Characterization of changes in composition and physicochemical properties of casein micelles from raw milk to buttermilk
Bibliographic record
Abstract
It is well-documented that buttermilk has poor coagulation properties due to changes that occur to the casein micelles during the butter-making process. These modifications are generally attributed to the pasteurization of the cream upon which interactions between the proteins are promoted. It was hypothesized that churning is also a critical step for the changes that occur in composition of the casein micelles. The objective of this work was to learn more about the interactions that occur between casein micelles and MFGM components during the butter making process. Raw cream was processed using a rotary churn at 18°C for approximately 30 minutes, and buttermilk was collected for analysis. Raw milk was skimmed at 10°C by centrifuging at 3000 x g for 20 minutes. Cream, skim milk and buttermilk were centrifuged at 60,000 x g for 40 minutes twice using imidazole buffer at pH 6.8 in order to isolate the micellar content in the pellet. Variation in physical properties of the casein micelles was determined using a Malvern Zetasizer. Protein profiles of UP cream, skim milk, and buttermilk were analyzed using one and two-dimensional gel electrophoresis technique. Experiments were performed using three different batches of UP cream, skim milk and buttermilk. Statistical analyses showed that processing the buttermilk significantly increased the surface charge (P0.05). Our results also indicate that churning of cream promoted interactions between casein micelles and MFGM proteins as shown by the more complex 2D-gel electrophoresis pattern obtained for casein micelles sedimented from buttermilk. This work is significant in its focus of better understanding the functionality changes of valuable milk components during the churning of cream.
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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 | 0.000 | 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".