Fate of metolachlor under subirrigation in a sandy soil: A lysimeter study
Bibliographic record
Abstract
A three-year field lysimeter study was conducted to investigate the role of subirrigation systems in reducing the risk of water pollution from metolachlor (2-chloro-N-(2-ethyl-6-methlphenyl)-N-(2-methoxy-1-methylethyl)ace tamide). Nine large PVC lysimeters, 1 m long x 0.45 m diameter, were packed with a sandy soil. Three water table management treatments, i.e. two subirrigation treatments with constant water table depths of 0.4 and 0.8 m, respectively, and a free drainage treatment in a completely randomized design with three replicates were used. Corn (Zea mays L.) was grown in each lysimeter, and at the beginning of summer of each year metolachlor was applied, at the locally recommended rate of 2.75 kg a.i./ha. Soil and water samples were collected at different time intervals after each natural or simulated rainfall event. Metolachlor was extracted from these samples and analyzed using Gas Chromatography. Results obtained in this three year study, (1993-1995), lead to the conclusion that metolachlor is quite mobile since it leached to a depth of 0.85 m below the soil surface quite early in the growing season. Metolachlor concentrations decreased with depth as well as with time. The shallower water table in the 0.4 m subirrigation treatment showed less residues in the soil solution than that of other treatments. However, a mass balance study, supported by an independent laboratory investigation, shows that water table management, statistically, has no significant effect on the reduction of metolachlor residues in sandy soils.
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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) | 0.000 | 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 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".