Effects of flaxseed supplementation on milk production, milk fatty acid composition and nutrient utilization by lactating dairy cows
Bibliographic record
Abstract
Twelve multiparous Holstein cows at 72 +/- 20 days in milk were used in a switch-back design with 14-d periods to determine the effect of replacing barley grain into a dairy total mixed ration with micronized or raw flaxseed on nutrient digestibility, milk yield, milk composition. Total mixed diets were (DM basis) 50% barley silage, 50% concentrate mix mainly rolled barley grain and canola meal. Diets were supplemented with 1 kg raw (RF) or micronized (MF) flaxseed to substitute 1 kg of rolled barley grain (C). Neutral detergent fibre, ADF and CP digestibility of the diets were not significantly affected by supplementation; however, calcium digestibility was reduced by 62% and 46% when raw and micronized flax were fed, respectively. Milk yield (38.3, 39.6, and 38.4 kg/d for diets C, RF and MF, respectively) was similar for all diets. Milk fat (3.50, 3.48, and 3.52%) and protein (3.31, 3.34, and 3.31%) for diets C, RF and MF, respectively, were not affected by treatment diets. Concentrations of c9, t11 conjugated linoleic acid (CLA; 0.51, 0.72 and 0.76 g/100 g fatty acids) in milk fat increased (P<0.05) similarly among the two flaxseed supplemented diets. The RF and MF diets significantly increased the C18:1, C18:1 trans-11, C18:2 cis-9, cis-12 and C18:3 in milk fat however, C12:0, C14:0 and C16:0 were significantly reduced compared with control. Replacing barley grain with flaxseed in the diet of lactating cows increased the beneficial fatty acids in milk without depressing nutrient digestibility. Micronization of flaxseed did not reveal any advantage over raw flaxseed.
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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) | 0.001 | 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 | 0.001 |
| 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".