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Record W4386578894 · doi:10.1016/j.anopes.2023.100049

Milk volatilome as affected by somatic cell count in Holstein cows

2023· article· en· W4386578894 on OpenAlexafffund
P.Y. Chouinard, C. Garon, Yolaine Lebeuf, Simon Dufour, R. Gervais

Bibliographic record

VenueAnimal - Open Space · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsUniversité de MontréalUniversité Laval
FundersFonds de recherche du Québec – Nature et technologies
KeywordsUdderChemistrySomatic cell countFood scienceRaw milkAnimal scienceHerdLactationIce calvingBiologyMastitisPregnancy

Abstract

fetched live from OpenAlex

The aim of the current trial was to study the impact of a high somatic cell count (SCC) on milk volatilome of fresh raw milk, and its evolution during storage of processed fluid milk. Six Holstein cows were selected from our research dairy herd based on test-day SCC records. Three cows were used to produce low-SCC milk (20 × 103 cells/mL). The three other cows had one-quarter infected by Staphylococcus aureus. Infected and healthy udder halves were milked separately, and high-SCC milk was standardized to 400 × 103 cells/mL by mixing these two milks. The profile of milk volatile organic compounds (VOCs) was determined on raw milk and during the storage of processed milk. The processing included a standardization to 3.25% fat, followed by homogenization, and thermization (65 °C/30 min). This procedure was repeated four times over a period of 7 days. A total of 40 VOC were identified using the solid-phase microextraction technique followed by gas chromatography separation, mass spectrometry analysis, and database search. These VOC were grouped into seven different families, including alcohols (n = 4), free fatty acids (n = 5), sulfur compounds (n = 3), esters (n = 7), ketones (n = 7), aldehydes (n = 12), and aromatic hydrocarbons (n = 2). In raw milk, high SCC was associated with a tendency for lower concentrations of ethyl-hexanoate (P = 0.07), acetone (P = 0.06), and benzaldehyde (P = 0.07) and lower concentrations of trans-2 hexenal (P = 0.04). On the contrary, high SCC was associated with a tendency for greater concentrations of acetic acid (P = 0.09) and hexanoic acid (P = 0.07) and greater concentrations of 2-nonanone (P = 0.02) and pentanal (P = 0.01). Concentrations of most VOC increased during the storage of processed milk. Lower concentrations of butanoic acid (P = 0.09; tendency) and ethyl hexanoate (P = 0.04), and greater concentration of 1-ocen-3-ol (P < 0.01) were observed in high-SCC milk at all times of storage evaluated. Increases in concentrations over time were less pronounced for ethanol (P < 0.01), ethyl butanoate (P = 0.05), and propanal (P = 0.10) in high SCC as compared with low SCC milk. In conclusion, an increase in SCC has a limited effect on milk volatilome, when a SCC standard of 400 × 103 cells/mL for bulk milk is respected.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.816
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.027
GPT teacher head0.270
Teacher spread0.243 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2023
Admission routes2
Has abstractyes

Explore more

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