Effects of carvacrol and cinnamaldehyde on microbial fermentation when added to a barley- or corn-based diet in a continuous-culture system
Bibliographic record
Abstract
Six dual-flow continuous-culture fermenters (1300 mL) were used to evaluate in a 2 × 3 factorial arrangement the effects of carvacrol (CAR) and cinnamaldehyde (CIN) supplementation [0.2 g kg-1 of dietary dry matter (DM)] and the source of grain (barley vs. corn) on microbial fermentation. Inoculum was collected from four ruminally cannulated lactating Holstein cows fed a mixed diet of 50% forage and 50% concentrate (16.3% crude protein, 33.5% neutral detergent fiber, DM basis). The experimental period consisted of 10 d, with the first 6 d for adaptation to experimental treatments, and 4 d of sample collection. Fermenter pH was lower for corn- than for barley-based diets (6.14 vs. 6.27; P < 0.05). True crude protein (CP) degradation tended (P = 0.10) to be higher for barley- than for corn-based diets (47.0 vs. 41.3%). Neither CAR nor CIN altered fermentation parameters [pH, NH3-N, total volatile fatty acid (VFA) concentration, and molar proportions of individual VFA], nutrient digestibility, N metabolism, and efficiency of microbial protein synthesis. The results of this study show that at the dosage selected (0.2 g kg-1 of dietary DM), CAR and CIN had no effects on microbial fermentation, feed digestibility, and N metabolism in continuous-culture fermenters fed a barley- or corn-based diet. Key words: Essential oil compound, barley, corn, continuous-culture system
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".