Butter making from caprine creams: Effect of washing treatment on phospholipids and milk fat globule membrane proteins distribution
Bibliographic record
Abstract
A washing treatment was applied to caprine cream before churning in order to improve phospholipids and MFGM protein purification from buttermilk and butter serum. Cream obtained from a first separation was diluted with water and separated a second time using pilot plant equipment. Regular and washed creams were churned to produce buttermilk and butter, from which butter serum was extracted. The washing treatment allowed a significant decrease of the casein content. As a result, the phospholipids-to-protein ratios in washed buttermilk and butter serum were markedly increased by 2.1 and 1.7-folds respectively, which represents an advantage for the production of phospholipids concentrates. However, when compared with bovine cream, lower phospholipids-to-protein ratios were observed when the washing treatment was applied to caprine cream. A higher concentration of MFGM protein and a lower retention of phospholipids during washing treatment are responsible for the lower phospholipids-to-protein ratios in buttermilk and butter serum obtained from caprine cream. The phospholipids distribution in the butter making process was similar to the one obtained from bovine regular and washed cream. Phospholipids were preferentially concentrated in the butter serum rather than the buttermilk fraction. This simple approach permitted the production of caprine and bovine butter sera extracts containing up to 180 and 240 g phospholipids/kg sera, respectively, on a dry basis.
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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) | 0.001 | 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".