Statistical modeling of the inactivation of spoilage microorganisms during ohmic heating of sour orange juice

Abstract

To reduce food pathogens, increase shelf life of fruit juices and maintaining bioactive properties preservation technologies as ohmic heating have gained interest. This study sought to investigate the effect of four ohmic resistance variables, temperature (Temp), voltage (V), current (AMP) and electric conductivity (EC), on the population of two yeasts, an ascospore and three fermentative bacteria, by inoculation into sour orange juice. The incidence of the variables was evaluated through different regression models. The results of the simple linear regression (SLR) indicated that Temp, AMP and EC had a significant negative effect on the population of all microorganisms, while V had no effect on the population of any microorganism. The results of the stepwise linear regression (SWLR) showed that, for each microorganism, the variables Temp and AMP were considered to be significant being the only ones included in the model. Temperature had the highest negative effect on the population of each microorganism, explaining more than 87% of the variability of the microorganism. A full quadratic multiple linear regression (FQMLR) model fitted to the dataset such that all significant variables and interactions between variables were considered. Diverse statistical analysis confirmed the goodness of the model.