Survival of Escherichia coli in Beef Cattle Fecal Pats Under Different Levels of Solar Exposure
Bibliographic record
Abstract
Understanding the survival and transport of Escherichia coli in feces on land and in water is important when trying to assess contamination of water by grazing animals. A fecal-pat experiment was conducted in July and August of 2003 to investigate the survival of E. coli under 4 levels of solar exposure controlled by using shade cloth. Fresh beef cattle manure was uniformly blended to produce 2.5- and 1.6-kg fecal pats, which were placed in plastic trays or in contact with the soil and covered with 0%, 40%, 80%, or 100% shade cloth treatments and replicated 5 times. Samples from each fecal pat were collected at Time 0 to establish E. coli levels; sampling was repeated at Day 1, Day 3, and approximately weekly thereafter for 45 days to determine die-off. E. coli concentration and percent moisture were measured for each fecal sample. At the end of the experiment, fecal pats under the 0% shade cloth had the lowest E. coli concentrations, followed by the 40%, 80%, and 100% treatments, with 0.018, 0.040, 0.11, and 0.44 X 10^6 colony-forming units (CFU) g-1, respectively. Fecal-pat size was significant only on Day 17, when large fecal pats had higher concentrations of E. coli (P < .0001). There was no significant difference (P = 0.43) in E. coli concentration between the fecal pats in contact with the soil vs. those in plastic trays. Percent moisture of fecal pats was not a good covariate. Age of fecal pats, as well as exposure to solar radiation negatively influences the survival of E. coli. From a management perspective, E. coli in fecal pats under forested situations would survive longer than in open grasslands due to shading, and any possible contamination by E. coli would be greatest within 7 days of removing cattle from a riparian area or pasture.
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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 | 0.001 | 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".