Phosphorus Speciation in Broiler Litter and Turkey Manure Produced from Modified Diets
Bibliographic record
Abstract
Modifying poultry diets by reducing mineral P supplementation and/or adding phytase may change the chemical composition of P in manures and affect the mobility of P in manure-amended soils. We studied the speciation of P in manures produced by broiler chickens and turkeys from either normal diets, or diets with reduced amounts of non-phytate phosphorus (NPP) and/or phytase, using a combination of chemical fractionation and synchrotron X-ray absorption near edge structure (XANES) spectroscopy. All broiler litters were rich in dicalcium phosphate (65-76%), followed by aqueous phosphate (13-18%), and phytic acid (7-20%); however, no hydroxylapatite was observed. Similarly, normal turkey manure had 77% of P as dicalcium phosphate and had no hydroxylapatite, while turkey manure from diets that had reduced NPP and phytase contained equal proportions of dicalcium phosphate (33-45%) and hydroxylapatite (35-39%). This is attributed to the higher total Ca to P ratio (>2) in modified turkey manures that resulted in transformation of more soluble (dicalcium phosphate) to less soluble P compounds (hydroxylapatite). Chemical fractionation showed that H2O-extractable P was the predominant form in broiler litter (56-77%), whereas aqueous phosphate determined with XANES was <18% indicating that H2O probably dissolved mineral forms of P (e.g., dicalcium phosphate). Results show that HCl extraction primarily removed phytic acid from broiler litters and normal turkey manure, while it removed a mixture of hydroxylapatite and phytic acid from modified turkey manures. The combination of chemical fractionation and XANES provided information about the nature of P in these manures, which may help to devise best management practices for manure use.
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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 | 0.001 | 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".