Effect of application timing of glyphosate and saflufenacil as desiccants in dry edible bean (Phaseolus vulgaris L.)
Bibliographic record
Abstract
McNaughton, K. E., Blackshaw, R. E., Waddell, K. A., Gulden, R. H., Sikkema, P. H. and Gillard, C. L. 2015. Effect of application timing of glyphosate and saflufenacil as desiccants in dry edible bean (Phaseolus vulgaris L.). Can. J. Plant Sci. 95: 369-375. Early application of desiccants in dry edible bean may cause yield reductions and unacceptable herbicide residue levels, resulting in rejection of exported shipments. The effect of application timing of two registered desiccants, glyphosate and saflufenacil, was examined in 12 field trials conducted over a 4-yr period (2009-2012) at Exeter, Ontario, Carman, Manitoba, and Lethbridge, Alberta. Desiccants were applied alone and in combination at five crop maturation stages. When glyphosate or saflufenacil alone, or in combination, was applied at 100% crop maturity, herbicide residue levels were acceptable (less than 2.0 and 0.01 ppm for glyphosate and saflufenacil, respectively) and there was no reduction in yield or hundred seed weight. Glyphosate residues remained below 2.0 ppm when the desiccant was applied alone or with saflufenacil at 75% crop maturity, but crop yield decreased by 16% compared with the untreated control when glyphosate and saflufenacil were combined. Residue levels were unacceptable when glyphosate was applied at 0, 25, and 50% maturity; generally the earlier glyphosate was applied, the greater the residue concentration in the seeds at harvest. Although no application timing resulted in saflufenacil residues above 0.01 ppm, crop yield was reduced when the desiccant was applied at 0, 25, 50, and 75% crop maturity. This information will provide dry bean processors with the necessary information to design guidelines concerning the application timing of glyphosate and saflufenacil so that bean yield and quality remain unaffected and seed residues remain below accepted levels.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".