Interactions of<i>Pyricularia setariae</i>with Herbicides for Control of Green Foxtail (<i>Setaria viridis</i>)
Bibliographic record
Abstract
Sethoxydim, tralkoxydim, imazethapyr, quinclorac, propanil, glyphosate, and glufosinate were tested at rates below those recommended by the manufacturers withPyricularia setariaeNiskada under greenhouse conditions for control of green foxtail. At one-tenth of the recommended rate in a 100 L/ha carrier volume, only the sethoxydim–P. setariaecombination achieved more effective green foxtail control when compared with the herbicide or pathogen alone. Selected herbicides at one-tenth, one-fourth, and one-half of the recommended rates showed variable interactions with the pathogen on plants with three and five leaves. Propanil (recommended rate 0.99 kg ai/ha) was more synergistic at higher rates, especially on larger plants, for which the combined treatment increased green foxtail mortality from zero in the herbicide alone to 100%. Quinclorac (recommended rate 0.10 kg ai/ha) acted similarly to propanil with slightly lower synergy effects. Sethoxydim (recommended rate 0.15 kg ai/ha) at one-tenth or one-quarter of the rate plusP. setariaeoften enhanced green foxtail control on larger plants. On smaller plants, the herbicide and pathogen alone were highly efficacious. Compared with tank mixes withP. setariae, propanil, quinclorac, or sethoxydim applied 6 h before the pathogen or earlier generally showed greater efficacy. Delaying a tank mix application for up to 2 h had little negative effect, but longer than 4 h often reduced efficacy. When combining the pathogen at different doses with propanil, quinclorac, or sethoxydim at one-tenth, one-quarter, and one-half of the rate, both fungal dose and herbicide rate affected the efficacy. Coapplying any of the herbicides at the one-quarter rate with the pathogen at the sublethal dose of 2 × 107spores/ml achieved complete control of green foxtail.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".