Alcohol-free wine based jelly candies enriched with grape pomace extracts with antioxidant and antidiabetic properties: Implications for sustainable development and health benefits
Bibliographic record
Abstract
Pinot noir and Chardonnay wines were dealcoholised, reducing the ethanol to final content below 0.5 mL/100 mL and concentrating their non-volatile extract. Grape pomace (wine industry by-product) was incorporated as a source of bioactive compounds. The influence of temperature and ultrasonic treatment on polyphenols extraction efficiency was assessed. The best extraction yield was found when 60 min of ultrasonic treatment followed by 60 min of shaking at 60 °C were applied. Pinot noir grape pomace extracts contained higher levels of phenolic acids, catechins, tannins, and anthocyanins, whereas Chardonnay lacked anthocyanins and resveratrol. These extracts were incorporated into the production of functional jelly candies formulated with dealcoholised wine, dietary fibers, and natural sweeteners. Pinot noir jellies consistently showed greater phenolic content, antioxidant activity, and stronger α-glucosidase inhibition compared to Chardonnay , with values nearly twice as effective as acarbose when expressed as GAE. Pinot noir extracts provided an intense, wine-like character of jelly candies and high functional value, but their excessive astringency requires optimization. Chardonnay extracts offered a milder and more consumer friendly sensory profile. The presented jelly candies are an innovative example of functional confectionery with nutritional and commercial relevance, aligning with current consumer demand for health-promoting, environmentally responsible and sustainable food products. • Dealcoholisation reduces volatile acidity and concentrates non-volatile extract • Temperature and ultrasound improve the recovery of polyphenols from grape pomace • Phenolic rich grape pomace are a natural alternative to antidiabetic pharmaceuticals • Wine industry by-products can be reused in the creation of functional confectionery
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".