Impact of <i>Pediococcus pentosaceus</i> and <i>Pichia anomala</i> in combination with chitinase on the preservation of high‐moisture alfalfa hay
Bibliographic record
Abstract
Abstract This study assessed the effects of applying Pediococcus pentosaceus (PED) or Pichia anomala (PIC) in combination with chitinase (CH) on the conservation characteristics and rumen digestibility of large round‐bale high‐moisture alfalfa hay (HMH). Alfalfa was wilted in the field to 23%–27% moisture and baled without (Control) or with PED + CH, PIC + CH and propionic acid (PA). The study was repeated yearly from 2012 to 2014. The PED + CH‐treated HMH had the numerically lowest high degree day (bale internal temperature >30°C) in all 3 years, which was less (p < .05) than Control HMH and PA in 2012. Treatments had no effect on pH, but mixed effects on chemical and microbial compositions across 3 years. The PED + CH treatment had the highest water‐soluble carbohydrate (WSC) content (p < .05) in 2012 and 2014, whereas PA treatment had the lowest (p < .05) WSC in these years. Total bacteria were decreased (p < .001) by PIC + CH and PED + CH in 2012 only. The PED + CH treatment had greater (p < .01) soluble fraction of dry matter (DM) than Control HMH and PA in both 2012 and 2014, but treatments did not affect the potential degradable fraction of DM. The PED + CH and PIC + CH treatments increased (p < .01) in situ neutral detergent fibre digestibility after 6, 24 and 96 hr of ruminal incubation in 2012 but not in 2014. Combinations of P. pentosaceus or P. anomala with chitinase have potential as high‐moisture hay inoculants to reduce microbial spoilage and to increase fibre digestibility.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".