Odor Measurements for Manure Spreading Using a Subsurface Deposition Applicator
Bibliographic record
Abstract
Odor emissions during manure spreading events have become a source of concern, particularly where farms are located nearby urban areas. The objective of the present study was to compare odor concentrations and odor emission rates due to pig manure application using two different types of applicators, a sub-surface deposition system and a conventional splash-plate applicator. Air samples were collected using a Surface Isolation Flux Chamber and the "bag-in-vacuum chamber" techniques, at 0.5, 1.5 and 2.5 hours after manure application. A three-station forced-choice dynamic dilution olfactometer was used by an odor panel for determining odor concentration. Preliminary results indicated that with the sub-surface deposition system applicator odor emission rate was reduced by 8% to 38% compared to that of the conventional splash-plate applicator. The highest reduction in odor strength and odor emission rate was observed in the most offensive period after manure application. The sub-surface deposition system may be a solution for hog producers who wish to reduce odor complaints from applying manure without the cost and problems associated with deep injection systems.
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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 | 0.000 | 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".