Influence of pH and ionic strength on the color parameters and antioxidant properties of an ethanolic red grape marc extract
Bibliographic record
Abstract
The aim of present study was to investigate the influences of pH and several salts on the antioxidant activity and color of an ethanolic grape marc extract. Furthermore, the phenolic content of the extract was analyzed using HPLC and spectrophotometric methods while the total antioxidant activity was assessed by the reaction with ABTS radical. Gallic acid, procyanidins B1, B2, polydatin, catechin, epicatechin, hyperoside, ferulic, chlorogenic, and salicylic acids were among the main identified polyphenols. Different pH values had slight influence on the antioxidant activity, the highest value being determined for pH 3.7. The redness, chroma, and hue were significantly enhanced at pH 3.7 and 2.6. The chromaticity decreased at pH = 5.5 and pH = 7.4, so the extract should be used with care in products with such media. The presence of salts did not noticeably affect the antioxidant activity, except the higher concentrations of CaCl2, which decreased the antioxidant activity but enhanced the color intensity. Practical application The data presented in this paper could be used for the development of a new food dye with antioxidant properties of natural origin. The optimal medium conditions (i.e., pH and ionic strength) for the use of an ethanolic red grape marc extract have been identified. The information could be used in product development and product formulation, especially when functional foodstuffs are envisaged. Consequently, this paper would be of significant interest for food chemists, food technologists, food manufacturers, and especially manufacturers of food dyes and all those using natural substances in their production process.
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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 | 0.000 |
| 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 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".