Intermittent agitation of liquid manure: effects on methane, microbial activity, and temperature in a farm-scale study
Bibliographic record
Abstract
Liquid manure storages are a significant source of methane (CH4) emissions. Farmers commonly agitate (stir) liquid manure prior to field application to homogenize nutrients and solids. During agitation, manure undergoes mechanical stress and is exposed to the air, disrupting anaerobic conditions. This on-farm study aimed to better understand the effects of agitation on CH4 emissions, and explore the potential for intentional agitation (three times) to disrupt the exponential increase of CH4 emissions in spring and summer. Results showed that agitation substantially increased manure temperature in the study year compared to the previous year, particularly at upper- and mid-depths of the stored manure. The temporal pattern of CH4 emissions was altered by reduced emissions over the subsequent week, followed by an increase during the second week. Microbial analysis indicated that the activity of archaea and methanogens increased after each agitation event, but there was little change in the populations of methanogens, archaea, and bacteria. Overall, CH4 emissions were higher than any of the previous three years, likely due to warmer manure temperatures that were higher than the previous years (despite similar air temperatures). Therefore, intermittent manure agitation with the frequency, duration, and intensity used in this study is not recommended as a CH4 emission mitigation practice.Implications: The potential to mitigate methane emissions from liquid manure storages by strategically timed agitation was evaluated in a detailed farm-scale study. Agitation was conducted with readily-available farm equipment, and targeted at the early summer to disrupt methanogenic communities when CH4 emissions increase exponentially. Methane emissions were reduced for about one week after agitation. However, agitation led to increased manure temperature, and was associated with increased activity of methanogens. Overall, agitation was associated with similar or higher methane emissions. Therefore, agitation is not recommended as a mitigation strategy.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".