Storage Stability of DHA in Enriched Liquid Eggs
Bibliographic record
Abstract
The oxidative stability of liquid eggs enriched with very long‐chain n‐3 fatty acids and liquid regular eggs stored under refrigerated temperature, is investigated. Oxidized lipids can alter both nutritional and sensorial properties of foods. The extent of lipid oxidation is evaluated by quantification of total lipids, docosahexaenoic acid (DHA), and peroxide value (PV), but also by assessment of total tocopherols and γ‐tocopherol losses. Additionally, the development of fishy off‐flavor is evaluated. Results highlight significant differences between omega and regular liquid eggs stability. Although, the oxidative changes are observed in both types of liquid eggs, more susceptible to oxidation are omega liquid eggs. Practical Applications: Food enrichment with essential nutrients contributes to human health by providing the proper intake of essential nutrients. The results of this study suggest that fortification of eggs with highly unsaturated fatty acids should be in conjunction with the addition of natural antioxidants to retard undergoing oxidative changes. Liquid omega eggs are, unfortunately, more susceptible to oxidation than regular liquid eggs under simulated long time storage. The high concentration of unsaturated fatty acids improved their nutrition value but at the same time these products are less stable and unfavorable changes are more prominent. Therefore, the very long chain fatty acids in liquid omega eggs should be protected from undergoing deterioration. Although, the liquid omega eggs samples are stored at refrigerated temperature, significant changes are observed. The storage period led to a modification of the odor of liquid omega eggs, the increase in the fishy odor intensity is noticeable. And for the consumer, off‐flavor is generally the first factor which will make the product unacceptable.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".