Effects of exogenous fibrolytic enzymes on epiphytic microbial populations and <i>in vitro</i> digestion of silage
Bibliographic record
Abstract
Abstract Epiphytic microbial populations, reducing sugar (RS) concentrations and in vitro fermentation were measured in unsterilised and sterilised barley silage and corn silage treated with an exogenous enzyme preparation. Enzyme treatments comprised spraying silages (10 ml kg−1 DM) with a xylanase/β‐glucanase enzyme preparation or with water or autoclaved enzyme (controls). In Experiment 1, autoclaving the silages increased (P < 0.05) concentrations of RS present 24 h after treatment. Enzymes increased (P < 0.05) RS in both fresh and autoclaved silages, more so (P < 0.05) with autoclaving than without. Autoclaved enzymes did not affect RS concentrations relative to the (water) controls. Aerobic exposure of corn silage numerically increased microbial numbers; no microbial viability was detected in autoclaved silages. Enzymes increased (P < 0.05) total bacterial counts in all silage types, and this effect was more pronounced on aerobically exposed silage. In Experiment 2, RS concentrations were determined 0 and 24 h after enzyme treatment of silages unsterilised or sterilised with ethylene oxide (EO). Irrespective of EO or silage type, RS concentrations were higher (P < 0.05) 24 h after enzyme treatment than immediately after (0 h). In enzyme‐treated silages, 24 h RS concentrations were higher (P < 0.05) with EO than without. Reducing epiphytic microbiota by sterilisation conserved enzyme‐liberated RS in the silages. Aerobic exposure before applying enzymes enhanced RS‐associated increases in microbial numbers. Enzymes effectively released RS from silages, but utilisation of the RS by inherent epiphytic micro‐organisms may limit their availability to the ruminant. By releasing RS, exogenous enzymes may encourage silage deterioration if the interval between treatment and feeding is excessive. During in vitro incubation of freeze‐dried silages (Experiment 3), incorporation of 15N into microbial N was decreased by enzyme applied to fresh silage (before drying), but increased by enzyme applied after the silage had been dried. Moisture level of feeds and epiphytic microbial populations may influence the effectiveness of enzyme treatment for enhancing utilisation of feeds by ruminants. For the Department of Agriculture and Agri‐Food, Government of Canada. © Minister of Public Works and Government Services Canada 2002. 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) | 0.001 | 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".