Fate of Coliform Bacteria in Composted Beef Cattle Feedlot Manure
Bibliographic record
Abstract
The link between livestock production, manure management, and human health has received much public attention in recent years. Composting is often promoted as a means of sanitizing manure to ensure that pathogenic bacteria are not spread to a wider environment during land application. In a two-year study (1998 and 1999) in southern Alberta, we examined the fate of coliform bacteria during windrow composting of cattle (Bos taurus) manure from feedlot pens bedded with cereal straw or wood chips. Numbers of total coliforms (TC) and Escherichia coli declined as the composting period progressed. In 1998, TC levels (mean of both bedding types) were log10 7.86 cells g(-1) dry wt. for raw manure on Day 0, log10 3.38 cells g(-1) by Day 7, and log10 1.69 cells g(-1) by Day 14. More than 99.9% of TC and E. coli was eliminated in the first 7 d when average windrow temperatures ranged from 33.5 to 41.5 degrees C. The type of bedding did not influence the numbers of TC or E. coli. Dessication probably played a minor role in coliform elimination, since water loss was low (< 0.07 kg kg(-1)) in the first 7 d of composting. However, total aerobic heterotroph populations remained high (> 7.0 log10 CFU g(-1) dry wt., where CFU is colony forming units) throughout the composting period, possibly causing an antagonistic effect. Land application of compost, with its nondetectable levels of E. coli compared with raw manure, should minimize environmental risk in areas of intensive livestock production.
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 | 0.001 | 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) | 0.000 | 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".