Agronomic and Environmental Soil Phosphorus Testing in Soils Receiving Liquid Swine Manure
Bibliographic record
Abstract
There is uncertainty concerning evaluation of bioavailable P in manured soils. This study assessed P availability in manured Iowa soils by measuring soil P with agronomic and environmental P tests and P uptake by corn ( Zea mays L.) and soybean [ Glycine max (L.) Merr.]. Soil and plant samples were collected at the V5‐V6 growth stage from trials established at nine locations that received various rates of liquid swine ( Sus scrofa ) manure, and from farmers' fields that received other animal manures. Soil P was analyzed by the Bray‐P1 (BP), Olsen (OP), and Mehlich‐3 (M3P) agronomic tests, and by the Fe‐oxide impregnated filter paper (FeP), anion‐exchange resin membrane (RP), and water (WP) environmental tests. Soil P at a 15‐cm depth ranged from deficient to 15 times optimum levels for crops. Extracted P was highest for BP, M3P, and RP, intermediate for OP and FeP, and lowest for WP. Relationships between soil P extracted by the tests were linear, trends were similar for manured and unmanured plots, and correlation coefficients were ≥0.70 (correlations were poorest for WP). There was no conclusive evidence for differences between tests in detecting manure‐derived soil P at most sites. However, in some conditions BP, M3P, OP, and RP may extract proportionally more manured‐derived P than FeP and WP. Only the agronomic tests were significantly correlated (0.42 for M3P, 0.44 for BP, and 0.47 for OP) with plant P uptake across sites. Agronomic soil tests would predict plant P availability for crops better than environmental P tests in soils receiving liquid swine manure.
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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) | 0.001 | 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".