Inbred Corn Response to Acetamide Herbicides as Affected by Safeners and Microencapsulation
Bibliographic record
Abstract
Corn inbreds are often more sensitive to herbicides than hybrids. Field experiments were conducted with three corn inbreds to (1) evaluate inbred sensitivity to the acetamide herbicides acetochlor, dimethenamid, flufenacet, and metolachlor, (2) compare the effects of various crop safeners in combination with acetochlor and metolachlor, and (3) measure the effect of herbicide microencapsulation on acetochlor injury. Herbicides were applied preemergence at the registered rate and at two, three, or four times the registered rate in corn. Injury ratings, plant population, and the percentage of plants showing acetamide injury symptoms were used to measure herbicide effect. The inbreds ‘Mo17’ and ‘Great Lakes 15’ (GL15) were sensitive to acetamide injury. Reductions in plant population and increases in the injury rating and the percentage of injured plants were caused by acetochlor, dimethenamid, flufenacet, metolachlor, and flufenacet + metribuzin when applied at three times the registered rate. The inbred ‘B73’ was not injured. The safeners benoxacor and dichlormid reduced injury caused by metolachlor. The percentage of plants injured by metolachlor 15 days after treatment (DAT) was lower when benoxacor was the safener compared to dichlormid. By 28 DAT, plants treated with safeners recovered from injury, and there were no differences between the treatments. The safeners dichlormid and furilazole reduced, but did not always eliminate, injury caused by acetochlor applied at three times the registered rate. Microencapsulation of acetochlor reduced injury to GL15. When the safeners dichlormid or furilazole were included in an acetochlor formulation, microencapsulation did not further reduce corn injury.
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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) | 0.001 | 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".