Feeding Strategy of Ruminants and Its Potential Effect on Methane Emission Reduction
Bibliographic record
Abstract
A study was conducted to determine the potential effect of Leucaena leucocephalain the diet with 3 levels 0%, 6%, 12% of ration on the population of rumen methanogenic bacteria of cattle and buffalo. Three each ruminally-fistulated (body weight 342 ± 66.93 kg) were used in this experiment. The amount of feed offered was 2.5% of live weight on DM basis. Rumen fluid was collected from each animal before feeding, after 17 days on feed. The rumen fluid was strained it through cheesecloth and stored in freezer prior to analysis. The samples were subjected to DNA extraction and amplification. Three universal primers were used to detect methanogenic bacteria, which had more than one band, ranging from 500 bp and 1.4 kbp. The results indicated that the level of Leucaena leucocephala in the diets reduced the population of methanogenic rumen bacteria of the cattle and enhanced the Fibrobacter succinogenes. Thus, reduction of methane production increases rumen propionate since methane production is inversely proportional with propionate production. Leucaena leucocephala give many benefit e.g. for ruminant that will have a good impact in the term of ruminant nutrition and global environmental contribution through reducing methanogens 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".