Freeze drying for microencapsulation of α‐linolenic acid rich oil: A functional ingredient from <i>Lepidium sativum</i> seeds
Bibliographic record
Abstract
Lipids rich in polyunsaturated fatty acids (PUFA) are of great importance to the food industry. However, due to unsaturation they are highly prone to rancidity, thereby presenting an enormous technological challenge. Emulsification and subsequent microencapsulation of oil forms a protective micro‐environment for these bioactives. Further, freeze drying of emulsified lipids is used to enhance shelf‐life of the dietary targets. In the current study, α‐linolenic acid (ALA) rich oil from Lepidium sativum seed was stabilized through microencapsulation by freeze drying. O/W emulsion was prepared using a combination of gum ghatti, gum arabic, and soy protein isolate. Thereafter induced coacervates were lyophilized by the batch method in a tray dryer. The encapsulation procedure was optimized by the central composite design, through variation of parameters such as the ratio between gum and soy protein isolate (SPI), wall and core and the speed of homogenization. The response was measured in terms of microencapsulation efficiency (MEE) with the maxima of 81.11% for the parameter values of Gum:SPI at 0.32, Wall:Core at 2 and homogenization speed of 10 000 rpm. The prepared emulsion was characterized through ζ‐potential, viscosity, and droplet size measurements while the encapsulated product was deliberated through Raman spectroscopy and aw evaluations. Practical applications: Dietary requirement of polyunsaturated fatty acids (PUFA) is seldom met by a vegetarian diet and therefore for the benefit of the vegetarian population, novel food products incorporating vegetarian PUFA need to be developed. However, rancidity is a major problem encountered while working on unsaturated molecules. Thus to gain maximum benefit from these functional lipids one needs to design stable bioavailable ingredients. With this in mind, the focus of the current study was formulation and process optimization to obtain encapsulated oil. Freeze drying process for microencapsulation leads to superior quality capsules due to the low temperature conditions. In this way L. sativum seed oil was explored for the first time to develop α‐linolenic acid rich bioactive ingredient. Microencapsulation of PUFA rich oil by freeze drying. In the current study α‐linolenic acid rich oil was extracted from Lepidium sativum and processed into a functional ingredient by freeze drying. Soxhlet extracted oil along with SPI, gum arabic, and gum ghatti was utilized for formation of coacervates. Encapsulated oil in the form of coacervates was then dehydrated to form microcapsules in a freeze dryer. The capsules were then analyzed for microencapsulation efficiency and capsule composition. The optimized capsules can be used to deliver α‐linolenic acid rich oil in novel targeted food products.
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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".