Metagenomic Analysis during Co-Digestion Buffalo Sludge and Tomato Pomace Post Thermal Stress: A Case Study
Bibliographic record
Abstract
The tomato industry and buffalo farming generate waste, including sludge (BS) and tomato pomace (TP), which can significantly impact their economic and environmental sustainability. The case study tracked changes in microflora composition after a thermal shock during anaerobic co-digestion. The inoculum-to-substrate ratio was 0.5 based on volatile solid content under mesophilic conditions. An Automatic Methane Potential Test System was used to monitor the process before and after thermal stress (50°C) occurred for three days. Next-generation sequencing analyzed the bacterial and archaeal communities. The pH decreased, and methane production plateaued due to the high volatile solid content (87 g/L). After thermal stress, the pH returned to neutral, and the batch resumed biogas production. The cumulative CH4 production reached 3,115 Nml. The biogas had a maximum methane peak of 78.5% compared to 58.4% in BS. The taxonomic classification showed that Firmicutes (51.7%) and Bacteroidetes (29.9%) represented 81.6% of the total OTUs among the bacteria. Fonticella, the most abundant Clostridiaceae (average 4.3%), was absent in BS and increased (up to 17.1%) in TP during methane production. Methanocorpusculum was the most abundant in the archaeal community. However, Metanosarcina showed a stronger correlation with methane production. Brief thermal stress significantly altered bacterial and archaeal populations and allowed to resume biogas production.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".