Blended soil amendments: A viable strategy to reduce soluble phosphorus in soils
Bibliographic record
Abstract
Abstract Phosphorus (P) loss from soils can contribute significantly toward P enrichment in water bodies, impairing water quality. Application of soil amendments is a viable strategy to decrease soluble P in surface soils. Since soluble P is reduced through different mechanisms that are amendment‐specific, blended amendments could be a better approach than single amendment applications; however, very little information is available on blended amendment effects in reducing P loss from soils. We compared the effectiveness of gypsum (CaSO 4 ·2H 2 O), Epsom salt (MgSO 4 ·7H 2 O), and alum [Al 2 (SO 4 ) 3 ·18H 2 O] applied singly or blended in different ratios in reducing water‐extractable P (WEP) and Mehlich‐3 P of two soils (0‐ to 15‐cm depth) with contrasting P status (Mehlich‐3 P of 7.1 mg kg −1 and 202 mg kg −1 ) from the Red River Valley region in MB, Canada. Ten treatments used for the laboratory incubation study were unamended control, gypsum or Epsom salt at 2.5 or 5 Mg ha −1 , alum at 2.5 Mg ha −1 , and four blended treatments of gypsum: alum or Epsom salt: alum at 1:1 or 2:1. Treated soils were saturated and incubated for 2 weeks and analyzed for WEP (an indicator of risk of P loss) and Mehlich‐3 P (plant‐available P) concentrations. All amendments significantly reduced the WEP concentrations compared to control in both soils. The blended amendments, particularly gypsum–alum blends, performed better than unblended amendments in reducing the potential risk of P loss. Mehlich‐3 P concentration was not influenced by amended treatments, suggesting no significant decrease in plant‐available P with amendments in both soils.
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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 | 0.001 | 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".