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Record W4412535696 · doi:10.3168/jds.2025-26596

Effect of dietary palmitic acid supplementation and milking frequency: 2. Butter manufacture and properties

2025· article· en· W4412535696 on OpenAlexafffund
Maurice Landry, M. Gareau-Vignola, M Guyard, Yolaine Lebeuf, Julien Chamberland, G. J. Brisson, P.Y. Chouinard, R. Gervais

Bibliographic record

VenueJournal of Dairy Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Chemistry and Fat Analysis
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaFonds de recherche du Québec – Nature et technologiesMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
KeywordsMilkingPalmitic acidFood scienceMilk fatChemistryAnimal scienceBiologyBiochemistryFatty acid

Abstract

fetched live from OpenAlex

Dietary palmitic acid (PA) supplementation promotes fat yield, whereas increased milking frequency (MF) enhances milk yield. Such practices can be useful at the farm level, but their effects on milk processing remain to be determined. The objective of this study was to evaluate the effects of dietary PA supplementation and increased MF from 2 times to 3 times daily on butter manufacture and properties. In a duplicated 4 × 4 Latin square design, with a 2 × 2 factorial arrangement of treatments, 8 Holstein cows received a diet with or without PA (2% or 0%, on a DM basis) and were milked 2 times or 3 times daily. For each period, after 18 d of treatment adaptation, milk was collected from each cow for 2 d, and pooled by treatment before butter manufacture. Milk free fatty acids (FA) concentration and casein micelle size were similar between treatments, as well as cream fat globule diameter and butter yield. There was a significant interaction between PA and MF on churning time. With the nonsupplemented diets, 3 times daily milking increased churning time, and with 2 times daily milking, PA supplementation also increased churning time. Butter FA composition was mostly affected by PA, whereas MF had a limited effect. Total 16 C FA concentration in butter was increased with dietary PA at the expense of short-chain FA (6-14 C) and, to a lesser extent, long-chain FA (≥18 C). Dietary PA increased butter hardness at 20°C, whereas this effect was limited to a tendency when measured at 4°C. Resistance to spreadability increased with PA at both 4°C and 20°C. Overall, the effects of PA on butter texture were less pronounced at 4°C than at 20°C. Milking frequency had no effect on butter texture. Butter melting point was greater with PA and was positively correlated with the concentration in 16:0 and the spreadability index (cis-9 18:1/16:0). The solid fat content of butter was similar between PA and non-PA treatments at 5, 8, and 20°C. However, from 30°C, the solid fat content was higher with the PA diet. The spreadability index was correlated with butter hardness, and to a greater extent, with butter spreadability. This work underscores how dairy farm management influences the technological properties of milk, with potential implications for butter manufacturing and quality.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.234
Teacher spread0.224 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2025
Admission routes2
Has abstractyes

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