Factors influencing the antimicrobial efficacy of Dielectric Barrier Discharge (DBD) Atmospheric Cold Plasma (ACP) in food processing applications
Bibliographic record
Abstract
Atmospheric cold plasma (ACP) is an emerging technology in the food industry with a huge antimicrobial potential to improve safety and extend the shelf life of food products. Dielectric barrier discharge (DBD) is a popular approach for generating ACP. Thanks to the numerous advantages of DBD ACP, it is proving to be successful in a number of applications, including microbial decontamination of foods. The antimicrobial efficacy of DBD ACP is influenced by multiple factors. This review presents an overview of ACP sources, with an emphasis on DBD, and an analysis of their antimicrobial efficacy in foods in open atmosphere and in-package modes. Specifically, the influence of process, product, and microbiological factors influencing the antimicrobial efficacy of DBD ACP are critically reviewed. DBD ACP is a promising technology that can improve food safety with minimal impact on food quality under optimal conditions. Once the issues pertinent to scale-up of plasma sources are appropriately addressed, the DBD ACP technology will find wider adaptation in food industry.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".