Concentration with Nanofiltration of Red Wine Cabernet Sauvignon Produced from Conventionally and Ecologically Grown Grapes: Effect on Phenolic Compounds and Antioxidant Activity
Bibliographic record
Abstract
The aim of this study was to investigate the influence of different operating conditions (four pressures: 2.5, 3.5, 4.5 and 5.5 MPa; two temperature regimes: with and without cooling) and wine type on phenolic compounds retention during the nanofiltration process of two Cabernet Sauvignon red wines (conventionally and ecologically produced). The nanofiltration process was conducted on Alfa Laval LabUnit M20 with plate module and six NF M20 membranes. In initial wines and obtained retentates, total polyphenol and flavonoid contents, monomeric anthocyanins content, antioxidant activity, individual phenolic compounds and CIELab colour parameters were determined. A loss of total phenolic compounds and decrease in antioxidant activity was observed in all retentates comparing to initial wine. However, retentate cooling and higher pressure increased their retention. Besides processing parameters, individual phenolic compound retention depended on several factors, such as the wine type, chemical properties of compounds and membrane type, and their combinations. Different chemical composition of initial conventional and ecological wine influenced the retention of individual compounds.
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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".