Long term impact of lignin accumulation in cattle manure digesters on biomass activity and chemical post treatment
Bibliographic record
Abstract
• Long-term anaerobic biodegradability of lignin-rich cattle manure was 42 %. • The highest solubilization of digested cattle manure was observed at pH 12. • Digested cattle manure solubility does not corelate to biodegradability. • Lignin is refractory to chemical and anaerobic treatment. • Bacteroidota and Firmicutes were dominant in cattle manure and digestate. Animal manures, which are typically rich in lignocellulosic content, pose both significant environmental impacts and opportunities for renewable energy. Lignin is particularly resistant to anaerobic degradation. In this work, the effect of lignin accumulation on anaerobic biomass activity and its potential degradation by chemical post treatment was evaluated. Anaerobic digestion of lignin-rich cattle manure (CM) in a 12-L continuously stirred tank reactor for 224 days (d) under mesophilic conditions, at an average organic loading rate of 2.9 g COD/L/d, and sludge retention time (SRT) of 30 d achieved average steady-state COD, lignin, cellulose, and hemi-cellulose removal efficiencies of 41 %, 11.9 %, 54.5 %, and 55.4 %, respectively. Fluorescence excitation-emission matrix parallel factor (EEM-PARAFAC) analysis for the cattle manure and digestate indicate the presence of aromatic compounds, potentially a lignin hydrolysis by-products, which may be inhibitory. The application of chemical post treatment to enhance the anaerobic biodegradability of lignin-rich digested cattle manure (DCM), achieved additional biodegradability of 15%–24 %, which did not correlate with solubility. This work has demonstrated that despite the accumulation of lignin in the digestate, the activity of the acclimatized lignocellulose-degrading bacteria was enhanced, and thus post treatment technologies should be assessed not only based on their impact with respect to lignin solubilization, but also with respect to how they affect microbial activity.
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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 | 0.000 | 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 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".