Production of composted recycled manure solids from a Canadian dairy farm: impact on microbial air quality in experimental conditions
Bibliographic record
Abstract
Recycled manure solids (RMS) produced in dairy farms from fresh manure need to be sanitized before using them as bedding material. However, the impact on air quality of composting RMS remains unknown. Four RMS composting methods were tested during a 10-day aging of piles in experimental chambers: static windrow (SW), turned windrow (TW), SW following drum composting for 24 h (DC24) or SW following drum composting for 72 h (DC72). Air samples were collected using a SASS®3100 Dry Air Sampler on days 0 (pilling of the RMS), 5 and 10. Bacteria (16S rRNA genes), Penicillium/Aspergillus, A fumigatus, and 11 human pathogenic bacteria (e.g. Klebsiella pneumonia) were quantified by qPCR while endotoxins and dust particles were respectively measured by LAL assays and with a DustTrakTM DRX Aerosol Monitor. On day 0, RMS produced by SW and TW yielded the lowest concentrations of airborne bacteria, while DC24 resulted in the lowest levels of Penicillium/Aspergillus and dust particles. SW method led on day 5 to the lowest concentration of bacteria and Penicillium/Aspergillus, and DC24 and DC72 to the lowest concentration of airborne dust. On day 10, SW and TW piles were associated with the lowest levels of Penicillium/Aspergillus and dust particles. A significant difference was observed between concentration of airborne bacteria, Penicillium/Aspergillus and endotoxins before and during the turnover of TW piles. None of the studied human pathogens was detected in the air samples. Results of the present study suggest that SW and TW are the most promising methods for the production of composted RMS with respect to microbial air quality. However, the experimental chambers do not accurately represent commercial dairy barns and further research on these composting methods is necessary. Finally, the study highlights that bedding material and its management may be determinant factors for air quality in dairy barns. The manuscript entitled “Production of composted recycled manure solids from a Canadian dairy farm: impact on microbial air quality in experimental conditions” is a technical paper (air pollution).The research evaluated the impact on microbial air quality of composting recycled manure solids (RMS) produced from fresh cow manure. RMS need to be composted or sanitized before using them as bedding material for animals. The impact on animal health of RMS still needs to be confirmed, while the effect on air quality and the health of dairy farmers is unknown. In the present study, microbial air quality associated with four RMS composting methods was investigated. Data revealed that two methods resulted in lower aerosolization of dust particles, endotoxins, molds and bacteria. The manuscript entitled “Production of composted recycled manure solids from a Canadian dairy farm: impact on microbial air quality in experimental conditions” is a technical paper (air pollution). The research evaluated the impact on microbial air quality of composting recycled manure solids (RMS) produced from fresh cow manure. RMS need to be composted or sanitized before using them as bedding material for animals. The impact on animal health of RMS still needs to be confirmed, while the effect on air quality and the health of dairy farmers is unknown. In the present study, microbial air quality associated with four RMS composting methods was investigated. Data revealed that two methods resulted in lower aerosolization of dust particles, endotoxins, molds and bacteria.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".