Estrone and 17β-estradiol mineralization in liquid swine manure and soil in the presence and absence of penicillin or tetracycline
Bibliographic record
Abstract
Natural steroid estrogens (e.g., 17 β-estradiol) and antibiotics (e.g., penicillin) are chemicals detected in livestock manure storage facilities and in manure-amended agricultural soils. The fate of natural steroid estrogens in these media has been studied for the past two decades but seldom in association with antibiotics. This factorial experiment examined estrone (E1) and 17 β-estradiol (E2) mineralization in liquid swine manure, soil and manure-amended soil containing 0, 40 and 200 mg kg−1 penicillin or tetracycline. Maximum mineralization (MAX) across treatments ranged from 13.5% to 49.9% for E1 and from 15.4% to 51.2% for E2. Estrogen mineralization almost always significantly decreased in the order of: manure > soil amended with a low rate of manure = soil > soil amended with a high rate of manure, suggesting that periodically agitated manure was a more favorable medium for biotic removal of estrogens than soil. Both rates of tetracycline in manure induces a lag phase of 40 to 50 days prior to the onset of a log phase of mineralization, and tetracycline at 200 mg kg−1 significantly decreased E1 and E2 MAX in manure. For soils amended with a high rate of manure, penicillin at 200 mg kg−1 significantly decreased E1 and E2 MAX and also the other antibiotic additions resulted in numerically lesser E1 and E2 MAX values, relative to soils free of antibiotics. We conclude that storage of liquid swine manure for 3 to 4 months with periodic agitation prior to application to agricultural land may reduce the potential for estrogens to become environmental contaminants, but that the persistence of estrogens in manure storage lagoons is also influenced by farm management practices such as the types and rates of antibiotics administered to livestock. When both estrogens and antibiotics are present in manure applied to soils, estrogens may have slower dissipation rates in soil particularly when manure is applied at high rates or not mechanically incorporated in the surface horizon.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".