Impact of Organic Loading Rate on Psychrophilic Anaerobic Digestion of Solid Dairy Manure
Bibliographic record
Abstract
Increasing the feed total solids to anaerobic digester improves the process economics and decreases the volume of liquid effluent from current wet anaerobic digestion. The objective of this study was to develop a novel psychrophilic (20 °C) anaerobic digestion technology of undiluted cow feces (total solids of 11%–16%). Two sets of duplicate laboratory-scale sequence batch bioreactors have been operated at organic loading rates (OLR) of 6.0 to 8.0 g total chemical oxygen demand (TCOD) kg−1 inoculum day−1 (d−1) during 210 days. The results demonstrated that the process is feasible at treatment cycle length (TCL) of 21 days; however, the quality of cow feces rather than the OLR had a direct influence on the specific methane yield (SMY). The SMY ranged between 124.5 ± 1.4 and 227.9 ± 4.8 normalized liter (NL) CH4 kg−1 volatile solids (VS) fed d−1. Substrate-to-inoculum mass ratio (SIR) was 0.63 ± 0.05, 0.90 ± 0.09, and 1.06 ± 0.07 at OLR of 6.0, 7.0, and 8.0 g TCOD kg−1 inoculum d−1, respectively. No volatile fatty acids (VFAs) accumulation has been observed which indicated that hydrolysis was the rate limiting step and VFAs have been consumed immediately. Bioreactors performance consistency in terms of the level of SMYs, VFAs concentrations at end of the TCL, pH stability and volatile solids reduction indicates a stable and reproducible process during the entire operation.
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 | 0.001 |
| 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 | 0.001 | 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".