Nitrous oxide and carbon dioxide emissions from soils amended with compost and manure from cattle fed diets containing wheat dried distillers’ grains with solubles
Bibliographic record
Abstract
The N2O and CO2 emissions from soil amended with cattle manure and compost from animals fed a diet including wheat dried distillers’ grains with solubles (DDGS) were evaluated in a 105 d aerobic incubation study in the laboratory. Manure (BM) and compost (BC) from cattle fed a typical finishing diet containing barley, and manure (DDGSM) and compost (DDGSC) from cattle fed a diet containing 60% wheat DDGS replacing barley grain, were used. A nonamended control (soil without manure or compost) was included for comparison. Organic amendments significantly increased N2O and CO2 emissions compared with the control, and manure resulted in significantly higher CO2 emissions than compost. Adding DDGS to cattle diet resulted in significantly higher N2O emission amounts and emission factors from soil regardless of whether the amendment was manure or compost, mainly due to increased NH4+-N content. While N2O emissions were lower in soil amended with DDGSC than DDGSM, there was no difference in N2O emissions when soils were amended with BM and BC. Our results suggest that across diet types and management approaches, application of compost from cattle fed a typical diet could be less detrimental to the environment with relatively lower emissions of CO2 and N2O.
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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 | 0.001 | 0.001 |
| 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".