Digestion, Milk Production, Milk Composition, and Blood Composition of Dairy Cows Fed Whole Flaxseed
Bibliographic record
Abstract
A total of 90 lactating Holstein cows averaging 628 kg (SE = 8) of body weight (BW) were allotted at calving to 30 groups of three cows blocked for similar calving dates to determine the effects of feeding whole untreated flaxseed on milk production and composition, fatty acid composition of blood and milk, and digestibility, and to determine whether flaxseed could substitute for other sources of fat such as Megalac and micronized soybeans. Cows were fed a total mixed diet based on grass and corn silage and fat supplements for ad libitum intake. The experiment was carried out from calving up to wk 16 of lactation. Cows within each block were assigned to one of the three isonitrogenous, isoenergetic, and isolipidic supplements based on either whole flaxseed (FLA), Megalac (MEG), or micronized soybeans (SOY). Intake of dry matter and change in BW were similar among diets. Cows fed FLA had greater milk yield than those fed MEG (35.7 vs. 33.5 kg/d) and there was no difference between cows fed FLA and those fed SOY (34.4 kg/d). Fat percentage was higher in the milk of cows fed MEG (4.14%) than in the milk of those fed FLA (3.81%) or SOY (3.70%), but milk protein percentage was higher for cows fed FLA (2.98%) than for those fed MEG (2.86%) and SOY (2.87%). Digestibilities of acid detergent fiber, neutral detergent fiber, and ether extract were lower for cows fed FLA than for those fed SOY and MEG. Retention of N was similar among diets. Feeding FLA resulted in the lowest omega-6-to-omega-3-fatty-acids ratio, which would improve the nutritive value of milk from a human health point of view. The data suggest that micronized soybeans and Megalac can be completely substituted by whole untreated flaxseed as the fat source in the diet of early lactating cows without any adverse effect on production and that flaxseed increased milk protein percentage and its omega-6-to-omega-3-fatty-acids ratio.
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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".