Interactions of<i>Colletotrichum truncatum</i>with Herbicides for Control of Scentless Chamomile (<i>Matricaria perforata</i>)
Bibliographic record
Abstract
A host-specific fungusColletotrichum truncatumstrain 00-3B1 (Ct) was mixed with herbicides to improve the control of scentless chamomile, a noxious weed in western Canada. The compatibility of Ct conidia (spores) with herbicides was evaluated in vitro, and varying effects were observed with different products on spore germination. Clodinafop, glufosinate, MCPA, and 2,4-D ester were relatively benign and delayed the germination slightly, whereas dicamba, imazethapyr, metribuzin, and 2,4-D amine were noticeably more inhibitive. Bromoxynil, glyphosate, sethoxydim, and Merge®(spray adjuvant) were most inhibitive, showing >50% inhibition after 24 h. To determine potential synergy, Ct was applied at 7 × 106spores/ml in tank mixtures with selected herbicides at 1× and 0.1× registered rates under greenhouse conditions. Combining Ct with MCPA, 2,4-D ester, clopyralid, or metribuzin at 1× rate resulted in synergistic or additive interaction on scentless chamomile, increasing weed control significantly when compared to Ct or herbicides applied alone. Similar applications of Ct with imazethapyr, 2,4-D amine, dicamba, or glyphosate were antagonistic. Treatments with Ct plus 1× metribuzin killed scentless chamomile completely, whereas neither Ct nor the herbicide alone caused plant death, suggesting the value of this tank mixture.
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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".