Microbiota succession during aerobic stability of maize silage inoculated with <i>Lentilactobacillus buchneri</i> NCIMB 40788 and <i>Lentilactobacillus hilgardii</i> CNCM‐I‐4785
Bibliographic record
Abstract
Aerobic deterioration of silage following feeding out is responsible for the deterioration of its quality. Inoculation of silage with lactic acid bacteria is one strategy to limit these effects. A trial was performed using whole-plant corn ensiled in bag silo, and forage was inoculated with Lentilactobacillus buchneri NCIMB 40788 (Lactobacillus buchneri) and Lentilactobacillus hilgardii CNCM-I-4785 (Lactobacillus hilgardii) or not (Control silage). After 159 days of fermentation, the silos were opened and the silage was sampled at 24-h intervals during a 10-day aerobic stability assay to measure pH, the fermentation profile, mycotoxins, and microbial and fungal populations. In inoculated silage, lactic acid concentrations and pH remained stable during the aerobic phase and higher microorganism alpha-diversity was observed. Treated silage was characterized by a high abundance of Saccharomycetes and maintenance of Lactobacillus throughout the aerobic stability assay. The high aerobic stability of the inoculated silage contrasted with the decrease in lactic acid contents and the increase in pH observed in the Control silage, concomitantly with an increase in lactate-assimilating yeast (Pichia and Issatchenkia), and in Acetobacter and Paenibacillus OTUs. Remarkably, Penicillium and roquefortine C were detected in this silage by day 8 following exposure to air. Our study highlighted the fact that the use of L. buchneri with L. hilgardii modified the consequences of exposure to air by maintaining higher microbial diversity, avoiding the dominance of a few bacteria, and preventing fungi from having a detrimental effect on silage quality.
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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) | 0.000 | 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) | 0.001 | 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".