Oral-stomach sampling as an alternative to rumen canula for the inoculation of in vitro batch fermentation systems
Bibliographic record
Abstract
The standard method to collect rumen fluid (RF) serving as inoculum for in vitro rumen fermentation assays and using ruminally cannulated animals is less and less accepted in some countries, and oral-stomach sampling (OSS) could be an alternative that needs to be validated. The objective of this study was to compare the in vitro rumen fermentation parameters of a large set of substrates with contrasted fermentation profiles using inocula obtained by OSS and from different sampling sites in the rumen of cannulated dairy cows. Rumen fermentation assays were conducted using twelve different substrates (six forages and six total mixed rations) and three types of inoculum consisting in fresh RF sampled in the reticulum (RF ret ), sampled both in the reticulum and the ventral sac (RF mix ) and using OSS (RF tub ) during three feeding periods creating variability in RF composition (control and acidogenic diets). There was a strong effect of substrate on all the parameters (P < 0.001) and a limited effect of the type of RF on the overall fermentability of substrates, particularly between RF mix (standard method) and RF tub that had similar values for dry matter (DM) and fiber degradabilities, gas production (including proportion of methane (CH 4 ) in the gas produced), total volatile fatty acids (VFA) and ammonia (NH 3 ). Above all, we did not detect any interaction between the substrate and the type of RF, highlighting the possibility to measure confidently relative differences among substrates or treatments. Overall, our results showed that fresh OSS can be a relevant alternative to the fresh RF sampling using cannulated animals. To keep OSS as a research tool on the long term, efforts should be continued to improve the standardization and the refinement of the OSS method.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".