Soil Test Phosphorus and Phosphorus Availability of Swine Manures with Long‐Term Application
Bibliographic record
Abstract
Core Ideas Net P additions of 9.8 to 16.1 kg ha −1 were needed to increase soil test P by 1 mg kg −1 . Manure P source availability coefficients were 0.99 for liquid manure, 1.08 for solid manure, and 0.97 for composted manure. The long‐term P availability was identical, regardless of the form of swine manure. The long‐term availability of P from swine manure was similar to that of chemical fertilizer. Understanding the form‐specific long‐term effects of manure (liquid, solid, and composted) application on soil P is essential for nutrient management planning. This 8‐yr study aimed to quantify changes in soil test P (STP, Olsen‐P) with application of three forms of swine manure compared with inorganic fertilizer and to calculate the manure P source availability coefficient (PSAC) as the ratio of the specific manure form to inorganic P in providing crop P availability. The STP content increased linearly with both total and net P addition at the surface (0–15 cm) and subsurface (15–30 cm) soil depths, regardless of P source. The slope of STP vs. total or net P addition in the surface layer was steeper for liquid than for solid manure, whereas in the subsurface layer, composted manure showed a greater slope than either liquid or solid manure. The amount of applied P required to increase STP by one unit in the surface layer was 19.9, 15.7, 31.6, and 20.9 kg P ha −1 for inorganic fertilizer and liquid, solid, and composted manure, respectively. When increases in subsoil STP and grain P removal were considered, the net P additions of inorganic fertilizer and liquid, solid, and composted manure needed to increase STP by one unit were 12.2, 9.8, 16.1 and 10.7 kg ha −1 , respectively. The PSAC values were 0.99, 1.08, and 0.97 for liquid, solid, and composted manure, respectively. The long‐term availability of swine manure P was largely identical among forms and was similar to that of inorganic fertilizer.
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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 | 0.000 | 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 | 0.001 |
| 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 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".