Research Note: Evaluation of the efficacy of engineered water nanostructures in inactivating airborne bacteria in poultry houses
Bibliographic record
Abstract
Methods to control microbial contamination in confined livestock facilities are important to the health of both animals and workers. In addition, bacterial contamination is also a food safety issue. The most common disinfection technique employed in livestock facilities is the application of oxidizing agents (e.g., potassium peroxymonosulphate, chlorine, hydrogen peroxide, ozone). However, these techniques are associated with a number of limitations (e.g., toxicity, high cost, corrosiveness). Recently, engineered water nanostructures (EWNS) generated using an electrospray system was found effective in inactivating foodborne bacteria. Thus, this study investigated the efficacy of EWNS generated using a laboratory-scale electrospray system in inactivating bacteria found in poultry facilities. The effects of various operating conditions (distance between the injector and grounded electrode of the electrospray system, applied voltage, liquid pH and conductivity, liquid flow rate, and treatment time) on the efficacy were also assessed. In these various experiments, airborne bacterial samples were collected from a pullet room using tryptic soy agar plates and then exposed to EWNS under varying conditions. After treatment, the plates were incubated at 37°C prior to colony counting. Reductions in bacterial concentrations up to 1.26 logs were obtained. The results indicate that the EWNS generated by the electrospray system can be a potential chemical-free alternative to conventional disinfection methods. Future tests will focus on scaling up the system for larger scale trials.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 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".