LIPID CLASS COMPOSITIONS, TOCOPHEROLS AND STEROLS OF TREE NUT OILS EXTRACTED WITH DIFFERENT SOLVENTS
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Bibliographic record
Abstract
ABSTRACT The chemical compositions of tree nut oils were examined. The oils of almonds, Brazil nuts, hazelnuts, pecans, pine nuts, pistachios and walnuts were extracted using hexane and chloroform/methanol. The chloroform/methanol system afforded a higher oil yield for each tree nut type examined (pine nuts had the highest oil content while almonds had the lowest). The lipid class compositions of the tree nut oils were analyzed using the thin‐layer chromatography‐flame ionization detector and showed that triacylglycerols were the predominant lipid class present. Smaller amounts of sterols, sterol esters, phospholipids and sphingolipids were also present. The fatty acid compositions of the tree nut oils were analyzed using gas chromatography, showing that oleic acid was the predominant fatty acid in all samples except pine nut and walnut oils, which contained high amounts of linoleic acid. The sterol and stanol content and compositions were analyzed using gas chromatography; β‐sitosterol was the predominant sterol present in all samples, with lower amounts of campesterol, stigmasterol, Δ5‐avenasterol, 22‐nordehydrocholesterol, 24‐methylenecholesterol, cholesterol, cholestanol and β‐sitostanol also present. The tocopherol compositions were analyzed using high‐performance liquid chromatography, showing that α‐ and γ‐tocopherols were the predominant tocopherol homologs present; however, δ‐ and β‐tocopherols were also detected in some samples. PRACTICAL APPLICATIONS Tree nut oils contain health‐promoting unsaturated fatty acids and minor components that may render beneficial effects. The lipid class compositions of the oils are reported as these affect the stability of the tested oils. Results may have significance in terms of practical applications for food and use in nutraceutical and/or cosmoceuticals products.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it