Impact of concentration, temperature, and pH on inactivation of <i>Salmonella</i> spp. by volatile fatty acids in anaerobic digestion
Bibliographic record
Abstract
It is known that the presence of volatile fatty acids may play a role in the inactivation of pathogens for systems that employ an acid phase reactor. This study was conducted to investigate the influence of volatile fatty acids on the inactivation of Salmonella spp. over a range of digestion temperatures. In this study, digesters that were treating municipal wastewater treatment plant sludges were operated at temperatures that ranged from 35 to 49 degrees C and had a solids residence time of 15 days. Samples collected from the effluent of the digesters were dosed with solutions containing acetic, propionic, and butyric acids alone and in mixtures, and the dosed effluents were analyzed for Salmonella spp. over time. In the first round of testing, the digester effluents were dosed with individual organic acids and also a mixture containing all three volatile fatty acids over a range of concentrations from 750 to 6000 mg/L, and the pH of the samples was fixed at a value of 5.5. In the second round of testing, the sample sludges were spiked with a fixed amount of organic acid mixture, and the pH was varied from 4.5 to 7.5. The reduction of Salmonella spp. in digester effluents, when dosed with volatile organic acids, was found to depend on pH, temperature, the chain length of the acids, and the concentration and composition of the acids present. Increases in temperature appeared to increase the inhibitory effects of the volatile organic acids. At mesophilic temperatures, acidic pHs resulted in a greater inhibition of Salmonella spp.; whereas at higher temperatures neutral pHs were found to be more inhibitory. The results suggest that acid phase digesters that operate at elevated temperatures and low pH can achieve substantial reduction of Salmonella spp.
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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) | 0.000 | 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) | 0.001 | 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".