Effects of inoculum temperature and characteristics on cellulose and sewage sludge biodegradability: A comparative study of three inocula
Bibliographic record
Abstract
The role of inoculum in initiating anaerobic digestion (AD), and accelerating the start-up of anaerobic digesters has been well-documented. However, the effect of aligning the origin temperature of the inoculum with the operational temperature of the new digester remains underexplored. This study investigates how the origin temperature and characteristics of the inoculum affect the kinetics and biodegradability of sewage sludge (SS) and microcrystalline cellulose (MCC) under mesophilic and thermophilic conditions. Three inocula were used: one thermophilic (I1) and two mesophilic inocula (I2 and I3) in six Biomethane Potential tests (BMP) at 37 and 55 °C. Results indicated that inoculum temperature had no significant impact on the BMP values for MCC and SS, regardless of the experimental temperature. However, kinetic analyses revealed that I2 significantly outperformed I1 and I3 under both temperature conditions. This was attributed to I2's more diverse bacterial structure and lower inhibitor concentrations. High alkalinity, ammonia, and volatile fatty acids (VFA), as well as the presence of denitrifying bacteria (41.7 % of total communities in I1) contributed to poor kinetics of I1 and I3, which were unsuitable for mesophilic and thermophilic temperatures, respectively. Alkalinity (correlation with the Simpson index = -0.92, p < 0.05) and ammonia (correlations with Chao and ACE = -0.93 and -0.91, respectively, p < 0.05) were significantly linked to low bacterial diversity, while high VFA levels were strongly associated with poor inoculum kinetics (correlation with degradation kinetics = -0.90 to -0.99, p < 0.05). These findings offer insights into assessing the inoculum suitability based on its characteristics.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".