Effect of recycled manure solids as bedding on bulk tank milk and implications for cheese microbiological quality
Bibliographic record
Abstract
The dairy farm environment influences the raw milk microbiota and consequently affects milk processing. Therefore, it is crucial to investigate farm management practices such as the bedding materials. The aim of this study was to evaluate the effect of recycled manure solids (RMS) as bedding material on bulk tank milk and microbiological implications for cheese quality. Bulk tank samples were collected from 84 dairy farms using RMS or straw bedding. The use of RMS did not influence thermophilic and mesophilic aerobic viable counts from spores. However, straw-milk samples gave higher values for mesophilic anaerobic spore-forming bacteria (0.44 log cfu/mL) than RMS-milk samples (0.17 log cfu/mL). The presence of thermoresistant lactic acid bacteria was not increased in milk from farms using RMS. Nevertheless, taxonomic profiles of thermoresistant bacteria isolated were different between the 2 types of milk. More Enterococcus faecalis and Streptococcus spp. were identified in RMS-milk samples. Thermoresistant enterococci and streptococci could easily end up in cheese. Therefore, milk proteolytic activities of these isolates were tested. Neither Streptococcus spp. nor Enterococcus faecium isolates exhibited proteolytic activities, whereas 53% of E. faecalis showed some. Also, only 1 vancomycin-resistant enterococcus was detected. Survival of selected RMS-milk samples isolates (3 E. faecalis and 1 Streptococcus thermophilus) was evaluated during a model Cheddar cheese manufacture. Although those strains survived well, they did not modify the acidification curve of milk. However, they might cause organoleptic defects during cheese maturing.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".