Enhancing phosphorus release from struvite with biostimulants
Bibliographic record
Abstract
Struvite is a phosphorus (P)-rich by-product of wastewater treatment facilities that can be recycled as a P source in agriculture. Because struvite is not water soluble, it is solubilized gradually by organic acids released by soil microorganisms and from growing plant roots when used as fertilizer. To speed up the solubilization process, struvite can be combined with biostimulants such as P-solubilizing bacteria (PSB) or earthworm casts (WC). The objective of this greenhouse study was to compare the fertilizer value of struvite, with and without PSB (Bacillus megaterium) or WC, with that of triple superphosphate in two contrasting soils (a low-P soil and a high-P soil). Oat (Avena sativa L.) was grown for 8 wk under a controlled environment, and dry matter yield at harvest, total N and total P uptake, the soil residual Mehlich-3 P, and phosphomonoesterase activity were measured. The high-P soil was unresponsive to P application, but the low-P soil was responsive. In the low-P soil, there was more Mehlich-3-extracted P when struvite was combined with PSB or WC compared with struvite alone, resulting in greater oat dry matter and more total N and more total P uptake. Combining struvite with biostimulants increased total dry matter and total P uptake by an average of 39% and 33%, respectively. We conclude that greater P release from struvite occurs when it is combined with PSB or WC, particularly in low-P soil, but this needs to be confirmed in field-scale studies.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".