Microencapsulation of Flaxseed Oil by Lentil Protein Isolate-κ-Carrageenan and -ι-Carrageenan Based Wall Materials through Spray and Freeze Drying
Bibliographic record
Abstract
Lentil protein isolate (LPI)-κ-carrageenan (κ-C) and -ι-carrageenan (ι-C) based microcapsules were prepared through spray-drying and freeze-drying to encapsulate flaxseed oil in order to reach final oil levels of 20% and 30%. Characteristics of the corresponding emulsions and their dried microcapsules were determined. For emulsion properties, all LPI-κ-C and LPI-ι-C emulsions remained 100% stable after 48 h, while the LPI emulsions destabilized quickly (p < 0.05) after homogenization mainly due to low emulsion viscosity. For spray-dried microcapsules, the highest yield was attributed to LPI-ι-C with 20% oil, followed by LPI-κ-C 20% and LPI-ι-C 30% (p < 0.05). Flaxseed oil was oxidized more significantly among the spray-dried capsules compared to untreated oil (p < 0.05) due to the effect of heat. Flaxseed oil was more stable in all the freeze-dried capsules and showed significantly lower oil oxidation than the untreated oil after 8 weeks of storage (p < 0.05). As for in vitro oil release profile, a higher amount of oil was released for LPI-κ-C powders under simulated gastric fluid (SGF), while more oil was released for LPI-ι-C powders under simulated gastric fluid and simulated intestinal fluid (SGF + SIF) regardless of drying method and oil content. This study enhanced the emulsion stability by applying carrageenan to LPI and showed the potential to make plant-based microcapsules to deliver omega-3 oils.
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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) | 0.000 | 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".