Physical and Chemical Changes during Composting of Wood Chip–Bedded and Straw‐Bedded Beef Cattle Feedlot Manure
Bibliographic record
Abstract
In the 1990s, restrictions on incineration encouraged the forest industry in western Canada to develop new uses for their wood residuals by product. One such use was as a replacement for cereal straw bedding in southern Alberta's beef cattle (Bos taurus) feedlot industry. However, use of carbon (C)-rich bedding, such as wood chips, had implications for subsequent composting of the feedlot manure, a practice that was being increasingly adopted. In a 3-yr study, we compared composting of wood chip-bedded manure (WBM) and barley (Hordeum vulgare L.) straw-bedded manure (SBM). There were no significant differences in temperature regimes of SBM and WBM, indicating similar rates of successful composting. Of 17 physical and chemical parameters, five showed significant (P < 0.10) differences due to bedding at the outset of composting (Day 0), and 11 showed significant differences at final sampling (Day 124). During composting (10 sampling times), seven parameters showed significant bedding effects, 16 showed significant time effects, and four showed a Bedding x Time interaction. Significantly lower (P < 0.10) losses of nitrogen (N) occurred with WBM (19%) compared with SBM (34%), which has positive implications for air quality and use as a soil amendment. Other advantages of WBM compost included significantly higher total C (333 vs. 210 kg Mg(-1) for SBM) and inorganic N (1.3 vs. 1.0 kg Mg(-1) for SBM) and significantly lower total phosphorus (4.5 vs. 5.3 kg Mg(-1) for SBM). Our results showed that wood chip bedding should not be a problem for subsequent composting of the manure after pen cleaning. In combination with other benefits, our findings should encourage the adoption of wood chips over straw as a bedding choice for southern Alberta feedlots.
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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) | 0.000 | 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) | 0.000 | 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".