Antioxidant Properties of Flaxseed Protein Hydrolysates: Influence of Hydrolytic Enzyme Concentration and Peptide Size
Bibliographic record
Abstract
Abstract Flaxseed is an emerging source of protein raw materials for bioactive protein hydrolysate production; however, there is insufficient information on the structural properties of its antioxidative peptides. The aim of this work was to determine the peptide composition and relationships to antioxidant properties of flaxseed protein hydrolysates (FPH) obtained using two protease (thermoase) concentrations (2.5 and 3.0%). The FPH were passed through ultrafiltration membranes to yield fractions with <1, 1–3, 3–5, and 5–10 kDa peptide sizes, which were also tested for antioxidant properties. Mass spectrometry data yielded several peptide sequences located within the flaxseed conlinin, but a lesser number was found in the 3.0% thermoase‐FPH. 2,2‐Diphenyl‐1‐picrylhydrazyl radical scavenging was lowest (54%) for the 3.0% thermoase‐FPH while membrane separation enhanced the values up to 65% for the <1 kDa peptides. Metal chelation and iron‐reducing ability were also significantly ( P < 0.05) enhanced after membrane fractionation. In contrast, the hydroxyl radical scavenging ability was unchanged (2.5% thermoase‐FPH) or significantly ( P < 0.05) diminished (3.0% thermoase‐FPH) after membrane fractionation, except for the 5–10 kDa peptides that had notably ( P < 0.05) higher values. We conclude that the <1 and 1–3 kDa peptides may be useful agents to suppress oxidative stress within living tissues while the 3–5 and 5–10 kDa could be suitable preservatives to enhance food shelf life.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".