Canola variety, nitrogen, phosphorus, and sulfur fertilization affect yield, quality, and fatty acid profile
Bibliographic record
Abstract
Canola yield and quality are important for food, feed, and industrial end-uses. There may be trade-offs between the agronomic and quality aspects of canola production depending on varietal traits and management. The objective of this work was to assess the effects of nitrogen (N), phosphorus (P), and sulfur (S) fertilization on agronomic and quality properties of canola varieties with distinct oleic acid contents. Nitrogen fertilization rates were 0, 25, 50, or 100 kg·ha−1, P rates were 0 or 30 kg·ha−1, and S rates were 0 or 20 kg·ha−1. Canola was grown in 2003, 2004, and 2005 at Brandon, a private farm close to Brandon, and at Lacombe, Canada. Canola yields averaged 2.36 t·ha−1 for conventional, 2.53 t·ha−1 for low, and 2.2 t·ha−1 for the high oleic acid varieties at maximum fertilization of N, P, and S. The high oleic acid variety averaged 75% oleic acid content, whereas the low variety averaged 65%, and the conventional variety 62%. Total saturated fatty acids were greatest with the conventional oleic acid variety, and tended to increase with N, decrease with S, and were not influenced by P. The high oleic acid variety yielded slightly less than the other two varieties but tended to have lower glucosinolate and saturated fatty acid contents. This work could have implications for human nutrition or other end-uses. Current canola varieties and fertility management should be studied to produce canola with quality tailored for the end use.
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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 | 0.000 |
| 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) | 0.001 | 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".