Phosphate Sorption and Release in a Sandy‐Loam Soil as Influenced by Fertilizer Sources
Bibliographic record
Abstract
Soil phosphate (PO 4 –P) sorption and release is affected by reactions at the solution–soil surface interface. The objective of this study was to determine how the net negative surface charge and phosphate adsorption/desorption processes in a sandy‐loam soil were affected by cattle manure and inorganic fertilizer applications. The soil came from a field experiment where manure and triple superphosphate (TSP) were applied annually on an equivalent plant‐available P basis. After 4 yr, manured soils had 37% more negative surface charge in soil suspensions from pH 4 to 7 than TSP‐fertilized soils. Phosphate adsorption was 23% lower in soils receiving manure than TSP. The phosphate adsorption data (adsorption of added phosphate + native adsorbed phosphate) was modeled with the Langmuir 2‐surface equation, which revealed that the binding strength for phosphate, including native adsorbed phosphate, was about 50% less in the manured soils than the TSP‐fertilized soils. These results suggest that manure applications that increase the net negative surface charge also reduce the soil phosphate adsorption capacity. The cumulative desorbed phosphate was twofold greater from manured soils than TSP‐fertilized soils. This confirmed the results from phosphate adsorption isotherms showing that phosphate was weakly bound in manured soils, compared with TSP‐fertilized soils. We found that manuring not only decreased phosphate retention by the soil but also increased phosphate release into the soil solution, and thus may lead to greater transport of phosphate from agricultural land to waterways.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| 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".