Transport of Lincomycin to Surface and Ground Water from Manure‐amended Cropland
Bibliographic record
Abstract
Livestock manure containing antimicrobials becomes a possible source of these compounds to surface and ground waters when applied to cropland as a nutrient source. The potential for transport of the veterinary antimicrobial lincomycin to surface waters via surface runoff and to leach to ground water was assessed by monitoring manure-amended soil, simulated rainfall runoff, snowmelt runoff, and ground water over a 2-yr period in Saskatchewan, Canada, after fall application of liquid swine manure to cropland. Liquid chromatography tandem mass spectrometry was used to quantify lincomycin in all matrix extracts. Initial concentrations in soil (46.3-117 mug kg(-1)) were not significantly different (p > 0.05) for manure application rates ranging from 60,000 to 95,000 L ha(-1) and had decreased to nondetectable levels by mid-summer the following year. After fall manure application, lincomycin was present in all simulated rainfall runoff (0.07-2.7 mug L(-1)) and all snowmelt runoff (0.038-3.2 mug L(-1)) samples. Concentrations in snowmelt runoff were not significantly different from those in simulated rainfall runoff the previous fall. On average, lincomycin concentrations in ephemeral wetlands dissipated by 50% after 31 d. Concentrations of lincomycin in ground water were generally <0.005 mug L(-1). This study demonstrates that the management practice of using livestock manure from confined animal feeding operations as a plant nutrient source on cropland may result in antimicrobial transport to surface and ground waters.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".