Agri‐environmental Thresholds using Mehlich III Soil Phosphorus Saturation Index for Vegetables in Histosols
Bibliographic record
Abstract
The P concentration in Norton Creek which drains cultivated Histosols in Quebec showed median concentration exceeding up to 14 times the environmental guideline of 0.03 mg total P L(-1). The aim of this study was to develop environmental and agronomic thresholds using soil tests to provide a tool for P management in Histosols. Soil samples were collected from Histosols across Quebec (82) and in fertilizer trials (66) to calibrate soil test methods against the degree of P saturation (DPS(OX)) using the acid-oxalate method and setting alpha(m) = 0.4, and the water-extractable P (P(W)) (Sissingh, 1971). The field trials on crop response to added P were conducted with carrots (8), potatoes (11), onions (10), Chinese cabbage (7), celery (10), and lettuce (20). Relative yields were computed as yield in control without P divided by highest yield with added P. The Mehlich III (M-III) P extraction was more closely related (r(2) = 0.73) to DPS(OX) than the Bray 1 method (r(2) = 0.62) and the Florida extraction method (r(2) = 0.53). The [P/(Al+gammaFe)](M-III) ratio as index of P saturation (IPS(M-III)) was the most closely related to DPS(OX) (r(2) = 0.88) setting gamma = 5. The critical [P/(Al+5Fe)](M-III) ratio of 0.05 at DPS(OX) = 0.25 and P(W) = 9.7 mg P L(-1) was validated by an independent study from North Carolina. The soil group (low- vs. high-IPS(M-III) soils) significantly influenced crop response to added P. Critical agronomic IPS(M-III) values were found between 0.10 and 0.15. Those environmental and agronomic benchmarks are instrumental for managing the P in vegetable-grown Histosols.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".