Responses of Winter Wheat to Herbicide-Fungicide Tankmixes
Bibliographic record
Abstract
Tankmixing herbicides with fungicides could improve production efficiency and reduce application costs. A total of six field trials were conducted from 2012 to 2014 in Ontario to study the tolerance of winter wheat to herbicide (fenoxaprop-p-ethyl/mefenpyr, prosulfuron + bromoxynil and fluroxypyr + MCPA ester) plus fungicide tankmixes (pyraclostrobin/metconazole, tri-floxystrobin/propiconazole, azoxystrobin/propiconazole and picoxystrobin) applied alone and as a tankmix. At 1 WAT, fenoxaprop-p-ethyl/mefenpyr applied alone or in tankmix with tri-floxystrobin/propiconazole or azoxystrobin/propiconazole fungicides caused minimal visible injury (up to 1.3%) in winter wheat but caused no significant injury when applied as a tankmix with pyraclostrobin/metconazole or picoxystrobin fungicides. There was no effect on visible injury in winter wheat with other herbicide and fungicide tankmixes. Fenoxaprop-p-ethyl/mefenpyr applied alone with no fungicide reduced winter wheat height 3% but had no adverse effect on height when tankmixed with fungicides evaluated. Prosulfuron + bromoxynil or fluroxypyr + MCPA ester herbicides applied alone with no fungicide or tankmixed with pyraclostrobin/metconazole, tri-floxystrobin/propiconazole, azoxystrobin/propiconazole and picoxystrobin fungicides had no adverse effect on winter wheat height. There was no adverse effect of herbicide plus fungicide treatments on winter wheat yield. Co-application of fenoxaprop-p-ethyl/mefenpyr, prosulfuron + bromoxynil and fluroxypyr + MCPA ester herbicides with pyraclostrobin/metconazole, tri-floxystrobin/pro- piconazole, azoxystrobin/propiconazole and picoxystrobin fungicides could provide winter wheat growers with a single-pass treatment for the control of weeds and diseases.
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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) | 0.001 | 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) | 0.001 | 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".