0834 Do buffaloes have better milk fat profile than cows? Where does the evidence stand in 2016?
Bibliographic record
Abstract
The objective of the present study was to document a comprehensive comparison between the milk fat profiles of buffalo and cattle. Data on milk fat profiles of buffalo were retrieved from nine published studies on different breeds of buffalo (Nili-Ravi, Kundi, Murrah, Egyptian, Italian, Romanian), and values/proportions of individual/groups of fatty acids (FA) were averaged across breeds. Data on milk fat composition of cow milk was obtained from a recent study on Canadian Holstein cows using large gas chromatography data. Milk fat profiles (means of 29 variables each) of the buffalo and the cow were compared using Student's t-test. Overall, Holstein cows had approximately 3–4 times higher daily milk yield than buffalo. Buffalo milk had greater total solids (17.76% vs. 13.94%) and a higher fat percentage (7.02% vs. 3.86%) than cow milk, indicating more value for buffalo milk. Buffalo milk fat had slightly higher proportions of total saturated, total trans, and total mono-unsaturated FA but similar proportions of total polyunsaturated FA than that of cow; although differences in these groups of FA were statistically nonsignificant. Buffalo milk fat had higher proportions of human-health-related beneficial fatty acids (comparing one fatty acid at a time) such as oleic acid, CLA, cis-9 trans-11, and two omega-3 FA (C18:3 cis-9, 12, 15 and C20:5n3). Additionally, buffalo milk had relatively lower proportions of potentially undesirable (from human health standpoint) saturated FA (C12:0, C14:0, and C16:0) than cow's milk. Although the present study did not correct the data for various background effects involved in each of the reported studies, it provides a comprehensive comparison between buffalo and cow milk fat and is likely to have useful implications for the promotion of buffalo as a dairy animal from the human health point of view.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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.
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".