Phosphorus fractions in soil amended with organic and inorganic phosphorus sources
Bibliographic record
Abstract
Information on the P fractions in soils treated with different organic amendments is needed to better manage land application of organic amendments to agricultural soils. This study investigated the forms and distribution of P after 1, 4 and 16 wk in a Lakeland silty clay loam soil using a sequential fractionation procedure. Phosphorus was added at rates of 0, 123, 307 and 614 mg P kg-1 in the form of biosolids, hog manure, cattle manure and fertilizer P. The largest difference among the amendments was in the water-extractable P fraction, which was significantly lower in soil amended with biosolids. Regression analysis showed that the slope of P increment in the H2O fraction as a function of P application rate was four times lower for biosolids (0.06) than for hog manure (0.24) and seven times lower than for fertilizer (0.42) amended soils. In the biosolids-amended soil, there was a net increase of H2O-P, NaOH-Pi and HCl-P fractions at the expense of organic P (NaOH-Po) and residual P fractions after 16 wk of incubation, signifying net P mineralization. In hog manure amended soil, H2O-P decreased by 128 mg kg-1 with a corresponding increase in the NaHCO3-P, possibly due to P sorption during the 16 wk of incubation. The results for cattle manure indicated net immobilization of P as the H2O-P and NaHCO3-P declined while the inorganic P (NaOHPi), HCl-P and residual P increased with incubation time. The transformation of P in fertilizer-amended soil was similar to that of hog manure amended soil. The amount of labile P (defined as H2O-P plus NaHCO3-P) in amended soils followed the order of fertilizer P > hog manure > cattle manure > biosolids. Key words: Phosphorus fractions, sequential P extraction, incubation, organic amendments
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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".