Antioxidant potential and physicochemical properties of protein hydrolysates from body parts of North Atlantic sea cucumber (Cucumaria frondosa)
Bibliographic record
Abstract
Abstract Protein hydrolysates were prepared from North Atlantic sea cucumber (Cucumaria frondosa) body wall (BW), and processing by-product flower (FL) and internal organs (IN). Sea cucumber proteins from these three tissues were hydrolysed with selected endopeptidases and exopeptidases. The enzymes used were Alcalase (A), and Corolase (C) as endopeptidases and Flavourzyme (F) with both endo- and exopeptidase functions. These were employed individually or in combination under controlled conditions. The hydrolysates so prepared were subsequently analysed for their antioxidant potential and functionalities in food systems for the first time. Hydrolysates treated with the combination of A and F exhibited the highest radical scavenging activity against DPPH and ABTS radicals. The highest metal chelation activity was observed for samples hydrolysed with the combination of enzymes (C + F and A + F). All treatments inhibited beta-carotene bleaching in an oil-in-water emulsion and TBARS production in a meat model system. In addition, sea cucumber protein hydrolysates were more than 75% soluble over a pH range of 2–12. Hydrolysed proteins were also effective in enhancing water holding capacity in a meat model system compared to their untreated counterparts. The amino acids of sea cucumber protein hydrolysates had desirable profiles with glutamic acid as the predominant component in samples analysed. These findings demonstrate the desirable functionalities of hydrolysates from North Atlantic sea cucumber and their potential for use as functional food ingredients. Graphical abstract
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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) | 0.001 | 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".