Flat fan and air induction nozzles affect soybean herbicide efficacy
Bibliographic record
Abstract
Fifteen field experiments were conducted from 2002 to 2005 to determine the influence of the nozzle type, spray volume, spray pressure, and herbicide rate on herbicidal efficacy in soybean. There was no effect of the nozzle type on herbicidal efficacy with fomesafen, bentazon, glyphosate, and cloransulam‐methyl when applied at the manufacturer's recommended rate. The control of Echinochloa crus‐galli (barnyardgrass) with quizalofop‐p‐ethyl was improved when applied with flat fan (FF) nozzles compared with air induction (AI) nozzles. There was an increase in weed control with the FF nozzles compared with the AI nozzles in four of the 13 comparisons when the herbicides were applied at half the recommended rate, while in two situations, application with the AI nozzles resulted in improved weed control. With the FF nozzles, there was no effect of the water carrier volume on weed control with bentazon, glyphosate, and cloransulam‐methyl. The control of Abutilon theophrasti (velvetleaf) and Chenopodium album (common lambsquarters) with fomesafen and E. crus‐galli with quizalofop‐p‐ethyl was improved at the higher water carrier volume. With the AI nozzles, the control of A. theophrasti and Ambrosia artemisiifolia (common ragweed) with fomesafen and E. crus‐galli with quizalofop‐p‐ethyl was improved at the higher water carrier volume, while the control of A. theophrasti and Polygonum persicaria (ladysthumb) was improved with glyphosate at the lower water carrier volume. With the AI nozzles, the control of C. album with bentazon and E. crus‐galli with quizalofop‐p‐ethyl was improved at the higher spray pressure. There was no effect of the nozzle type on the soybean yield with glyphosate, cloransulam‐methyl, and quizalofop‐p‐ethyl. The use of the FF nozzles compared with the AI nozzles to apply fomesafen and bentazon increased the soybean yield by 6 and 7%, respectively. Based on this study, the optimum nozzle type, water carrier volume, and spray pressure is herbicide‐ and weed species‐specific.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".