Microbial Decontamination of Egg Surface via Cold Plasma
Bibliographic record
Abstract
Eggs and egg products are widely consumed worldwide. In North America, eggshells are cleaned to eliminate contamination by microorganisms such as Salmonella and Escherichia coli. The most common commercial decontamination method in the egg industry is washing eggshells with hot water and a chemical solution. Egg washing reduces the bacterial load, however, the use of chemicals can produce a considerable amount of chemically contaminated wastewater.\nMore recently, cold plasma or non-thermal plasma has attracted global attention as an emerging non-thermal technology for food decontamination. Cold plasma is an emerging green technology, generating several reactive species that can be used effectively for microorganism inactivation and is attracting global attention for food safety purposes. Investigating the application of this technology as a chemical-free and non-thermal approach for decontaminating egg surfaces and assessing its potential as an alternative to the conventional method of washing eggs was the primary objective of this study. For optimizing the process, various operation conditions of a cold plasma jet device were examined to decontaminate eggshells inoculated with Escherichia coli and Salmonella. The different operating variables, including the distance between the nozzle and egg surface (1, 2, or 3 cm), device power (300, 350, or 400 W), gas flow rate (30, 32.5, or 35 l/min), feed gas (air, N2, He and air mixture), relative humidity of the feed gas (20%, 40%, 65%), and exposure time (20, 40, or 60 s) were examined in the study. To evaluate the potential impact of cold plasma on egg quality, different properties such as eggshell thickness, specific gravity, albumen pH, Haugh unit, yolk index, moisture content, and qualitative analysis of the egg albumen and yolk were measured after the treatment with cold plasma. \nThe results showed that 60 seconds of direct exposure time resulted in the optimal cold plasma operating conditions that led to the highest deactivation percentage for bacteria inoculated on the egg surface included an air (RH=65%) flow rate of 35 l/min, a distance of 1 cm, and a power of 400 W. At these conditions, the system achieved a maximum reduction of 1.94 log CFU/egg and a deactivation percentage of 98.64 % for E. coli and 92.20 % deactivation percentage with a 1.11 log reduction for Salmonella.\nStatistical analyses of the physical properties of treated eggs showed that there was no significant difference in physical properties between the cold plasma-treated eggs and the control eggs (unwashed and washed eggs) when measured one week after the treatment. The intensity of protein bands of SDS-PAGE gel image was analyzed, and the results indicated that there was no significant variation in protein content between the three sets of eggs (cold plasma-treated, washed, and unwashed eggs). The research has demonstrated that cold plasma jet can be used as a promising and environmentally friendly method for decontaminating eggshell surfaces. However, the study was limited in scale, and further investigations are required to scale up and apply the cold plasma system for large-scale commercial applications.
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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) | 0.001 | 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 | 0.001 | 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 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".