Genotype and growing location effects on phytosterols in canola oil
Bibliographic record
Abstract
Abstract There is little information available about phytosterols in canola (Brassica napa L.) oil and the effects of genotype and growing locations from Virginia and the mid‐Atlantic region of the United States, a potential area for the establishment of domestic production to provide edible oil. Our objectives were to characterize the phytosterols, phospholipids, unsaponifiable matter, and FA in oil from Virginia‐grown canola. Among 11 canola genotypes grown at two locations during 1995–1996 significant variations existed for oil content and FA profiles, but not for contents of phospholipids, unsaponifiable matter, total phytosterols, campesterol, stigmasterol, and β‐sitosterol, Total phytosterol content in the oil of Virginia‐grown canola varied from 0.7 to 0.9% with a mean of 0.8%. This concentration compared favorably with oil from Canadian canola, which typically contains 0.5 to 1.1% total phytosterols. The mean contents of brassicasterol, campesterol, stigmasterol, β‐sitosterol, Δ5‐avenasterol, and Δ7‐stigmatenol as percentages of total phytosterols in Virginia‐grown canola were: 9.7, 32.0, 0.6, 49.3, 4.99, and 3.5%, respectively. Growing location did not affect phytosterols in Virginia‐grown canola oil but had significant effects on contents of phospholipids, and saturated (myristic, stearic, and arachidic) and unsaturated (palmitoleic, linoleic, linolenic, eicosenoic, and erucic) FA.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".