Sustainable re-use of dairy cow manure as bedding and compost: Nutrients and self-heating potential
Bibliographic record
Abstract
Dairy farm operations rely on a continuous supply of bedding material for cow comfort and hygiene.The re-use of liquid manure for this purpose has become possible after solid/liquid separation of the manure stream and 24 h processing of the separated solids through a tumbling drum composter.The finished bedding solids are reported to produce superior bedding to regular straw and the separated liquid stream can be retained as crop fertilizer.Off-farm export as bedding is only possible if the material is stable to prevent re-heating if bagged or piled.The nutrient value of the retained liquid and the quality of solids for export were investigated on a Canadian dairy farm by examining nitrogen and phosphorus distribution, as well as the self-heating potential of the composted solids.The effect of curing the solids for an additional 4 weeks during both summer and winter operations was evaluated.Results showed that the solids separation and 24 h drum composting process did not result in a compost that could be classified as mature and stable.However, further curing the solid product in ambient temperature piles for 4 weeks reduced compost re-heating from 26.2°C above ambient to 7.7°C (winter curing) and 3.8°C (summer curing).Nitrogen and phosphorus analysis revealed little difference between the liquid stream (post solid separation) and the incoming raw manure on a wet weight basis.The use of either of these products as plant fertilizer is similar and solid separation does not impact the agronomic value of the liquid manure.
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 | 0.000 | 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".