Interactions between Ascophyllum nodosum Seaweeds Polyphenols and Native and Gelled Corn Starches
Bibliographic record
Abstract
seaweed flour (AF) and corn starch (CS) on the interactions between polyphenols and starch was studied in this paper. These methods comprised the blending of AF with native starch (NT) with previously gelled starch gel (GL) and promoting the gelling of corn starch in the presence of AF (CGL). Different AF-CS (g/g) ratios (from 1:0.5 to 1:25) were studied. The liquid phase was chemically characterized by polyphenols (TPC) and carbohydrates content. The antioxidant activity of the liquid phase after achieving the solid-liquid equilibrium was determined by DPPH, ABTS, and FRAP methods. The solid phase was characterized by FT-IR and SEM techniques. The Halsey model successfully fitted the equilibrium TPC in liquid and polyphenols adsorbed/retained by the solid phase of tested systems. NT samples showed lower polyphenols sorption than gelled samples. The differences found between samples obtained with GL and CGL methods suggested different interactions between polyphenols and starch. Specifically, physisorption is predominant in the case of the GL method, and molecular trapping of polyphenols in the starch gel structure is relevant for the CGL method. Results allowed us to determine the enhancement of the retention of polyphenols to achieve starchy foods with high bioactivity.
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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".