Tolerance of annual canarygrass (Phalaris canariensis L.) to combinations of MCPA, clopyralid, fluroxypyr and florasulam
Bibliographic record
Abstract
May, W. E., Johnson, E. N., Sapsford, K. L., Stevenson, F. C., Lafond, G. P., Holzapfel, C. B. and Holm, F. A. 2014. Tolerance of annual canarygrass (Phalaris canariensis L.) to combinations of MCPA, clopyralid, fluroxypyr and florasulam. Can. J. Plant Sci. 94: 701-708. Annual canarygrass (Phalaris canariensis L.) is a cereal crop that is primarily grown on the Canadian prairies as feed for caged birds. To widen the spectrum of herbicide options for producers, two experiments were conducted with the following nine herbicide treatments (application rates in parentheses expressed as g a.i. ha-1): weed-free control; single and double applications of MCPA (560)+clopyralid (100) (Curtail M); MCPA (562)+fluroxypyr (108) (Trophy); and MCPA (560)+clopyralid (100)+fluroxypyr (144) (Prestige); florasulam (5)+MCPA (420) (Frontline); difenzoquat (700)+MCPA (560)+clopyralid (100) (Avenge+Curtail M); and a single application of difenzoquat (700). Experiment 2 included the same herbicide treatments in factorial combinations with two application times; crop growth stages of two to three leaf (2-3 lf) and four to five leaf (4-5 lf). Experiments were conducted at Indian Head, Scott, and Saskatoon, SK, in 2001 to 2003. In exp. 1, difenzoquat caused up to 30% crop injury when combined with MCPA+clopyralid at the 2× rate, but improved crop yield relative to other herbicides because it reduced yield interference from wild oat infestations at Indian Head in 2002. In exp. 2, the 2× rate of florasulam+MCPA resulted in the greatest visual injury, with higher levels recorded at the 2-3 lf; however, seed yield reduction was greater when applied at the 4-5 lf. In summary, annual canarygrass was tolerant to combinations of MCPA, clopyralid, and fluroxypyr, herbicides which control important weed species in prairie fields.
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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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".