Changes in the bacterial community colonizing extracted and non-extracted tannin-rich plants in the rumen of dromedary camels
Bibliographic record
Abstract
Leguminous trees and saltbushes provide potential alternatives to conventional feeds to overcome feed deficiency in arid and semi-arid countries. However, these plants are rich in antinutritional factors that have adverse effects on rumen microbiota and the host- animal. Some rumen microbiota detoxifies plants' secondary metabolites; thus, understanding plant-microbe interaction in the rumen could improve the plants' utilization. This study investigated the bacterial colonization and degradation of non-extracted and extracted tanniniferous plants: Atriplex halimus, Acacia saligna, and Leucaena leucocephala, in the rumen of three fistulated camels at 6 and 12 hours. The results showed that these plants have high nutritional value and tannins contents. The rumen degradation and microbial diversity of plant-attached bacteria varied according to plant type and phenols' extraction. Atriplex and leucaena showed higher microbial diversity at 6 and 12h, respectively. Bacteroidetes and Firmicutes were the main bacterial phyla, and the main genera were Prevotella, RC9_gut_group, Butyrivibrio that overrepresented in non-extracted plants (P<0.05). Fibrobacteres and Anaerovibrio showed sensitivity to plant toxins and Ruminococcus attached to plants with lower tannins. Several bacterial genera in the camel rumen have the potential to resist antinutritional factors in fodder plants, which could be used to improve the performance of grazing animals.
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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 | 0.001 | 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) | 0.001 | 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".