PSVII-10 Effect of Lactobacillus spp. and Saccharomyces cerevisiae alone or in combination on the fermentation and aerobic stability of whole-crop corn silage
Bibliographic record
Abstract
Abstract The objectives of the study were to evaluate the effects of Lactobacillus spp. and Saccharomyces cerevisiae alone or in combination as inoculants on the ensiling characteristics and aerobic stability of corn silage. Chopped and kernel processed whole-crop corn was treated with either distilled water (CON), or with (cfu g1 fresh forage) 1.1 × 105 of a Lactobacillus plantarum and Lactobacillus buchneri (LAB) mixture (INOC1), 1.0 × 104 S. cerevisiae strain 3 (INOC2), or 1.1 × 105 LAB + 1.0 × 104 S. cerevisiae strain 3 (INOC3) and ensiled in mini-silos. Minisilos were opened at 7, 30, 60 and 90 d of ensiling and a subsample of d 90 silage was used to assess stability after 3, 7, 14 and 21 d of aerobic exposure. Silages were analyzed for chemical and fermentation traits and enumerated for LAB, total bacteria, yeast and mold. Data were analyzed as repeated measures with treatment (T), days of ensiling or aerobic exposure (D) and T × D as main effects, and individual minisilos (n = 3) or insulated containers (n = 3) served as the experimental unit for ensiling and aerobic stability parameters, respectively. Silage in INOC2 had lower pH (P < 0.01), higher lactate (P = 0.03), lower acetate (P < 0.01) and lower LAB counts (P = 0.05) than INOC1 at d 90. Yeast in INOC2 tended to be higher (P = 0.08) than INOC3 on d 3 of aerobic exposure. Aerobic stability of INOC3 was greater (P = 0.01) than CON and INOC2. A combination of LAB and S. cerevisiae strain 3 did not impact fermentation, but enhanced the aerobic stability of corn silage. This raises the possibility of delivering S. cerevisiae strain 3 as direct fed microbial to ruminants in corn 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) | 0.001 | 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 | 0.001 |
| 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".