Effects of Soil Factors on Phytotoxicity and Dissipation of Sulfentrazone in Canadian Prairie Soils
Bibliographic record
Abstract
Studies were conducted to examine the effects of soil properties on sulfentrazone phytotoxicity and dissipation under laboratory conditions. The pH values of five soils from Saskatchewan were altered through acidification with hydrochloric acid (HCl) and alkalization with calcium carbonate (CaCO3). The phytotoxicity of sulfentrazone to sugar beet (Beta vulgaris L. Beta 1385), determined using a shoot length bioassay, was reduced when soil pH was lowered and was greater when soil pH increased. Concentrations corresponding to 50% inhibition (I50 values) obtained from the dose–response curves were correlated with soil pH, demonstrating the relationship between soil pH and sulfentrazone phytotoxicity. Dissipation of sulfentrazone was examined in soils incubated at 25 °C and moisture content of 85% field capacity. Sulfentrazone dissipation followed a two-compartment model, and sulfentrazone half-lives estimated from the dissipation curves ranged from 21 to 111 days. Half-lives were correlated with soil pH (R = –0.857, p = 0.014) and soil organic carbon content (R = 0.790, p = 0.034) but not with clay content (R = 0.287, p = 0.533). Soil characteristics, particularly soil pH and organic carbon content, affect the bioactivity of sulfentrazone and influence both sulfentrazone efficacy in weed control and its potential for carry-over injury to subsequent crops.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".