Feeding oregano oil and its main component carvacrol does not affect ruminal fermentation, nutrient utilization, methane emissions, milk production, or milk fatty acid composition of dairy cows
Bibliographic record
Abstract
Because of their antimicrobial properties, essential oils and their components have been suggested as alternatives to other antimicrobials (e.g., monensin) that are commonly fed to ruminants to improve nutrient utilization and enhance feed efficiency and milk performance. In this study, we evaluated the potential of oregano oil and its main component (carvacrol) as rumen modifiers. For this purpose, 8 ruminally cannulated lactating dairy cows (92 ± 11 d in milk, 36.5 ± 7.6 kg of milk yield, and 703 ± 74 kg of body weight) were used in a double 4 × 4 Latin square (28-d periods). Cows were fed 1 of the 4 following treatments: (1) control (CTL, no additive); (2) monensin [MON, 24 mg/kg of dry matter (DM)]; (3) oregano oil (ORE, 50 mg/kg of DM); and (4) carvacrol (CAR, 50 mg/kg of DM). Cows were fed (ad libitum intake) a total mixed ration consisting of 60% forages (corn silage and alfalfa silage) and 40% concentrates, on a DM basis. Feeding ORE and CAR had no effect on nutrient total-tract apparent digestibility, N utilization, rumen fermentation (i.e., pH, ammonia, volatile fatty acids), protozoa counts, or milk performance. Feeding MON increased the molar proportion of propionate and tended to increase total-tract apparent digestibility of crude protein. None of the feed additives evaluated affected enteric methane production (491 g/d, 21.1 g/kg of DM intake, 6.14% of gross energy intake on average). Milk fatty acid composition was not changed by ORE or CAR, but MON increased the proportion of trans-10 18:1, an intermediate of ruminal biohydrogenation. Thus, when included at 50 mg/kg of dietary dry matter, neither oregano oil nor carvacrol favorably altered rumen fermentation, improved nutrient utilization or milk performance, or mitigated enteric methane emissions in dairy cows.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".