Determination of methanogenic <i>Archaea</i> abundance in a mesophilic biogas plant based on 16S rRNA gene sequence analysis
Bibliographic record
Abstract
Energy production of renewable raw material is of increasing importance for sustainable energy production. As an indispensable prerequirement for further upgrading of technical equipment and operation modes of biogas plants, a deeper knowledge of the microbial community responsible for methane formation is crucial. To overcome these limitations a mesophilic biogas plant converting pig manure, maize silage, and grains of crop was sampled and subsequently analysed by construction of a methanogenic Archaea specific 16S rRNA gene clone library combined with PCR-RFLP analysis and group-specific quantitative real-time PCR (qPCR). Seventy percent of all analysed clones belonged to the order Methanomicrobiales, whereas 13% belonged to Methanosarcinales, 6% belonged to the Methanobacteriales group, and 11% of all detected clones were assigned to the CA11 and Arch1 cluster. Comparable percentages were obtained with qPCR: 84% of all detected 16S rRNA gene copy numbers were affiliated with the Methanomicrobiales, while only 14% belonged to the Methanosarcinales and 2% to the Methanobacteriales order. In conclusion, both approaches detected similar archaeal groups and revealed nearly the same abundance, pointing to a predominance of hydrogenotrophic methanogens in the biogas plant.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".