Abstract With the global promotion of healthy diet, people's demand for freshness of food has risen, so extending the shelf life of food has become a hot topic now. Electrostatic field is widely concerned because it has the advantages of simple equipment, low cost, low maintenance, low energy consumption, one investment can be used for a long time, flexible operation, no drug pollution, no secondary pollution to the environment, and can better retain the original quality and flavor of food. As a non-thermal physical preservation technology, electrostatic field preservation can produce ozone and electric ions to kill bacteria inside and outside the food and reduce the enzyme activity, so as to play the effect of preservation. In this paper, based on the introduction of the working principle and mechanism of action of electrostatic field processing technology, the research progress of the application of this technology in different perishable food sterilization and preservation is described, and the limitations of electrostatic field technology are proposed, in order to provide a theoretical basis for the processing application of electrostatic field in perishable food and to provide guidance for the industrial production of electrostatic field. diet peoples people s risen now equipment cost maintenance consumption time operation environment nonthermal non thermal activity paper described proposed

Vibrio harveyi is considered as a causative agent of the systemic disease, vibriosis, which occurs in many biological fields. The effects of temperatures (12.9-27.1 ºC) and water activity (NaCl% 0.6%-3.4%) on V. harveyi were investigated. The behavior and growth characteristics of V. harveyi was studied and modeled. Growth curves were fitted by using Gompertz and Baranyi models, and the Baranyi model showed a better fittness. Then, the maximum growth rates (µmax) and lag phase durations (LPD, λ) obtained from both Gompertz and Baranyi model were modeled as a combination function of temperature and water activity using the response surface and Arrhenius-Davey models for secondary model. The value of r², MSE, bias and accuracy factor suggest Baranyi model has better fitness than Gompertz model. Furthermore, validation of the developed models with independent data from ComBase also shown better interrelationship between observed and predicted growth parameter when using Baranyi model.