Evaluation of Freeze Drying and Electrospinning Techniques for Saffron Encapsulation and Storage Stability of Encapsulated Bioactives
Bibliographic record
Abstract
Saffron extract was encapsulated into a gelatin matrix by means of electrospinning and freeze drying techniques and the degradation kinetics of bioactive compounds were evaluated during their storage at 4, 24, and 35 °C as compared to non-encapsulated control. The encapsulation efficiency, thermal properties, storage stability, morphology, and diameter distribution of the encapsulated saffron extract were evaluated as output parameters. In general, both encapsulation techniques demonstrated superior retention of bioactive compounds compared to samples without encapsulation during the entire storage period. Electrospinning and freeze drying techniques were able to retain at least 96.2 and 93.7% of crocin, respectively, after 42 days of storage at 35 °C with the 15% saffron extract. The half-life (t1/2) time parameter for the control sample (with 15% saffron extract without encapsulation) was 22 days at 4 °C temperature, while that encapsulated by electrospinning was 138 days and that obtained for freeze drying was 77 days, The half-lives were longer at lower temperatures. The encapsulation efficiency of crocin, picrocrocin, and safranal associated with the electro-spun gelatin fibers were 76.3, 86.0, and 74.2%, respectively, and in comparison, the freeze drying encapsulation efficiencies were relatively lower, at 69.0, 74.7, and 65.8%, respectively. Electro-spun gelatin fibers also had higher melting and denaturation temperatures of 78.3 °C and 108.1 °C, respectively, as compared to 65.4 °C and 93.2 °C, respectively, for freeze-dried samples. Thus, from all respects, it was concluded that electrospinning was a better and more effective technique than freeze drying in terms of preserving saffron bioactive compounds.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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".