Bulgarian Mavrud Wine Under Nanofiltration and ReverseOsmosis: Evaluating the Composition After the Process
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Bibliographic record
Abstract
This work presents new results and conclusions on nanomembrane filtration and reverse osmosis of Mavrud red wine, produced in Bulgaria. The experiments were focused on lowering the alcohol content while preserving the valuable substances in the wine. Commercially available nanomembranes were used (Alfa Laval NF99HF, Alfa Laval RO99, NADIR NP030P). Two modes of nanofiltration (concentration mode and diafiltration mode, including constant volume diafiltration and two-step diafiltration) and reverse osmosis were employed for this study. The nanofiltration membranes (Alfa Laval NF99HF, NADIR NP030P) used for wine dealcoholization showed high separation effectiveness. Several wine components were recognized as indicators to be monitored during the process: carboxylic acids (citric, tartaric, malic, succinic, acetic); monosaccharides (glucose, fructose); alcohol (ethanol). The monitoring of the named compounds was performed with an HPLC-RID system on an H-charged ion exclusion analytical column. Based on the analysis of the collected samples, it could be stated that the alcohol content in the wine was lowered from 11.8% to 4.3 vol% of ethanol, when the sequential diafiltration mode of operation is used. Content change depends on the type of molecule; for example, in most cases the citric acid is strongly retained (Rej > 90%) by the membrane, whereas the acetic acid could permeate significantly (Rej < 20%). The obtained results present valuable information about the changes in the composition of the Mavrud wine which will aid in the preservation of the chemical composition and valuable substances in the event of future full or partial dealcoholization of this wine variety.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it