Farm management practices and season dependent factors affect the microbial community and chemical profile of corn and grass-legume silages of farms in Ontario, Québec, and Northern New York
Bibliographic record
Abstract
The effects of farm management practices and seasonal variation on the microbial community and chemical composition of corn and grass-legume silage are largely understudied due to the advantages of controlled mini-silo experiments. This study aims to investigate the effects that some key farm factors (use of an inoculant, farm region, and bunker or tower silo) and seasonal variations have on corn and grass-legume silage from farms across Ontario, Quebec, and New York. The silage was either treated with a commercial inoculant (Lallemand Biotal Buchneri 500® or Chr Hansen SiloSolve FC®) or left untreated. The bacterial communities of silage were compared to those of raw bulk tank milk from the same farm to determine if they were similarly affected by management practices or seasonal variations. Family level analysis of the 16S rRNA V3-V4 gene amplicon bacterial community, the ITS1 amplicon fungal community, NMR water soluble metabolome, and mycotoxin LC–MS were performed on silage over a two-year period. Chemical compounds associated with the use of inoculants in corn and grass-legume silage were higher in inoculated corn (acetate, propane-1,2-diol, γ-aminobutyrate; p < 0.001) and grass-legume (propionate; p = 0.011). However, there was no significant difference in the relative abundance (RA) of Lactobacillaceae in either silage type. Leuconostocaceae was higher in non-inoculated corn (p < 0.001) and grass-legume (p < 0.001) silage than in inoculated silage. Tower silos had higher RA of Leuconostocaceae (p < 0.001) and higher pH (p < 0.001) in corn and grass-legume silage. The one farm that used liquid manure with no other fertilizer type had higher RA of Clostridiaceae (p = 0.045) and other rumen/fecal (p < 0.006) bacteria in grass-legume silage than all other farms. Seasonal variation affected most of the key silage microbial families, however the trends were rarely visible across both years. Few trends in microbial variation could be observed in both silage and bulk tank milk: two farms had higher Moraxellaceae (p < 0.001) in milk and either corn or grass-legume silage. In farms using an inoculant, lower Staphylococcaceae was observed in the raw bulk tank milk.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".