Response of organic grain and forage crops to struvite application in an alkaline soil
Bibliographic record
Abstract
Abstract Struvite (NH4MgPO4·6H2O) may be an appropriate fertilizer to address phosphorus (P) deficiencies in organic cropping systems, but field studies assessing crop response to struvite are lacking. Field experiments were conducted over 3 yr on a low‐P, alkaline soil in Manitoba to assess the effect of struvite application rate on the yield and P accumulation of organically managed grain and forage crops. Struvite was applied to spring wheat (Triticum aestivum L.) and flax (Linum usitatissimum L.) at 0, 20, 30, and 40 kg P ha–1 in separate experiments each year and to alfalfa (Medicago sativa L.)–grass forage at 0, 30, 60, and 90 kg P ha–1 in a single application in a 3‐yr experiment. Wheat grain yield, P concentration, and P accumulation increased linearly with increasing struvite rate, whereas flax showed little to no response. Forage yield, P concentration, and P accumulation also increased with struvite rate. Benefits to forage yield and P accumulation were greatest in the second year, demonstrating important residual effects of struvite application. Struvite application shifted forage composition to become dominated by alfalfa whereas the unfertilized treatment was dominated by grasses. Annual P recovery efficiency was 4–7% for wheat, 1–2% for flax, and 7–12% for forage and did not vary significantly with struvite application rate. Our findings demonstrate that struvite applied at a relatively high rate is an effective P source for wheat and alfalfa‐based forage under organic management, but not for flax.
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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".