Evaluating the effectiveness of cleaning with detergent soap alone verses detergent soap followed by sanitizer on reducing aerobic microorganism numbers that are present on food contact surfaces
Bibliographic record
Abstract
Background: Cross-contamination is one of the leading causes of foodborne illness which poses a massive burden to an individual’s health and to the healthcare system. One way to prevent cross-contamination is through the elimination of pathogens from surfaces by properly washing with a detergent soap followed by sanitizing with a sanitizer. However, as found from a previous research study, not all restaurants in British Columbia wash and sanitize their food contact surfaces. Thus, this study aims to compare the cleaning effectiveness between using detergent soap alone verses using detergent soap followed by sanitizer. Methods: Aerobic organisms were introduced to a cutting board by cutting alfalfa sprouts and then the surface was cleaned with Dawn Detergent soap and sanitized with 200ppm of chlorine bleach sanitizing solution. 3M™ Quick Swabs were used to sample the aerobic organisms (colony forming units) prior to and after each method of cleaning. The swabs were then transferred to 3M™ Petrifilm Plates, incubated at room temperature for 4 days, and then enumerated. Results: The results show that there is a statistically significant greater microbial reduction through cleaning with detergent soap followed by sanitizer (mean log microbial reduction of 4.10) as compared to cleaning with detergent soap alone (mean log microbial reduction of 3.53). The p-value obtained is 0.003843 when α=0.05. The power was determined to be 92%. Conclusions: This study was able to conclude that cleaning with detergent soap followed by sanitizer is 0.57 log (mean log microbial reduction of 4.10 - mean log microbial reduction of 3.53) more effective at cleaning than using detergent soap alone. However, the specific log microbial reduction value for the detergent soap followed by sanitizer achieved in this study is lower than what is found in the previous studies (Gilbert, 1970; Sores et al., 2012; Rossvoll et al., 2015). A possible reason for this discrepancy may be due to the presence of soil and food debris on the surface which may have had interfered with the sanitizing ability of the chlorine bleach (Lee et al., 2007).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".