Effect of Feeding Whole, Unprocessed Sunflower Seeds and Flaxseed on Milk Production, Milk Composition, and Prostaglandin Secretion in Dairy Cows
Bibliographic record
Abstract
Four multiparous Holstein cows were used in a 4 x 4 Latin-square design experiment to study the effects of different fat sources on milk production and composition, N utilization, follicular development, and prostaglandin secretion. Cows were fed 4 total mixed rations (TMR) based either on calcium salts of palm oil (Megalac), whole flaxseed, whole sunflower seed, or no supplementary fat (control). Feed intake and digestibilities were generally similar among treatments, except that ether extract digestibility was the lowest for cows fed the control diet. Milk yields were greater for cows fed whole flaxseed and Megalac (32.1 and 31.5 kg/d, respectively) than for those fed sunflower seed and control (25.9 and 24.8 kg/d, respectively). Milk protein concentration was significantly lower for cows fed Megalac (3.68%) compared with those fed flaxseed (3.87%) or control (3.92%). Concentrations of n-3 fatty acids and the n-6 to n-3 fatty acids ratio in milk were the highest and lowest, respectively, for cows fed whole flaxseed. There was an interaction between treatment and time for levels of 13,14-dihydro-15-keto-PGF(2alpha) in plasma; they were greater 30 and 45 min after the oxytocin challenge for cows that were fed sunflower seed compared with those fed either Megalac, flaxseed, or control. Moreover, when concentrations of 13,14-dihydro-15-keto-PGF(2alpha) in plasma were expressed as the area under the overall response curve from 0 to 120 min after the oxytocin injection, it tended to be greater for cows that were fed the sunflower diet compared with those fed either Megalac or flaxseed. In general, follicle dynamics were similar among treatments. These results suggest that feeding diets with high proportions of n-6 fatty acids (61% of total fatty acids for the sunflower seed diet) tended to increase the secretion of series 2 prostaglandins in blood.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".