Triacylglycerols and Polar Lipids in Cow and Goat Milk are Differentially Affected by Various Lipid Supplemented Diets
Bibliographic record
Abstract
Abstract This study characterizes milk triacylglycerol (TAG) and polar lipid (PL) fractions from cows and goats fed various lipid supplements modulating milk fat content. Twelve Holstein cows and 12 Alpine goats, at 86 ± 24.9 and 61 ± 1.8 days in milk, respectively, are allocated to one of 4 groups to receive diets supplemented with either corn oil [5% dry matter intake (DMI)] plus wheat starch (COS), marine algae powder (MAP; 1.5% DMI) or hydrogenated palm oil (HPO; 3% DMI), or a no‐added‐lipid control diet (CTL), according to a 4 × 4 Latin square design with 28 d experimental periods. Milk TAG and PL contents are determined by liquid chromatography‐mass spectrometry (LC‐MS). Multivariate analysis and ANOVA demonstrate major between‐species differences in diet effects. In cows, COS specifically increases TAG 54:3 and 54:4 associated with milk fat depression (MFD), and increases the sum of phosphatidylcholines (PC) and phosphatidylinositols (PI). In addition to causing a MFD, MAP diet increases long‐chain polyunsaturated TAG in both species, with higher magnitude in cows than in goats, and decreases the sum of PI in goats. HPO increases TAG 52:1 and the sum of PI in cows, but not in goats. Practical applications: Feed strategies can quickly and efficiently modulate the ruminant milk fat production and composition to improve nutritional quality for consumers. Certain starch‐rich diets supplemented with polyunsaturated fatty acids (PUFA)‐rich vegetable oils and diets supplemented with marine products (long‐chain PUFA) reduce milk fat secretion and modify the milk fatty acid (FA) profile in cows, but not—or less so—in goats. Advanced analysis of both the TAG and PL fractions of milk fat is required to unravel these differences in lipid metabolism between cows and goats fed various lipid‐supplemented diets. This study brings new insight on using nutritional strategies to control milk lipid composition according to ruminant species.
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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 | 0.000 |
| 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".