Effect of Ultrafiltration of Milk Prior to Fermentation on Mass Balance and Process Efficiency in Greek-Style Yogurt Manufacture
Bibliographic record
Abstract
Ultrafiltration (UF) can be used to concentrate yogurt to produce Greek-style yogurt (GSY) (UF-YOG), but this generates acid whey permeate, which is an environmental issue. However, when UF is applied before fermentation (UF-MILK), a nonacidified whey permeate is generated. For this study, two model GSYs (UF-YOG and UF-MILK) were produced to compare the composition, UF performance, and energy consumption of the two processes. For UF-MILK, skim milk was ultrafiltered with a 30 kDa spiral-wound UF membrane to achieve a 3× volume reduction factor (VRF). The retentate was fermented to a pH of 4.5. The UF-YOG process was the same except that regular yogurt was ultrafiltered. Both GSYs had similar protein (~10%) and solid content (~17%). As expected, lactic acid/lactate was not detected in UF-MILK permeate, while 7.3 g/kg was recovered from the UF-YOG permeate. Permeation flux values (11.6 to 13.3 L m−2 h−1) and total flux decline (47% to 50%) were constant during UF-MILK, whereas drastic decreases in these two membrane performance indicators (average flux: 38.5 to 10.9 L m−2 h−1; total flux decline: 2% to 38%) were calculated for UF-YOG. Moreover, for UF-YOG, UF membrane performance never recovered, even when drastic and repeated cleaning steps were applied. Energy consumption was 1.6 kWh/kg GSY and remained constant for UF-MILK, whereas it increased from 0.6 to 1.5 kWh/kg GSY for UF-YOG. Our results show that, although the composition of GSYs was similar for both processes, the UF step of yogurt concentration affected process efficiency due to drastic and permanent membrane fouling.
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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".