Gut microbiota of cattle and horses and their use in the production of ethanol and lactic acid from timothy hay
Bibliographic record
Abstract
The gut of herbivorous animals is an untapped source of the microbial consortium that could be used to improve the hydrolysis of lignocellulosic biomass. This study investigated the hydrolysis of Timothy hay by the anaerobic incubation with fecal inocula from four cows (CB) and four horses (HB) for 72 h. The microbial communities colonized timothy hay were analyzed using Illumina Mi-Seq sequencing of 16S rDNA genes. The source of the inoculum affected the structure of microbial communities that were dominated by phylum Firmicutes, Bacteroidetes, and Proteobacteria, and the dominant genera were Enterococcus, Streptococcus, Escherichia-Shigella, Bacteroides, and Prevotella. Moreover, several bacteria were observed exclusively in a specific group. For example, group CB had phylum Fibrobacterota and Spirochaetota besides genera Prevotellaceae YAB2003 and Bacteroides; and group HB had genera Weissella and Lactococcus. Moreover, function prediction revealed that the CB group has a higher abundance of genes related to carbohydrate metabolism. Group CB showed higher neutral detergent fiber degradability (NDFD), gas production, cellulase, xylanase, and xylose, and group HB showed higher dry matter degradability (DMD), glucose, ethanol, and lactic acid. The feces of cattle and horses represent a source of the bacterial consortium for enzyme production and the hydrolysis of lignocellulosic biomass.
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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 | 0.001 | 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".