Microbial Decontamination of Egg Surface via Cold Plasma
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».