Fertilizer Nitrogen, Phosphorus, Potassium, and Sulphur Effects on Forage Yield and Quality of Timothy Hay in the Parkland Region of Saskatchewan, Canada
Bibliographic record
Abstract
For producers in the Parkland zone of Canadian prairies, timothy (Phleum pratense L.) hay provides another opportunity for crop diversification and there is potential for an increase in the production area. The objective of this study was to determine the influence of nitrogen (N) (0 to 200 kg N ha−1), phosphorus (P) (0 to 87.5 kg P ha−1), potassium (K) (0 to 62.5 kg K ha−1), and sulphur (S) (0 to 40 kg S ha−1) fertilization rates on forage dry matter yield (DMY) and quality of timothy (cv. Drummond) grown for hay under dryland conditions. Forage quality measurements included percentage of leaf, stem and head, head length, protein content (PC), neutral detergent fiber content (NDF), and acid detergent fiber content (ADF). The field experiments were conducted at Buchanan, Saltcoats, Carrot River, and Star City in the Parkland zone of Saskatchewan, Canada. The fertilizer sources were ammonium nitrate for N, triple super phosphate for P, muriate of potash for K, and potassium sulphate for S. The fertilizers were surface-broadcast annually in mid to late April. The application of N at the three sites (Buchanan, Saltcoats, and Star City) markedly increased DMY, usually increased the percentage of leaf and head, head length and PC, reduced the percentage of stem and had no consistent effect on NDF and ADF. The DMY increased moderately with P and K application at Carrot River, and with S application at Star City. The percentage of leaf, stem and head, head length, PC, NDF, and ADF showed no response to P, K, or S fertilizer applications. In summary, the application of N at Buchanan and Saltcoats, P and K at Carrot River, and N and S at Star City were considered essential for optimum forage yield and quality of timothy.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".