Physico-Chemical Properties of Casein Micelles Concentrated by Membrane Filtration and Their Behavior in Acid Gelation
Bibliographic record
Abstract
Membrane filtration is a widespread unit operation in dairy technology. In this study we investigated how ultrafiltration (UF) and diafiltration (DF) may affect the physico-chemical properties of the casein micelles and their functionality related to acid gelation. By concentrating by UF, the volume fraction of protein increased while maintaining the serum composition similar to that of the original milk. By using UF in combination with DF, the mineral equilibrium was modified. UF and DF retentates showed different behavior during heating, with the formation of different populations of non sedimentable complexes. Various combinations of heating temperature and time were investigated. Calcium solubilization as a function of pH was also affected, as demonstrated by measurements of buffering capacity and soluble calcium. The area of the maximum peak in buffering capacity observed at pH ~5.1, which is related to the presence of colloidal calcium phosphate, was significantly affected by casein volume fraction, but did not increase proportionally to casein concentration, even in the UF milk. This suggested the release of calcium phosphate even during concentration by UF. It was hypothesized that the changes in calcium equilibrium during UF and DF, as well as the formation of different types of soluble aggregates, during membrane filtration as well as after heating, may have profound consequences on the acid gelation behaviour of the caseins. Hence, in a second part of the thesis, UF and DF retentates were subjected to heating at 80 °C for 15 min, and then gelation was induced using glucono-delta-lactone. The gelation pH, measured by rheology and diffusing wave spectroscopy, significantly increased with the extent of concentration (p<0.05, as measured by ANOVA). The increase was not only due to a reduction in the interparticle distance, but most importantly, because of the changes in the soluble fraction, and in particular the presence of the non-sedimentable aggregates. DF milk gelled at a significantly higher pH than UF milk. Furthermore, at a 2× concentration, the gel firmness at pH 4.6 was higher for DF milk than for UF milk. This was not the case for 4× concentrated milk, possibly because of limited rearrangements of the casein micelles and heat induced complexes at this high concentration. This work clearly demonstrated for the first time that UF and DF processes cause substantial changes in the composition of the soluble fraction, and modify the acid induced aggregation behaviour of concentrated milk.
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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 | 0.001 |
| 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".