Tocol Composition and Supercritical Carbon Dioxide Extraction of Lipids from Barley Pearling Flour
Bibliographic record
Abstract
Samples of whole grain and 35% pearling flour of 20 different barley varieties grown in Alberta were analyzed for their lipid contents. Total lipid contents of whole grains were within 1.9% to 3.0% (w/w), whereas those of the 35% pearling flour were 4.3% to 7.9%. Lipids of 35% pearling flour fraction of Tercel barley were extracted using supercritical carbon dioxide (SC-CO2 ) at different pressures (24, 45, and 58 MPa) and temperatures (40 and 60 °C) for 3 h. Lipid recoveries of 73% to 97% were achieved using SC-CO2 extraction under different operational conditions. Tocol contents and compositions of whole grain, 35% pearling flour, and SC-CO2 extracts were analyzed using HPLC. Tocol content of the whole grain was 53.8 to 124.9 μg/g and that of the pearling flour was 195 to 363 μg/g of flour. The hulless barley varieties were higher in tocols, with waxy, double waxy and Tercel varieties having the highest levels (P < 0.05). The ratios of total tocotrienols to total tocopherols varied within 1.6 to 3.9 range. Tocol concentrations of SC-CO2 extract fractions varied from 1171 to 4391 μg/g extract depending on the operational conditions. Barley oil is a good natural source of different tocol isomers rich in tocotrienols.
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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) | 0.000 | 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".