Effect of Inoculum Concentration and Pretreatment on Biomethane Recovery From Cotton Gin Trash
Bibliographic record
Abstract
The potential of cotton gin waste, a considerable challenge to the gin owners, has not been fully investigated as a renewable energy source via anaerobic digestion. The weathered cotton gin trash and inoculum for triplicate biomethane potential assays were obtained from a local cotton gin mill and a municipal wastewater treatment plant, respectively. The moisture, total solids, volatile solids, and C, H, N, S, hemicellulose + cellulose, and lignin contents of gin waste were determined in triplicates. The biomethane potential of untreated and pretreated (hot water and 6% NaOH (wet CGT weight basis) gin waste was determined at different inoculum to substrate ratios. The highest cumulative biomethane yield of 111.8 mL gvs-1 was observed in inoculum to substrate ratio of 2.3, and it was statistically similar to the values; 101.8, 104.7, 100.5, and 108.9 gvs-1, observed in 0.8, 1.2, 1.5, and 1.9, respectively. The biomethane yield at the inoculum to substrate ratio of 0.4 was significantly lower than all higher ratios. The T80-90 for biomethane production was 26-30 for the ISRs of 1.2, 1.5, and 2.3. The T80-90 for inoculum to substrate ratios of 0.4, 0.8, and 1.9 were 26-31, 27-32, and 27-31 d, respectively. The modified Gompertz equation fitted very well (R2 = 0.98-0.99) to the anaerobic digestion at all inoculum to substrate ratios and pretreatments as the observed and predicted biomethane values were similar. The model predicted a lag phase of 8-10 days for control and treatments compared to the observed of 10-15 days. The highest biodegradability of 24.8±2.6% was observed at inoculum to substrate ratio of 2.3, which was statistically similar to the values observed in ratios of 0.8, 1.2, 1.5, and 1.9, respectively. Among pretreatments, the highest biodegradability of 33.0±2.4 was observed in 6% NaOH pretreatment, and it was statistically similar to hot water treatment and non-pretreated or control. These research findings advance the knowledge in the anaerobic degradation of cotton gin trash, thus helping to maximize biomethane recovery from this agro-industrial waste.
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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) | 0.001 | 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 | 0.001 |
| 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".