Response of Microbial Community to Induced Failure of Anaerobic Digesters Through Overloading With Propionic Acid Followed by Process Recovery
Bibliographic record
Abstract
In order to effectively use microbial-based strategies to manage anaerobic digesters, it is necessary to distinguish between community shifts that are part of the natural dynamic of the system and shifts caused by environmental or operational disturbances. The objective of this research study was to evaluate the significance of changes in the microbial community of anaerobic digesters during failure in correlation to operational parameters such as an organic acid overload. Five continuously stirred 0.5 L reactors were set-up as semi-continuously-fed, mesophilic dairy manure digesters with a 30-day hydraulic retention time. After a 120-day stabilization period, two digesters were kept as controls, while the organic loading rates in the triplicate set were increased step-wise to ultimately provide a shock-load leading to failure using propionic acid spikes. Acidosis resulting in near cessation of biogas and termination of methane production occurred between 4 and 7 weeks, after which all the digesters continued to be fed only dairy manure. The shock loading of propionic acid led to an accumulation of mainly acetate and propionate, with low levels of iso-butyrate, butyrate, iso-valerate, and valerate. High-throughput Illumina sequencing of the V4 region of the bacterial and archaeal 16S rRNA gene in digester samples showed a significant change in the microbial community composition during propionic acid overload, followed by a return to the original composition with regular feedstock. Bacterial genera whose relative abundance decreased during the inhibition stage included Sedimentibacter, Syntrophomonas, TSCOR003.O20, and Marinilabiaceae, while the relative abundance of Lachnospiraceae, Ruminococcus, Mogibacteriaceae, Pyramidobacter, and Bacteroides increased. The relative abundance of dominant methanogens, Methanosarcina and Methanobacterium, although initially resistant, were decreased (from 91.71 to 12.14% and from 2.98 to 0.73%, respectively) during inhibition, while Methanobrevibacter and Methanosphaera that were prominent in the manure feedstock increased from 17.36 to 79.45% and from 0.14 to 1.12%, respectively. Shifts in bacterial and archaeal compositions, back to their pre-shock steady state after failure, highlight the digester’s microbial resilience and recovery potential.
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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 | 0.001 |
| 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".