Fiber degradability, chemical composition and conservation characteristics of alfalfa haylage ensiled with exogenous fibrolytic enzymes and a ferulic acid esterase-producing inoculant
Bibliographic record
Abstract
Lynch, J. P., Prema, D., Van Hamme, J. D., Church, J. S. and Beauchemin, K. A. 2014. Fiber degradability, chemical composition and conservation characteristics of alfalfa haylage ensiled with exogenous fibrolytic enzymes and a ferulic acid esterase-producing inoculant. Can. J. Anim. Sci. 94: 697–704. This study investigated the effects of two fibrolytic enzyme products, applied at baling alone or in combination with a ferulic acid esterase-producing bacterial additive, on the ensilage dynamics, chemical composition and digestibility of alfalfa haylage. Five replicate wrapped bales were produced with one of five treatments, including an untreated control, and one of two fibrolytic enzyme products (EN1 and EN2) applied either alone or in combination with a ferulic-acid producing bacterial additive (FAEI). No effect of treatment was observed on the neutral detergent fiber (NDF) (P=0.889) or acid detergent fiber (ADF) (P=0.065) concentrations of haylage after ensilage, but haylage produced using fibrolytic enzyme products underwent greater (P<0.018) increases in temperature following exposure to aerobic conditions. Haylages produced with fibrolytic enzyme products had a greater (P<0.001) in vitro NDF degradability (NDFD) than untreated haylage. The use of fibrolytic enzymes applied to alfalfa haylage at ensiling increased the NDFD, despite minimal effects on the chemical composition of the herbage. However, the greater aerobic deterioration of fibrolytic enzyme-treated bales indicates higher dry matter losses during aerobic exposure. The use of FAEI with fibrolytic enzymes did not further enhance the effects of fibrolytic-enzyme treatments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".