production than B. rapa. In two high intraspecific competition field experiments with varied herbivore pressure, BC2F2 hybrids produced less vegetative dry weight than B. rapa. The competitive ability of transgenic and nontransgenic BC2F2 hybrids against a neighbouring crop species were quantified in competition experiments that assayed wheat (Triticum aestivum) yield reductions under agronomic field conditions. The hybrids were the least competitive with wheat compared with parental Brassica competitors, although differences between transgenic and nontransgenic hybrids varied with location. Hybridization, with or without transgene introgression, resulted in less productive and competitive populations.
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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 | 0.001 | 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 | 0.001 |
| 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".