Impact of apple processing modes on extracted juice quality: Pressing assisted by pulsed electric fields

The purpose of this study was to compare the effects of pulsed electric field (PEF) on apple juice characteristics (turbidity, polyphenolic content and antioxidant capacities). The pressing was used as a standard method for juice extraction. Experiments were carried out at a constant pressure (P = 3 bar) using a laboratory press cell. Two different methods for PEF application at 400 V/cm were investigated (PEF treatment of whole samples before cutting and PEF treatment of apple slices after cutting). PEF treatment resulted in increase of the juice yield from 44 g/100 g apple (untreated samples) to 58 g/100 g apple (treatment of whole apples) and 64 g/100 g apple (treatment of slices) after 30 min of pressing. The analysis of pH and conductivity showed no significant difference between untreated and PEF-treated samples. However, the total soluble matter content of juice increased after PEF treatment. The obtained turbidity and transmittance data evidence a noticeable improvement of juice clarity for PEF-treated samples. The PEF pre-treatment was accompanied by an increase of the content of polyphenols and intensification of the antioxidant capacities of juice. Most of these effects (juice clarity and content of antioxidants) were more pronounced for the whole treated apples as compared to untreated apples and PEF-treated apple slices. The evolution of apple browning before and after PEF treatment was more pronounced for whole samples. PEF treatment accelerates browning. The obtained data can contribute to the determination of an optimum time for PEF application. The results evidence that PEF-enhanced expression is promising for production of higher quality juices. PEF treatment of whole apples reduces the energy consumption and is advantageous for industrial applications as compared to the treatment of apple slices. PEF combined with pressing can become a good alternative to traditional process.     

On a Hopfield Net Arising in the Modelling and Control of Over-Saturated Signalized Intersections

We present a neural method – based on the Hopfield net – for the modelling and control of over-saturated signalized intersections. The problem is to look, in real-time, for lights signal setting which minimize a given traffic criterion such as waiting time. The use of the Hopfield model is straightforward justified by its optimization capabilities, especially its fast time computing (by its own dynamic), which is of a great interest in real-time problems like the traffic control one. The original Hopfield algorithm is modified to take into account proper constraints of the traffic problem. This approach is illustrated by numerical examples of traffic conditions generated by a simulator. We extend the method to urban nets of several interconnected intersections.