Effect of a fibrolytic enzyme preparation from <i>Trichoderma longibrachiatum</i> on the rumen microbial population of dairy cows
Bibliographic record
Abstract
The effects of supplementing a dairy cow diet with incremental levels of a fibrolytic enzyme preparation (preparation B) from Trichoderma longibrachiatum on the rumen microbial population were investigated. Two cows fitted with rumen cannulae were each fed a diet containing barley-based concentrate (52%), maize silage (29%), and chopped alfalfa hay (19%), supplemented with 0, 1, 2, 5, or 10 L of preparation B per tonne of dry matter (DM). Preparation B stimulated numbers of total viable bacteria in a quadratic manner (P < 0.05), to approximately 230, 330, 390, and 250% at 1, 2, 5, and 10 L x t(-1) DM, respectively. Preparation B increased the numbers of cellobiose-utilizing (P < 0.01), xylanolytic (P < 0.05), and amylolytic bacteria (P < 0.05), but had no effect (P > 0.05) on numbers of cellulolytic bacteria. However, when bacterial numbers enumerated on each substrate were expressed as a proportion of total viable bacterial numbers, only cellobiose utilizers were stimulated, and this stimulation was limited to the 1 L x t(-1) DM level of preparation B (P < 0.05). The results of this study demonstrate that the inclusion of an exogenous fibrolytic enzyme preparation in dairy cow diets increased the numbers of rumen bacteria that utilize hemicelluloses and secondary products of cellulose digestion.
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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".