In vitro ruminal fermentation and methane inhibitory effect of three species of microalgae
Bibliographic record
Abstract
In this study, in vitro ruminal fermentation, anti-methanogenesis, and ammonia formation of two autotrophic algae [Nannochloropsis gaditana (NG), Phaeodactylum tricornutum (PT)], and one heterotrophic alga [Schizochytrium sp. (SS)] were investigated. The experimental diets consisted of a hay-concentrate basal diet (BD; 200 mg dry matter) supplemented with (1) no algae (just BD), (2) 40 mg of dried NG (BD + NG), (3) 40 mg of dried PT (BD + PT), and (4) 14 mg of dried SS. In total, 48 samples (four algal treatments × two replicates × three runs × two cows) were incubated for 24 h using the Hohenheim gas test method. All three algae decreased (P < 0.05) the production of short-chain fatty acids and protozoal abundance (both adjusted in amount to BD) as compared with BD. Ammonia formation of BD + NG and BD + PT was 1.2- and 1.1-fold of values in BD, respectively. The BD + NG diet enhanced the proportions of isobutyrate, valerate, and isovalerate at cost of acetate proportion of total short-chain fatty acids, whereas the BD + PT diet promoted the proportions of propionate and valerate at cost of acetate. None of the microalgae affected in vitro methane formation. In conclusion, these algae showed a very poor fermentability and no anti-methanogenic effect in vitro.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".