Solubility and transport of phosphate and the accompanying ions as influenced by sulphate salts in a model calcareous soil system
Bibliographic record
Abstract
Plant availability of phosphorus (P) in calcareous soil can be improved by modifying the chemical environment of the soil-P fertilizer reaction zone through the banding of non-phosphate fertilizer with P. We investigated the solubility and diffusive transport of P as influenced by addition of two sulphate salts [(NH4)2SO4 and K2SO4] to NH4H2PO4 and KH2PO4. The salts were applied to a series of wax columns packed with approximately 223 g of Ca2+-saturated cation exchange resin-sand mixture buffered with CaCO3. The background pH of the mixture was 8.8. Each treatment contained approximately 204.5 mg P kg-1 soil, while 632.3 mg SO42- kg-1 soil was added to each P source for treatments containing the dual bands to provide a molar concentration of P and SO42- of 6.6 mmol kg-1 soil. After 2 wk of incubation, column segmentation and extraction showed that H+ moved deeper into the columns on addition of the sulphate salts compared with adding NH4H2PO4 or KH2PO4 alone. The maximum depth of P penetration in the columns containing NH4H2PO4 was 4.2 cm, while P transport in the columns treated with KH2PO4 was restricted to the top 4.0 cm depth. Addition of (NH4)2SO4 or K2SO4 to NH4H2PO4 increased the concentration of water-extractable P by 43 and 21%, respectively, above that in NH4H2PO4 alone. Similarly, addition of (NH4)2SO4 or K2SO4 increased the concentration of water-soluble P by 48 and 41%, respectively, above the amount in KH2PO4 alone. The increased water solubility of P on addition of the sulphate salts was attributed to anion competition between HPO42- and SO42- for precipitation with Ca2+. We also observed ionic competition between NH4+ and K+ when both cations were added together, causing K+ to travel farther into the column and with increased solubility than when applied alone. Our results showed that anion and cation competition can be used to modify the transport and solution concentration of ions through dual banding. These results also suggested that the combination of anion competition by SO42- and pH reduction due to salt effect could have a positive influence on the availability of P in calcareous soils. Key words: Phosphate, sulphate, columns, solubility, diffusive transport, resin
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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".