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Record W7018225966

Development of a Novel Egg Surface Decontamination Method via Electro-nano-spray

2023· dissertation· en· W7018225966 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2023
Typedissertation
Languageen
FieldEngineering
TopicElectrohydrodynamics and Fluid Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsHuman decontaminationHydrogen peroxideWater disinfectionMicroorganismEnvironmentally friendlyContaminationSurface water
DOInot available

Abstract

fetched live from OpenAlex

Chicken eggs and their products are a widely consumed and important source of nutrients for people worldwide. However, they can also be vehicles for pathogens like Salmonella and Escherichia coli (E. coli) that can cause foodborne illnesses. Commercially processed eggs in North America are typically washed with hot water and a chemical solution to decontaminate the surface of eggshells. Although the washing process is effective, this approach also removes the egg cuticle, which acts as a natural barrier to bacterial intrusion. In addition, the use of large amounts of water and washing chemicals produces significant amounts of chemically contaminated wastewater, making this approach environmentally unsustainable. Therefore, exploring alternative methods and innovative technologies that are both effective in preserving food and environmentally friendly would be important to the egg industry.\nRecently, a new and innovative technique based on nanotechnology called Engineered Water Nanostructures (EWNS) has been developed as a chemical-free solution for disinfection processes. EWNS are formed by electrospraying and ionizing water to create highly charged nanoscale water droplets that possess unique physicochemical properties. It means EWNS are electron-rich water shells that contain a variety of reactive oxygen species (ROS) including hydroxyl radicals, superoxide, and hydrogen peroxide generated during the electrospray process which has been proven to effectively deactivate bacteria. Researchers have explored the effectiveness of EWNS against food-related microorganisms on the surface of various fruits and vegetables. The consumption of eggs is common in Canada, with an average person consuming about 242 eggs per year. However, it has not yet been tested whether EWNS could effectively decontaminate egg surfaces, which could potentially serve as an alternative disinfection method in the egg industry.\nTo evaluate the effectiveness of EWNS on eggshell decontamination, this research project was conducted in three phases. In Phase 1, an electro-nano-spray system was developed to generate EWNS, and lab-based experiments were conducted to assess the effectiveness of the process against E. coli inoculated on the eggshell surface. The parameters investigated included exposure time, water flow rate, and electric field strength to identify the most optimal operating conditions for the EWNS system. In Phase 2, the efficacy of the EWNS method to inactivate Salmonella on the egg surface was investigated under the optimal operating conditions established in Phase 1. In Phase 3, the impact of the EWNS technique on the quality attributes of treated eggs was evaluated and compared to washed and fresh eggs. Egg quality was measured based on physical properties such as eggshell specific gravity, eggshell thickness, albumen and yolk pH, yolk index, Haugh unit, and moisture content of albumen and yolk, as well as chemical components such as the main proteins of albumen. \nThe results of the study showed that in 5 minutes of exposure time, the optimal EWNS operating conditions that produced the highest inactivation efficiency for E. coli inoculated on the egg surface included a water flow rate of 1 μL/min/needle (total flow rate of 16 μL/min), and an electric field strength of 9.0 kV/cm (-4.5 kV at 0.5 cm distance). At these conditions, the system achieved the inactivation efficiency of 97.6% for Escherichia coli W3110 with a 1.64 log reduction and 80.4% for Salmonella enterica serovar Enteritidis with a 0.71 log reduction. Statistical analyses of the physical characteristics of treated eggs showed that there was no significant difference in the properties compared to unwashed and washed eggs one week after treatment (20 eggs per group). Moreover, the physical characteristics of different egg groups (3 eggs per group), including unwashed, washed, and treated eggs, were analyzed over a 21-day storage period, and it was found that the quality of all groups decreased over time. However, there was no significant difference in physical properties between the EWNS-treated eggs and the control (unwashed and washed eggs). The intensity of protein bands of SDS-PAGE gel images were analyzed statistically, and the results indicated that there was no significant variation in protein features between the three sets of eggs (3 eggs per group). The research has demonstrated that the EWNS system can be a promising and environmentally friendly method for decontaminating eggshell surfaces, and may be a suitable substitute for traditional egg sanitation methods. However, the study was limited in scale, and further investigations are required to how the EWNS system can be applied for larger-scale commercial applications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.178
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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