Long-Term Effects of Feeding Monensin on Milk Fatty Acid Composition in Lactating Dairy Cows
Bibliographic record
Abstract
The objective of this study was to determine the long-term effects of feeding monensin on milk fatty acid (FA) profile in lactating dairy cows. Twenty-four lactating Holstein dairy cows (1.46 +/- 0.17 parity; 620 +/- 5.9 kg of live weight; 92.5 +/- 2.62 d in milk) housed in a tie-stall facility were used in the study. The study was conducted as paired comparisons in a completely randomized block design with repeated measurements in a color-coded, double blind experiment. The cows were paired by parity and days in milk and allocated to 1 of 2 treatments: 1) the regular milking cow total mixed ration (TMR) with a forage-to-concentrate ratio of 60:40 (control TMR; placebo premix) vs. a medicated TMR [monensin TMR; regular TMR + 24 mg of Rumensin Premix per kg of dry matter (DM)] fed ad libitum. The animals were fed and milked twice daily (feeding at 0830 and 1300 h; milking at 0500 and 1500 h). Milk samples were collected before the introduction of treatments and monthly thereafter for 6 mo and analyzed for FA composition. Monensin reduced the percentage of the short-and medium-chain saturated FA 7:0, 9:0, 15:0, and 16:0 in milk fat by 26, 35, 19, and 6%, respectively, compared with the control group. Monensin increased the percentage of the long-chain saturated FA in milk fat by 9%, total monounsaturated FA by 5%, total n-6 polyunsaturated FA (PUFA) by 19%, total n-3 PUFA by 16%, total cis-18:1 by 7%, and total conjugated linoleic acid (CLA) by 43% compared with the control group. Monensin increased the percentage of docosahexaenoic acid (22:6n-3), docosapentaenoic acid (22:5n-3), and cis-9, trans-11 CLA in milk fat by 19, 13, and 43%, respectively, compared with the control. These results suggest that monensin was at least partly effective in inhibiting the biohydrogenation of unsaturated FA in the rumen and consequently increased the percentage of n-6 and n-3 PUFA and CLA in milk, thus enhancing the nutritional properties of milk with regard to human health.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".