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Record W2078048459 · doi:10.1017/s002202990800349x

Butter making from caprine creams: Effect of washing treatment on phospholipids and milk fat globule membrane proteins distribution

2008· article· en· W2078048459 on OpenAlexaff
Sophie Lamothe, Gilles Robitaille, Daniel St‐Gelais, Michel Britten

Bibliographic record

VenueJournal of Dairy Research · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsGlobules of fatFood scienceChemistryDistribution (mathematics)ChromatographyMilk fatMathematics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.210

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.080
GPT teacher head0.326
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations25
Published2008
Admission routes1
Has abstractyes

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