A NEW NATURAL FOOD DYE: MICROENCAPSULATED CORNELIAN CHERRY BIOACTIVE COMPOUNDS
Bibliographic record
Abstract
Cornus mas (CM) is one of the four edible fruits of the Cornus genus, a rich source of biologically active compounds (BACs) such as vitamins (like vitamin C), carotenoids, iridoids, and phenolics (phenolic acids, anthocyanins, and other flavonoids). This study aimed to analyse the improvement of the stability of CM anthocyanins by microencapsulation, in order to propose a new natural food dye. Microencapsulation using a mixture of whey protein isolate (WPI) and chitosan (CH) as wall materials has been applied to protect anthocyanins against external factors (e.g., light, temperature, storage, etc.). Two experimental variants of microencapsulated powders, WPI:CH = 1:1 (CH1) and WPI:CH = 1:2 (CH2), were realised by varying the wall materials ratio. The cornelian cherry fruit concentrated extract was evaluated for its phytochemical, colourimetric, and antioxidant capacities. Due to the excellent anthocyanin encapsulation effectiveness (74.29 – 88.71%), the wall materials utilised for both powders can be considered effective choices to safeguard the anthocyanins. All tests performed on the microencapsulated powders demonstrated that both suggested experimental forms can serve as a healthy substitute for artificial food additives. The incorporation of cornelian cherry fruit extract and microencapsulated powders into a food matrix (jelly candies) allowed examination of their effectiveness. The colour analysis rigorously characterised all the colour parameters related to red nuances (due to anthocyanins content, such as cyanidin-3-glucoside) and yellow nuances (associated with carotenoids content).
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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".