Impact of Inoculation with Pediococcus pentosaceus in Combination with Chitinase on Bale Core Temperature, Nutrient Composition, Microbial Ecology, and Ruminal Digestion of High-Moisture Alfalfa Hay
Bibliographic record
Abstract
This study evaluated the effects of Pediococcus pentosaceus (PP) and chitinase combinations on the conservation and nutritive value of alfalfa high-moisture hay (HMH). P. pentosaceus [1012 colony forming unit/g fresh forage] combined with (g/tonne of fresh forage) 1.5 (PP + LC), 7.5 (PP + MC), or 15.0 (PP + HC) g of LANiHay01 chitinase (Exp. 1) or with LANiHay02 (PP + Fe; 1.5 g), LANiHay01 (PP + Pe; 1.5 g), or Sigma (PP + Si; 55 mg) chitinase/tonne (Exp. 2) were used in 2016. In 2017, PP was applied alone or in combination with LANiHay01 at 1.5 g (PP + LC) or 7.5 g (PP + MC) chitinase/tonne (Exp. 3 and 4). Deionized water and propionic acid (4.0 L/tonne of fresh forage in Exp. 1 and 2 and at 6.0 L/tonne of fresh forage in Exp. 3 and 4) were applied as neutral (CON) and positive control (CON+), respectively. The maximum temperature (r2 = 0.66) and NH3-N concentration (r2 = 0.80) of the HMH were positively related to total microbial populations. PP + MC had lower (p ≤ 0.05) yeast and mold counts than CON in Exp. 3 and 4 while the neutral detergent fiber degradability was greater (p < 0.01) for PP + MC and PP + LC than CON in Exp. 1 and 3, respectively. P. pentosaceus in combination with chitinase has the potential in conserving the nutrient quality of alfalfa HMH.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".