Phosphorus Fractions in Manure from Growing Pigs Receiving Diets Containing Micronized Peas and Supplemental Enzymes
Bibliographic record
Abstract
Different livestock feeds manipulations have been reported to reduce the total P concentration in manure. Information on the influence of these dietary manipulation strategies on the forms of P in manure is, however, limited. This study was, therefore, conducted to investigate the effect of diet manipulation through feed micronization and enzyme supplementation on the forms of P in swine manure. Eight growing pigs were fed four diets: barley-raw pea (BRP), barley-micronized pea (BMP), barley-raw pea with enzyme (BRPE), and barley-micronized pea with enzyme (BMPE) in a 4 x 4 Latin square design. Because we are interested in the effect of enzyme cocktail and pea micronization on manure P, we did not reduce the non-phytate P with enzyme addition in this study. The fecal material and urine were collected and analyzed for total P. Fecal material was fractionated to determine the total P in H2O-, NaHCO3-, NaOH-, and HCl-extractable fractions. The total P in the residual fractions was also determined. About 98% of the total P excreted by the pigs was found in the fecal material. Inclusion of micronized pea in pig diet did not have any significant effect (p > 0.1) on either the total P or the different P fractions in the manure. The labile P (the sum of H2O-P and NaHCO3-P) was significantly reduced (p < 0.05) by the addition of enzyme to swine diets. Pigs fed the BRPE and BMPE had 14 and 18% lower labile P, respectively, compared with pigs fed the BRP. Enzyme addition to pig diets reduced not only the total P in manure, but also the labile P fraction, which is of great environmental concern. Thus, the potential of P loss to runoff and the subsequent eutrophication can be reduced by enzyme addition to pig diets.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".