Variations in the Physical Properties and Microbial Community of Dairy Cow Manure—Implications for Testing and Efficacy of Footbathing Products
Bibliographic record
Abstract
Footbaths containing disinfectants are used on dairy farms to reduce the spread of digital dermatitis; however, they commonly become contaminated with manure. This trial investigated the physical properties and microbial composition of dairy cow manure from two production systems and examined whether the source of manure impacted the efficacy of footbathing disinfectants. Manure was collected from eighteen dairy cows, nine housed and fed grass silage (HOUSED) and nine at pasture (PASTURE). The pH and dry matter content was determined, total DNA was extracted and the region v3-v4 of the 16s rRNA gene sequenced. The efficacy of formalin and two trial products (TP1: peracetic acid and hydrogen peroxide; TP2: chlorocresol and triamine) was evaluated when mixed with manure from the two production systems. Production system differences were found in manure dry matter content, bacterial microbiome and the efficacy of both trial footbathing products but not formalin. The properties of manure affected the results of laboratory testing and therefore have the potential to influence footbathing disinfectant efficacy when footbaths are contaminated with manure. Further research into the impact of organic contaminants on the efficacy of disinfectants could facilitate the development of improved testing programmes and disinfectant products.
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 | 0.001 | 0.001 |
| 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".