Microbial community dynamics of a sequentially fed anaerobic digester treating solid organic waste
Bibliographic record
Abstract
A 50-kg scale, high solids anaerobic digester (AD) comprising six sequentially fed leach beds with a leachate recirculation system was operated at 37°C for 88 weeks. The solid feedstock contained a constant fibre fraction (a mix of cardboard, boxboard, newsprint, and fine paper) and varying proportions of food waste. Previously, we reported on the stable operation of this digestion system, where significantly enhanced methane production from the fibre fraction was observed as the proportion of food waste increased. The objective of this study was to identify relationships between process parameters and the microbial community. Increasing food waste led to a large increase in the absolute microbial abundance in the circulating leachate. While 16S rRNA amplicons for Clostridium butyricum were most abundant and correlated with the amount of FW in the system and with the overall methane yield, it was more cryptic Candidatus Roizmanbacteria and Spirochaetaceae that correlated specifically with enhanced methane from the fiber fraction. A faulty batch of bulking agent led to hydraulic channeling, which was reflected in the leachate microbial profiles matching that of the incoming food waste. The system performance and microbial community re-established rapidly after reverting to better bulking agent, illustrating the robustness of the system.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".