Target and Non–target site Mechanisms Confer Resistance to Glyphosate in Canadian Accessions of<i><b>Conyza canadensis</b></i>
Bibliographic record
Abstract
Glyphosate-resistant populations ofConyza canadensishave been spreading at a rapid rate in Ontario, Canada, since first being documented in 2010. Determining the genetic relationship among existing Ontario populations is necessary to understand the spread and selection of the resistant biotypes. The objectives of this study were to: (1) characterize the genetic variation ofC. canadensisaccessions from the province of Ontario using simple sequence repeat (SSR) markers and (2) investigate the molecular mechanism (s) conferring resistance in these accessions. Ninety-eightC. canadensisaccessions were genotyped using 8 SSR markers. Germinable accessions were challenged with glyphosate to determine their dose response, and the sequences of 5-enolpyruvylshikimate-3-phosphate synthase genes 1 and 2 were obtained. Results indicate that a majority of glyphosate-resistant accessions from Ontario possessed a proline to serine substitution at position 106, which has previously been reported to confer glyphosate resistance in other crop and weed species. Accessions possessing this substitution demonstrated notably higher levels of resistance than non–target site resistant (NTSR) accessions from within or outside the growing region and were observed to form a subpopulation genetically distinct from geographically proximate glyphosate-susceptible and NTSR accessions. Although it is unclear whether other non–target site resistance mechanisms are contributing to the levels of resistance observed in target-site resistant accessions, these results indicate that, at a minimum, selection for Pro-106-Ser has occurred in addition to selection for non–target site resistance and has significantly enhanced the levels of resistance to glyphosate inC. canadensisaccessions from Ontario.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".