A dielectric barrier discharge (DBD) plasma reactor was investigated for the inactivation of Ralstonia Solanacearum which causes bacterial wilt in aquiculture. The DBD plasma reactor of this study was divided into power supply unit, gas supply unit and plasma reactor. The plasma reactor consisted of a quartz dielectric tube, discharge electrode (inner) and ground electrode (outer). The experimental results showed that the optimum 1st voltage, 2nd voltage, air flow rate and pH were for 100 V (1st voltage), 15 kV (2nd voltage), 4 L/min, and pH 3, respectively. At a low 1st voltage, shoulder and tailing off phenomena was observed. The shoulder phenomenon was decreased as the increase of 1st voltage. R. Solanacearum disinfection in the lower air flow rate was showed shoulder and tailing off phenomenon because the active species generated less. Under optimum condition, shoulder and tailing off phenomenon was reduced. When the 2nd voltage was less than 7.5 kV, tailing off phenomenon was observed and this was not vanishes even though the increase of the disinfection time. The inactivation efficiency increased as the increase of air flow rate, however, the efficiency decreased when the air flow rate was above 4 L/min. R. Solanacearum disinfection at pH 3 showed somewhat higher than in pH 11. The pH effect of R. Solanacearum deactivation is less than the impact on other factor.

The application of disinfection models on the plasma process was investigated. Nine empirical models were used to find an optimum model. The variation of parameters in model according to the operating conditions (first voltage, second voltage, air flow rate, pH) were investigated in order to explain the disinfection model. In this experiment, the DBD (dielectric barrier discharge) plasma reactor was used to inactivate Ralstonia Solanacearum which cause wilt in tomato plantation. Optimum disinfection models were chosen among the nine models by the application of statistical SSE (sum of squared error), RMSE (root mean sum of squared error), r2 values on the experimental data using the GInaFiT software in Microsoft Excel. The optimum model was shown as Weibull+talil model followed by Log-linear+ Shoulder+Tail model. Two models were applied to the experimental data according to the variation of the operating conditions. In Weibull+talil model, Log10(No), Log10(Nres), δ and p values were examined. And in Log-linear+Shoulder+Tail model, the Log10(No), Log10(Nres), kmax, Sl values were calculated and examined.