Phosphorus distribution with respect to particle size and microbial activity in dairy manure and implications for manure management
Bibliographic record
Abstract
This work investigated the distribution of phosphorus in dairy manure as it relates to particle size and provides experimentally derived insights for improving the management of phosphorus. The data presented here illustrates some aspects of manure handling that may be optimized for controlling the distribution of phosphorus. It provides experimental data that supplements existing literature by 1) extending the limits of study regarding particle size distribution; 2) extending the limit of centrifugal forces studied; 3) demonstrating an improved pathway for phosphorus management in wastewater using a substrate mediated flocculation process; and 4) providing some experimental observations showing that the microbiota present in dairy manure can diminish stratification of suspended solids and phosphorus concentrations within separated liquid manure products. Further, based on quadratic modeling of phosphorus relative to sieve size, and the observations that accompanied progressive washing and mechanical agitation performed, a convincing argument for relating phosphorus distribution to the surface area of a substrate is made. The findings imply that much of the phosphorus present in manure is superficially bound to larger particulates, rather than an intrinsic or chemical part of the bulk material itself, and can be mediated by washing or mechanical means where the phosphorus present in coarser fractions can be shunted towards finer or liquid fractions. Approximately 80% of phosphorus was associated with particulates bound to larger substrate. Indeed, 95.5% of the phosphorus in the bulk manure was removable as particulates with cross sectional diameter less than 2mm by simple washing. Further removal of phosphorus in >2mm substrate through fermentation and leaching was also demonstrated. Some portion of this distribution in phosphorus appears to be dominated by microbes.,
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".