<i>Trichoderma</i> enzymes promote <i>Fibrobacter succinogenes</i> S85 adhesion to, and degradation of, complex substrates but not pure cellulose
Bibliographic record
Abstract
Abstract The effects of an enzyme preparation from Trichoderma longibrachiatum (TE) on adhesion and growth of the fibrolytic rumen bacterium Fibrobacter succinogenes S85 was studied to gain a better understanding of the action of feed enzyme additives on fibre digestion by ruminants. Adhesion experiments were performed on crystalline cellulose, corn silage and alfalfa hay. Adhesion of F succinogenes to cellulose was negatively related to the concentration of TE (p < 0.05). At the highest concentration used, TE reduced adhesion to cellulose from 65 to 39%. For corn silage and alfalfa hay, TE stimulated adhesion at low levels (p < 0.05) but this effect was lost at higher levels. Culture experiments were performed on crystalline cellulose and corn silage. The presence of TE in media containing cellulose failed to increase substrate disappearance or gas production although it increased numbers of non‐adherent bacteria (p < 0.05). When corn silage was used, the addition of TE increased NDF disappearance (p < 0.05) at 24 and 48 h (33 and 52% in controls versus 53 and 65% in TE treatments). Growth rate and gas production were also stimulated (p < 0.05). We conclude that, for cellulose, the hydrolytic enzymes in TE obstructed available binding sites decreasing bacterial adherence. Fibrobacter succinogenes digested cellulose efficiently and addition of exogenous cellulases did not further increase substrate disappearance. However, for complex plant substrates, low concentration of TE increased bacterial adhesion and plant (corn) fiber degradation. For the Department of Agriculture and Agri‐Food, Government of Canada, © Minister of Public Works and Government Services Canada 2004. Published for SCI by John Wiley & Sons, Ltd.
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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".