Microbial Quantification Using ATP and Petrifilms for Irrigation Water Treated with Cold Plasma or Ozone
Bibliographic record
Abstract
Traditional methods of microbial quantification of irrigation water using colony counts from agar culture require dedicated laboratory space and trained personnel, limiting their on-site applicability. Dehydrated Petrifilm™ plates are a simpler alternative but still require 2–3 days to culture. Adenosine triphosphate (ATP) tests may offer a fast and reliable method for quantifying microbes in water. In this study, we compared (a) microbial quantification based on ATP assays with Petrifilm™-based assays, and (b) we evaluated the effectiveness of cold plasma or ozone treatments in controlling microbial growth at various oxidation–reduction potential (ORP) levels. Lake water was recirculated through an ozone or cold plasma treatment system until a target ORP of 700 mV was reached. Samples were collected at various ORP levels and plated for aerobic bacteria and yeast and mold counts using Petrifilm™ plates. The free and total ATP concentrations were measured using the Hygiena EnSURE luminometer and its accompanying free and total ATP swabs. Microbial ATP was calculated by subtracting the free from the total ATP. Cold plasma and ozone showed similar effects on microbial inactivation at 700 mV (p < 0.05). Both treatments achieved complete fungal inactivation at 600–700 mV ORP, bacterial inactivation at 600 mV ORP, and near-complete inactivation of microbial ATP at 600–700 mV. A moderate positive correlation (Pearson’s correlation = 0.39 and Spearman’s rank correlation = 0.39) was observed between the Petrifilm™ bacterial counts and microbial ATP levels, suggesting ATP quantification could complement Petrifilm™ for rapid and non-selective onsite microbial assessment of irrigation water.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".