Effect of dietary fiber on phosphorus distribution in fresh and stored liquid hog manure
Bibliographic record
Abstract
Diet manipulation is a promising way for reducing phosphorus (P) content in manure and subsequently in surface water. The objective of this study is to clarify the effects of dietary fiber content on P distribution in fresh and stored liquid hog manure. Ten, 25 L liquid manure storage tanks were constructed and operated to simulate farm-based manure storage lagoons. Fifteen pigs were randomly grouped into three pens and the pigs in each pen were fed with a diet of different fiber contents (12%, 16%, and 21%). For 20 weeks, one litre of liquid manure from each pen was fed to each storage tank once a week with 3 replicate storage tanks per diet treatment. The samples of fresh and stored manure, each representing a diet treatment, were analyzed for P distribution along the fractions of dissolved organic, dissolved inorganic, particulate organic, and particulate inorganic. The results showed that fresh manure derived from the high fiber diet contained lower total P concentrations. Of the four fractions of total P, particulate organic P and particulate inorganic P composed 95.3% to 97.5% of total P in the fresh manure. After storage, the dissolved P concentration increased from around 25 ppm to 30–60 ppm. Inorganic P was the main fraction in dissolved P and composed 80% of the dissolved P in stored manure. The dissolved inorganic P, and therefore the total dissolved P were speculated to increase with manure storage time, indicating microbial activity through digestion. It was concluded that a higher fiber diet yielding manure with higher fiber content resulted in enhanced anaerobic degradation during manure storage. This, in return might promote the destruction of organic materials, resulting in the release of P and subsequent formation of inorganic dissolved P.
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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".