Enrichment of flaxseed (Linum usitatissimum) oil with carotenoids of sea buckthorn pomace via ultrasound-assisted extraction technique
Bibliographic record
Abstract
Currently, flaxseed oil is used as an important functional food constituent owing to its large content of omega-3 fatty acids. However, flaxseed oil does not contain carotenoids that could enhance the oxidative stability of the oil. In this study, carotenoids extracted from sea buckthorn pomace were used to enrich cold-pressed flaxseed oil via an ultrasound-assisted extraction technique (UAE). The process parameters were optimized through Box-Behnken design to maximize the carotenoid content in the flaxseed oil. The results obtained by statistical analysis indicated that the yield of 14.02 mg/L of carotenoid content was found in the enriched flaxseed oil at 75.6 min, feed to oil ratio of 19.9 (wt. basis), and amplitude 80.81%. Further, UAE at optimum process parameters was compared with the conventional extraction (CE) method, and it was found that UAE had ~ 49 wt% of higher carotenoid content relative to CE. The physicochemical properties of the enriched flaxseed oil were determined to evaluate the effects of carotenoid enrichment in the flaxseed oil. Based on the outcomes of the present investigation, enriched flaxseed oil could be the potential source for the pharmaceuticals and nutraceuticals industry.
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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 | 0.000 | 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) | 0.001 | 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".