Use of Essential Oils for Manipulation of Rumen Microbial Fermentation Using Batch Culture
Bibliographic record
Abstract
The objective of this study was to evaluate the effects of various levels of essential oils on feed digestibility, gas production and rumen fermentation. Two batch cultures were designed for screening various doses of each essential oil (EO). Treatments were control (CON), cinnamon oil (CIN), clove oil (CLO), garlic oil (GAR), ginger oil (GIN), and lemongrass oil (LEM). Dosages were 0, 200, 400, 800, and 1600 mg/kg DM in experiment I (1st batch) and 50, 100, 150, and 200 mg/kg DM in experiment II (2nd batch). Digestibility of DM (DMD), neutral detergent fiber and acid detergent fiber was measured at 24 h and 48 h post incubation, while gas production (GP) was read at 3, 6, 12, 24, 36, and 48 h post incubation. Experimental diet used was a dairy type ration consisting of 50% forage (35% grass hay and 15% alfalfa hay) and 50% concentrate (20% barley grain, 10% corn DDGS, 10% wheat DDGS, 5% canola meal, and 5% vitamin and mineral supplements). All essential oils could improve DM disappearance with consistent results in both experiment I and experiment II. Meanwhile, the essential oils had no effect on NDF and ADF digestibility. Total VFA concentration and individual VFA proportion in experiment I were not affected by the essential oils. However, 200 mg/kg DM of each EO increased total VFA concentration without any effect on individual VFA proportion in experiment II. Ammonia N concentration was reduced by the essential oils in both experiments I and II, confirming the effect of essential oils on deamination. However, the effect of EOs on methane production was apparently negligible. These results suggest that the EOs used in the present study could be potentially developed as rumen modifiers to improve feed digestibility in the rumen.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".