Effect of N on Yield and Chemical Profile of Winter Canola in Mississippi
Bibliographic record
Abstract
There is increased interest in winter canola as an oilseeds crop for production of oil or biodiesel in the southeastern United States, but research has been limited. The objective of this study was to evaluate the effect of N (0, 60, 120, 180 kg N ha⁻¹) on productivity, oil content and oil composition of winter canola grown for two cropping seasons at three locations in Mississippi (Stoneville, and two locations at Verona: Verona upland silt loam, Verona-SL and Verona upland clay, Verona-C). Overall, increasing N application rates resulted in corresponding stepwise increase in seed yields in the two locations at Verona, whereas yields in the 60 and 120 kg N ha⁻¹ at Stoneville were not different from each other. Seed yields reached 3,383 and 3,166 kg ha⁻¹ in the 180 kg N treatment at Verona and at Stoneville, respectively. Oil yields were also increased with increasing N rates, however, oil yields at 60 and 120 kg N ha⁻¹ at Verona-C were not different from each other. Oil yields in the 180 kg N ha⁻¹ treatment reached 1,363 and 1,151 kg ha⁻¹ at Verona-SL and Stoneville, respectively. At Verona-SL location, higher N rates resulted in increased stearic acid compared to the lower N rates. However, the reverse effect was observed on the concentration of linolenic acid, which was lower at higher N rates. Also at that location, N application reduced the concentration of linoleic acid. At the Verona-C location, N application at 180 kg N ha⁻¹ reduced concentration of linolenic acid relative to the other fertility treatments. Overall, the increase in N application rates resulted in greater yield (kg FA ha⁻¹) of palmitic, palmitoleic, stearic, oleic, linoleic, linolenic, arachidic, eicosanoic, behenic, lignoceric and nervonic acids in all three locations, with N at 0 kg ha⁻¹ providing the lowest yields and N at 180 kg ha⁻¹ providing the highest yields. Winter canola production in the hot humid environment of southeastern United States can be successful and could provide seed and oil yields comparable to yields from major winter canola production areas.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 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".