Assessment of the Effects of Cinnamon Leaf Oil on Rumen Microbial Fermentation Using Two Continuous Culture Systems
Bibliographic record
Abstract
Two continuous culture (CC) systems, the rumen simulation technique (Rusitec) and a dual-flow (DF) fermenter, were used to evaluate effects of the essential oil from cinnamon leaf (CIN) on rumen microbial fermentation. Incubations (d 1 through 8 for adaptation and d 9 through 16 for sampling) were conducted concurrently in the 2 systems, with CIN added at 0 (control) and 500 mg/L of rumen fluid culture. Eight Rusitec (920 mL; dilution rate = 2.9%/h) and 6 DF (1,300 mL; dilution rate = 6.3%/h) fermenters were randomly assigned to treatment. Inoculum was prepared from 4 ruminally cannulated lactating Holstein cows fed a total mixed ration consisting of 51% forage and 49% concentrate (dry matter basis). Ruminal pH, total volatile fatty acid (VFA) concentration, and diet digestibility were reduced by CIN addition in the Rusitec but were not affected by CIN administration in the DF. The addition of CIN in the Rusitec decreased apparent N disappearance, NH3-N concentration, and molar proportions of branched-chain VFA. In contrast, in the DF no effect of CIN was observed on apparent N degradation, NH3-N concentration, and molar proportion of branched-chain VFA. In the Rusitec, the molar proportion of acetate was similar between treatments on d 9 and 13, but was lower from d 10 to 12 and higher on d 14 to 16 with CIN than with control (interaction of treatment x sampling day). The molar proportion of acetate remained unaffected by CIN addition in the DF. In both CC systems, the molar proportion of propionate was decreased whereas that of butyrate was increased by CIN addition. In the DF, CIN decreased microbial N flow and efficiency of microbial protein synthesis. Protozoa numbers were lower with CIN than with control in both CC fermenters. In the Rusitec, CIN increased 15N enrichment in total bacterial fractions, but no effect was observed on the production of microbial N. This study showed that CIN exhibited antimicrobial activity in both CC systems, but the effects were more pronounced in the Rusitec than in the DF system. These differences are likely a reflection of the higher dilution rate in the DF resulting in a lower effective concentration of CIN than in Rusitec. Based on these changes in rumen microbial fermentation, supplementation of CIN at the concentration evaluated in this study may not be nutritionally beneficial to ruminants.
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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 | 0.001 |
| 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 | 0.001 |
| 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".