Fatty Acid Distribution and Oxidative Stability of <scp>DHA</scp>/<scp>EPA</scp>‐Enriched Structured Lipids From Virgin Coconut Oil
Bibliographic record
Abstract
ABSTRACT Novel structured lipids (SLs) were successfully produced from virgin coconut oil (VCO) and docosahexaenoic acid (DHA) and/or eicosapentaenoic acid (EPA). Stereospecific analysis results indicated that both DHA and EPA were predominantly esterified at the sn‐1 and sn‐3 positions. For DHA‐enriched VCO, caprylic acid (CyA, C8:0) was mainly esterified at the sn‐2 position, while capric acid (CaA, C10:0) and lauric acid (LaA, C12:0) were primarily located at the sn‐3 position. In EPA and DHA + EPA‐enriched VCO, C8:0 and C10:0 were almost randomly distributed across all three positions, except for C12:0, which was mostly found at the sn‐2 position. The oxidative stability results of the SLs showed higher levels of conjugated dienes (CD) and 2‐thiobarbituric acid reactive substances (TBARS) after 12 days of storage. Furthermore, the primary volatile compounds identified in the SLs using headspace gas chromatography–mass spectrometry (HS GC–MS) included acetaldehyde, propanal, and 2‐propenal (acrolein), which were absent in the unmodified oils. These results indicate that the modified oils exhibited a higher susceptibility to oxidation compared to their unmodified counterparts. Oils high in polyunsaturated fatty acids (PUFAs) require protection from oxidation to mitigate the detrimental effects of oxidation products and preserve their nutritional and health benefits.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".