Comparative denaturing gradient gel electrophoresis analysis of fungal communities associated with whole plant corn silage
Bibliographic record
Abstract
Significant portions of grain produced for livestock consumption are convened into ensiled forage. Silage producers have long recognized the positive effects of using an inoculant to insure the proper transformation of forage into a palatable and digestible feedstuff. When silage is fed from a storage structure, exposure to air stimulates the growth of epiphytic aerobes that may result in the loss of up to 50% of the dry matter. Moreover, fungi have been found to be associated with ensiled forage, but their growth is normally suppressed by the anaerobic conditions. However, the introduction of oxygen results in a fungal bloom, and the fungi and the associated metabolites may result in lost productivity in the livestock consuming the contaminated forage. In this study, we report on the diversity of the fungal community associated with whole plant corn silage during the ensiling process, and the effect of two different bacterial inoculants as compared with the uninoculated natural epiphytic fermentation on the distribution of the fungi associated with the silage. The fungal community from duplicate mini-silo packages of the same treatment was analyzed by denaturing gradient gel electrophoresis and direct sequencing of the resulting operational taxonomic units. This method proved useful in analyzing the complex microbial communities associated with the forage in that it was possible to determine that one inoculant dramatically influenced the fungal community associated with whole plant corn silage.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".