Evaluation of Foliar Sprays to Reduce Crop Damage by Canada Geese
Why this work is in the frame
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Bibliographic record
Abstract
South Dakota Department of Game, Fish and Parks annually spends >$500,000 managing crop damage caused by grazing Canada geese (Branta canadensis). Foliar applications of a chemical feeding deterrent could provide an effective alternative to the methods currently being used to reduce damage. In 2011 and 2012, we evaluated Rejex-It Migrate Turfguard®, Bird Shield®, Avian Control®, and Avipel® as grazing deterrents. We used a ground sprayer to apply the treatments every 7 days to plots in soybean fields in Day County, South Dakota. We monitored activity in the plots using time-lapse photography. We began treating the plots after geese had begun using them (late June through mid- July). Damage was estimated after geese had abandoned the plots (August). The methyl anthranilate products (Rejex-It, Bird Shield, and Avian Control) were ineffective at reducing crop damage. Damage was 100% on all plots treated with these products. Use of plots significantly increased (P < 0.02) between the pretreatment and postreatment periods for Rejex-It (180 minutes/day and 313 minutes/day) and Bird Shield (200 minutes/day and 299 minutes/day); whereas, use was similar (P = 0.99) between plots treated with Avian Control (111 minutes/day) and reference plots (104 minutes/day). Less time was spent on plots treated with the anthraquinone-based product, Avipel (44 minutes/day) than on reference plots (132 minutes/day; P < 0.01). Additionally, soybean damage was less on Avipel-treated plots than on reference plots (P < 0.01). We recommend more research on Avipel to assess rates and timing of application to make this product efficacious and economical in the field.
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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 it