Herbicide diagnostics reveal multiple patterns of synthetic auxin resistance in kochia (<i>Bassia scoparia</i>)
Bibliographic record
Abstract
Abstract Herbicide-resistant (HR) kochia is a growing problem in the Great Plains region of Canada and the United States. Resistance to up to four herbicide sites of action, including photosystem II inhibitors, acetolactate synthase inhibitors, synthetic auxins, and the 5-enolpyruvylshikimate-3-phosphate synthase inhibitor glyphosate have been reported in many areas of this region. Despite being present in the United States since 1993/1994, auxinic-HR kochia is a recent and growing phenomenon in Canada. This study was designed to characterize 1) the level of resistance and 2) patterns of cross-resistance to dicamba and fluroxypyr in 12 putative auxinic-HR kochia populations from western Canada. The incidence of dicamba-resistant individuals ranged among populations from 0% to 85%, while fluroxypyr-resistant individuals ranged from 0% to 45%. In whole-plant dose-response bioassays, the populations exhibited up to 6.5-fold resistance to dicamba and up to 51.5-fold resistance to fluroxypyr based on visible injury 28 d after application. Based on plant survival estimates, the populations exhibited up to 3.7-fold resistance to dicamba and up to 72.5-fold resistance to fluroxypyr. Multiple patterns of synthetic auxin resistance were observed, in which one population from Cypress County, Alberta, was resistant to dicamba but not fluroxypyr, whereas another from Rocky View County, Alberta, was resistant to fluroxypyr but not dicamba based on single-dose population screening and dose-response bioassays. These results suggest that multiple mechanisms may confer resistance to dicamba and/or fluroxypyr in Canadian kochia populations. Further research is warranted to determine these mechanisms. Farmers are urged to adopt proactive nonchemical weed management practices in an effort to preserve efficacy of the remaining herbicide options available for control of HR kochia.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".