Effects of homo- and hetero-fermentative lactic acid bacteria on the quality and aerobic stability of corn silage
Bibliographic record
Abstract
This study aimed to investigate the effects of homo/heterofermentative lactic acid bacteria (LAB) on the quality of corn silage and its rumen digestibility. Maize (Zea mays strain Xingsiyu No. 10), at the early dough stage, was harvested, chopped, ensiled in vacuum bags, and divided into four groups: (1) control (without added bacteria); (2) with the homofermentative LAB Lactobacillus plantarum and Pediococcus pentosaceus (1:1 mixture, 1 × 10 5 cfu·g −1 ); (3) with the heterofermentative LAB Lactobacillus buchneri (1 × 10 5 cfu·g −1 ); and (4) with the homo/heterofermentative LAB L. plantarum, P. pentosaceus, and L. buchneri (1:1:1 mixture). At 2, 8, 15, 45, and 60 d of ensiling, nutritional quality, fermentation characteristics, and microbial content were assessed. After 60 d, aerobic stability and rumen digestibility tests were performed. The addition of homo- and (or) hetero-fermentative LAB significantly improved the nutritional quality, fermentation characteristics, and microbial content. Addition of the heterofermenter L. buchneri, with or without the homofermenters L. plantarum and P. pentosaceus, improved aerobic stability. The different LAB inoculants increased the degradation rates of dry matter, acid detergent fiber, and neutral detergent fiber of the corn silage by sheep ruminants. Analysis indicated that L. buchneri yielded the best 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) | 0.000 | 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".