---

In all societies and countries, in order to plan to provide the required energy for various sectors, it is necessary to accurately predict the demand, type of energy carriers and energy supply method. Considering the importance of food industries in each country, in this study, modeling of required energy for food industries sector was investigated. Modeling of energy consumption was performed using artificial neural networks. In the first step, the input data to the model was calculated according to statistics, balance sheets and input method proposed in this paper. Two methods, namely multiple neural network and single neural network were tested and the results showed that multiple neural network has a higher accuracy. For each of the energy carriers (gasoline, kerosene, fuel oil, natural gas, electricity, gasoline and LPG) the best neural network was selected by taking the average of 20 times per program for each network characteristic. Finally, the network was implemented in the form of final model using Simulink environment of MATLAB 7.0 software. Data analysis showed that daily consumption of natural gas in the industry is increasing, while the consumption of fuel oil and LPG is going to be decreased.

---

This study aimed to examine the effectiveness of combined microwave-ultrasonic pasteurization system on Escherichia coli and vitamin C content in sour cherry juice (SCJ). Based on the findings, microwave output power, ultrasound power, and ultrasonic exposure time as well as the microwave-induced temperature were the most effective factors in reducing E. coli and vitamin C content. In addition, the microwave-induced temperature and ultrasonic exposure time, as independent variables, were both effective on E. coli removal. At higher temperatures, the effectiveness of ultrasonic waves as well as cavitation intensity declined. However, their combined effect (ultrasound and temperature) was more significant than their individual effect. It was also found that any increase in ultrasound power, ultrasonic exposure time, and microwave output power led to a significant reduction in vitamin C content, while the ultrasound power was the most effective. On the basis of RSM modeling, the optimum processing condition was: 352.21W microwave output power, 49.94˚C temperature, 475.13W ultrasound power and 6 minutes of exposure time. On the basis of response surface methodology (RSM) modelling, the maximum vitamin C content was 142.5 mg per 100 mL with no remaining E. coli.