Effectiveness of an elemental sulfur fertilizer in an oilseed‐cereal‐legume rotation on the Canadian prairies
Bibliographic record
Abstract
Abstract Adequate sulfur (S) nutrition is critical for sustaining yields in crop rotation systems. Because of slow oxidation of elemental S (S°), research on S° fertilizers has emphasized improving the short‐term availability, while the long‐term effects of S° have been overlooked. The effectiveness of a dispersible granule S° fertilizer (SF: Sulfer95), consisting of S° particles smaller than any S° fertilizer reported in literature (< 44 μm in diameter), was compared to gypsum (CS: CaSO4) and ammonium sulfate [AS: (NH4)2SO4] in a three‐year experiment (1997—1999) on a moderately S deficient Black Chernozem soil (Typic Cryoboroll). The three S fertilizers were applied to canola (Brassica rapaL.) at 20, 40, and 80 kg S ha‐1, supplemented with corresponding rates of nitrogen (N) fertilizer in the first year. The control treatment (CT) received N only. Barley (Hordeum vulgareL.) and peas (Pisum sativumL.) were grown in the second and third years to test the availability of residual S. Although the yield of canola in SF fertilized treatments was only slightly higher than in CT, available S provided by SF produced a higher physiological S efficiency (PSE). Superior yields with residual SF were obtained in the second and third years by barley and peas at the rate of 80 kg S ha‐1applied in the first year, indicating that slow oxidation of SF was beneficial to the crops subsequently grown. Over three years, the total crop S uptake was 21, 4.0, and 15% higher with SF than with CT, CS, and AS, respectively.
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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 | 0.001 | 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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".