Glyphosate resistance in <i>Ambrosia trifida</i>: Part 1. Novel rapid cell death response to glyphosate
Bibliographic record
Abstract
BACKGROUND: Glyphosate-resistant (GR) Ambrosia trifida is now present in the midwestern United States and in southwestern Ontario, Canada. Two distinct GR phenotypes are known, including a rapid response (GR RR) phenotype, which exhibits cell death within hours after treatment, and a non-rapid response (GR NRR) phenotype. The mechanisms of resistance in both GR RR and GR NRR remain unknown. Here, we present a description of the RR phenotype and an investigation of target-site mechanisms on multiple A. trifida accessions. RESULTS: Glyphosate resistance was confirmed in several accessions, and whole-plant levels of resistance ranged from 2.3- to 7.5-fold compared with glyphosate-susceptible (GS) accessions. The two GR phenotypes displayed similar levels of resistance, despite having dramatically different phenotypic responses to glyphosate. Glyphosate resistance was not associated with mutations in EPSPS sequence, increased EPSPS copy number, EPSPS quantity, or EPSPS activity. CONCLUSION: These encompassing results suggest that resistance to glyphosate in these GR RR A. trifida accessions is not conferred by a target-site resistance mechanism. © 2017 Society of Chemical Industry.
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 | 0.000 | 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".