0704 Thermal stability of microfiltered and ultrafiltered retentates
Bibliographic record
Abstract
Membrane filtration technologies are widespread unit operations in the dairy industry and are often used to obtain ingredients of tailored processing functionalities. The objective of this work was to better understand the effect of partial removal of whey proteins by microfiltration (MF) on the heat stability of the retentates. Control retentates were obtained using ultrafiltration (UF). Pasteurized milk was microfiltered (80 kDa polysulfone membrane) or ultrafiltered (30 kDa cellulose membrane) in a plate and frame membrane system to reach two and four times concentration (based on volume reduction). Concentrates showed no differences in pH, casein micelle size, or minerals in the serum phase, before heating, as diafiltration was not used in this study. The reduced amount of whey protein in the MF retentates caused a significant increase in the heat stability of the retentates, compared with UF retentates. This difference was not due to ionic composition differences or to pH. Heat coagulation time decreased with protein concentration but significantly increased in MF retentates, containing less whey proteins than the corresponding UF controls. In 2x concentrates, retentates prepared with MF, containing 20% less whey proteins than UF control, showed an increase in the heat coagulation time of about 11 min. 4xMF retentates contained 17 ± 3 mg/mL of whey proteins, about 40% less whey proteins than the 4xUF control retentates. A 4x concentrate prepared by MF showed heat stability statistically similar to that of a 2xUF concentrates, with a heat coagulation time of about 38 min. The turbidity parameter 1/l*, measured by diffusing wave spectroscopy, increased after heating, with the UF retentates showing a higher value than the MF retentates, at the same protein concentration. In addition, 4xMF concentrates showed a 1/l* value comparable to that of 2xUF concentrates. In conclusion, this work demonstrated that partial removal of whey proteins by MF could be used as a means to increase heat stability of milk concentrates.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 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 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".