Use of thermal imaging and the in situ technique to assess the impact of an inoculant with feruloyl esterase activity on the aerobic stability and digestibility of barley silage
Bibliographic record
Abstract
Addah, W., Baah, J., Okine, E. K. and McAllister, T. A. 2012. Use of thermal imaging and the in situ technique to assess the impact of an inoculant with feruloyl esterase activity on the aerobic stability and digestibility of barley silage. Can. J. Anim. Sci. 92: 381–394. Feruloyl esters limit the digestibility of forages, a constraint that may be overcome if additives with feruloyl esterase (FE) activity are applied to forage. This study determined if a FE-producing strain of Lactobacillus buchneri LN4017 in combination with Lactobacillus plantarum LP7109 and Lactobacillus casei LC3200 improves fermentation, aerobic stability and in situ fibre disappearance of whole-crop barley silage. Barley forage (350 g kg −1 DM) was either uninoculated (UN) or inoculated (1.3×10 5 CFU g −1 fresh forage; IN) and ensiled in Ag-Bag ® silos. Bags were opened after 90 d of ensiling. Samples were collected on day 95, 123 and 175 for determination of fermentation characteristics. Surface temperature of the face of each bag was measured over 3 d using a thermal infrared camera. Ruminal in situ DM and NDF disappearance (aNDFD) of silage and rumen fermentation patterns were measured using three ruminally cannulated heifers. The L. buchneri-treated silage possessed a higher acetic acid concentration than UN (48.8 vs.18.4 g kg −1 DM). The temperature at the face of IN was lower than UN immediately upon exposure and after 3 d of aerobic exposure. Inoculation increased (P=0.01) 24-h and 48-h aNDFD with a trend towards a glucogenic pattern of ruminal fermentation in heifer compared with UN silage. There was evidence that the FE-producing inoculant improved aerobic stability and aNDFD of whole-crop barley silage.
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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 | 0.001 | 0.001 |
| 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".