Hazelnut tolerance to basal-directed applications of clopyralid and quinclorac
Bibliographic record
Abstract
Abstract Field studies were conducted to determine hazelnut tolerance to quinclorac and clopyralid and control efficacy of Canada thistle and field bindweed at three commercial orchards in western Oregon. Hazelnut cultivars evaluated included ‘Jefferson’, ‘Wepster’, and ‘McDonald’. Clopyralid at 278, 547, and 1,090 g ae ha−1, and quinclorac at 420, 840, and 1,680 g ai ha−1 were applied once a year as basal-directed applications to trees that were 1, 2, and 5 yr old. Treatments were imposed in the early spring of 2019 and reapplied in 2020. In both years, treatments covered hazelnut suckers. Hazelnut injury from clopyralid and quinclorac was consistently between 0% and 13% and not different from nontreated control plants (P > 0.05) between 14 d and 455 d after initial treatment. Similarly, there was no treatment effect on plant canopy index, leaf chlorophyll content, trunk cross-sectional area, internode length, or yield among treatments, even at the highest rates of clopyralid and quinclorac. In separate efficacy studies, clopyralid (278 g ae ha−1) resulted in 68% Canada thistle control and did not differ when clopyralid was mixed with carfentrazone (278 + 35 g ai ha−1) or glufosinate (278 + 1,148 g ai ha−1). Clopyralid-containing herbicide treatments suppressed field bindweed growth but did not kill plants even when mixed with carfentrazone or glufosinate. Quinclorac (420 g ha−1) alone provided 80% control of field bindweed and 93% and 98% control when combined with rimsulfuron (35 g ai ha−1) or carfentrazone (35 g ai ha−1), respectively. Still, all herbicide treatments resulted in similar field bindweed biomass. Results indicate that clopyralid and quinclorac are effective tools to help manage Canada thistle and field bindweed and that hazelnut can tolerate clopyralid and quinclorac at rates equivalent to 4-fold commercial-use rates not affecting plant growth and yield.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".