Effect of Halosulfuron Rate and Application Timing on Volunteer Azuki Bean Control in White Bean
Bibliographic record
Abstract
Three field experiments were carried out during 2017-2019 at the University of Guelph Huron Research Station near Exeter, Ontario, Canada to determine the effect of halosulfuron rate (25, 37.5 or 50 g∙ai∙ha-1) and application timing (POST 1, POST 2 and POST 3) on volunteer azuki bean control in white bean. At POST 1, halosulfuron at 25, 37.5 and 50 g∙ai∙ha-1 controlled volunteer azuki bean 46% - 50% at 1 week after application (WAA), controlled decreased to 16% - 25% at 8 WAA. At POST 2, volunteer azuki bean controlled decreased from 34% - 39% at 1 WAA to 17% - 27% at 8 WAA. A similar trend was observed at POST 3. Halosulfuron applied POST 1 at 25, 37.5 and 50 g∙ai∙ha-1 reduced biomass 49%, 64% and 69%, respectively. Halosulfuron applied POST 2 did not reduce volunteer azuki bean biomass at 25 g∙ai∙ha-1, but decreased biomass 51% at 37.5 g∙ai∙ha-1 and 49% at 50 g∙ai∙ha-1. Similarly, halosulfuron applied POST 3 did not reduce volunteer azuki bean biomass at 25 g∙ai∙ha-1, but decreased biomass 40% at 37.5 g∙ai∙ha-1 and 44% at 50 g∙ai∙ha-1. There was as much as 19%, 22% and 25% dockage with halosulfuron applied POST 1, POST 2 and POST 3, respectively. Volunteer azuki bean interference reduced white bean yield 40%. Reduced volunteer azuki bean interference with halosulfuron applied POST 1 at 37.5 or 50 g∙ai∙ha-1 resulted in an increase in white bean yield relative to the weedy control; however white yield was less than the weed-free control. This study concludes that halosulfuron at rates and application timings evaluated does not provide adequate control of volunteer azuki bean in white bean.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".