The Contrasting Effects of Alum‐Treated Chicken Manures and KH<sub>2</sub>PO<sub>4</sub> on Phosphorus Behavior in Soils
Bibliographic record
Abstract
Alum [KAl(SO)⋅12HO] is often added to chicken manure to limit P solubility after land application. This is generally ascribed to the formation of Al-PO complexes. However, Al-PO complex formation could be affected by the matrix of chicken manure, which varies with animal diet. Alum was added to KHPO (as a reference material) and two manures from typical chicken farms in China, one from an intensive farm (CMIF) and another from free-ranging chickens (CMFR). These were subsequently incubated with soils for 100 d to investigate P transformations. Alum reduced water-soluble colorimetrically reactive phosphorus (RP) from soils amended with manure more effectively than in soils amended with KHPO. Alum addition lowered Mehlich-3 RP in soils with CMFR but had no influence on Mehlich-3 RP in CMIF- or KHPO-amended soils. A comparison of P in digested Mehlich-3 extracts with RP in undigested samples showed significantly increased P in digests of alum-treated CMFR only. Fractionation data indicated that alum treatment increased P in the NHF-RP (Al-P) fraction only in soils with KHPO, but not in soils with manure treatments. Furthermore, NaOH-extracted nonreactive P was markedly higher in soil with alum-treated CMFR relative to normal CMFR. The CMFR manure was assumed to contain higher concentrations of organic P because these chickens were fed grains only. These results suggest that the formation of alum-organic P complexes may reduce P solubility. By comparing alum-treated KHPO and manures, it appears that organic matter in manure could interfere with the formation of Al-PO complexes.
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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) | 0.001 | 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) | 0.001 | 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 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".