Nitrogen and sulphur fertilizer management for growing canola on sulphur sufficient soils
Bibliographic record
Abstract
Canola is a crop that demands high nitrogen (N) and sulphur (S) inputs to achieve maximum seed yield. The practice of balancing these two nutrients by applying them in a fixed ratio has shown yield benefits on soils deficient in both these nutrients. A 9 site-year study was conducted between 2002 and 2004 to determine whether this practice is necessary for soils containing sufficient S levels. The practice was tested for both hybrid (HC) and open pollinated (OPC) canola cultivars by applying six rates of N (0, 40, 80, 120, 160 and 200 kg N ha -1 ) and supplementing N rates with S, so that three N:S ratios (1.5, 6 and 12 to 1) were achieved. Seed yield, protein and oil content responses of both HC and OPC cultivars were obtained primarily with N, with no evidence for a need of balancing this nutrient with S additions to achieve a ratio within those applied at this study. Hybrid canola cultivars overall yielded 23.7% more than OPC cultivars when they received the N application rate at which maximum yield of the OPC cultivars was obtained (120 kg N ha -1 ). Application of an additional 30 kg ha -1 to obtain maximum HC seed yield only resulted in an additional 1.5% yield advantage for the OPC. As N application rate was increased, small increases in seed protein levels (≈2.5%) were accompanied by a small reduction (≈2%) in seed oil content. Increased yield by HC compared with OPC canola reduces N residual fertility, hence, assessment of soil fertility status by soil testing after growing HC canola is a highly beneficial management practice. Our results indicate that the practice of balancing N and S to a fixed ratio is unnecessary and wasteful on canola grown on soils containing sufficient S. Key words: Hybrid canola, N:S ratio, open pollinated, residual soil fertility
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".