Lipid Components of North American Wild Rice (<i>Zizania palustris</i>)
Bibliographic record
Abstract
Abstract The content and composition of fatty acids, sterols, tocopherols, and γ‐oryzanol in wild rice (Zizania palustris) grown in North America were compared with those in regular brown rice (Oryza sativa L.). The lipid content of wild rice ranged from 0.7 to 1.1%, compared with 2.7% in regular brown rice. The lipids of wild rice comprised mainly linoleic (35–37%) and linolenic (20–31%) acids. Other fatty acids included palmitic (14.1–18.4%), stearic (1.1–1.3%), and oleic (12.8–16.2%). Wild rice lipids contained very large amounts of sterols, ranging from 70 g/kg for a Saskatchewan sample to 145 g/kg for Minnesota Naturally Grown Lake and River Rice. The main sterols found in an unsaponified fraction were: campesterol (14–52%), β‐sitosterol (19–33%), Δ5‐avenasterol (5–12%), and cycloartenol (5–12%). Some of sterols, γ‐oryzanols, were present as the phenolic acid esters; the amount ranged from 459 to 730 mg/kg in wild rice lipids. The largest amounts of tocopherols and tocotrienols, 3682 and 9378 mg/kg, were observed in North Western Ontario wild rice samples, whereas the lowest were 251 mg/kg in an Athabasca Alberta sample and 224 mg/kg in regular long‐grain brown rice. The α isomer was the most abundant among tocopherols and tocotrienols. The results of this study showed that wild rice lipids contain large amounts of nutraceuticals with proven positive health effects.
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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 | 0.000 | 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) | 0.001 | 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".