Effects of Drying,Packaging, and Temperature on the Quality of Fried Onion Slices

Abstract: Onion is used widely as a condiment for meat and other types of food in Iran. Because of the high sensitivity of this product to storage conditions and having not enough storage under controlled atmosphere (CA), the effects of drying method, packaging, and temperature during storage on thin slices of fried red Azershahr variety onion were investigated. To prepare this processed food with excellent organoleptic properties and useful in the food service industry onions were sliced (2 mm), deep-fried with corn frying oil in a batch fryer at 150 °C, and dried to a water content of 3-4% in a hot-air dryer at 70 °C for 24 h and a microwave system. Samples were packed in aluminum foil, which was purged by nitrogen gas, and cellophane-sealed with thermal sewing. Then these samples were kept for one year at laboratory temperature and in a freezer at −18 °C. During the storage time the moisture content, peroxide value, vitamin C content, total microbial count (TMC), and organoleptic characteristics of the samples were analyzed every 2 mo. The results of microbial analyses indicated that after 6 mo all of the samples had higher TMCs than the permission limits so the expiration date was set before that. The moisture contents and peroxide values showed a noticeable increase, probably due to seal failure, whereas vitamin C decreased up to 66% during storage. The loss of sensory properties was parallel to the microbial and chemical results. The findings revealed that the best sample was oven-dried, packed in aluminum foil under inert gas, and kept in a freezer (OAF) up to 6 mo.     

NOMA performance enhancement-based imperfect SIC minimization using a novel user pairing scenario involving three users in each pair

Wireless Networks - Due to the non-uniform distribution of users in a cellular area, there are users with similar channel conditions. In non-orthogonal multiple access (NOMA) systems, a small...     

Influence of milling time on the structural and exchange bias of CoO and Co–Co oxide nanocomposite systems

This study aimed to investigate the effect of milling time on the structural and exchange bias properties of two exchange-coupled nanocomposite systems that were prepared by mechanical milling. The first system consists of an antiferromagnet (CoO), named CoO-series and the second one consists of a mixture of a ferromagnet with an antiferromagnet (10 wt% Co + CoO), called MIX-series and both systems were milled for various times. Upon field cooling, going through low temperature (5 K), hysteresis loop shifts, coercivity enhancements, and saturation magnetization reductions were observed as milling time increases. Noticeable enhancements of exchange bias (270 Oe) and coercivity (1039 Oe) of the CoO-series after 10 h of milling, in comparison with those of unmilled ones (16 Oe) and (136 Oe) respectively, showed that the main structural changes occurred at the first milling hours. Introduction of large structural defects, the formation of cobalt and crystallite size reduction, ensuing from milling, can be the causes of an increase in exchange bias and coercivity. On the other hand, ferromagnet-antiferromagnet exchange coupling induces by milling is another origin for exchange bias. The results show that ferromagnet-antiferromagnet ratio and/or crystallite sizes play key roles in exchange bias enhancement. So that milled CoO-series with lower Co content in comparison with that of MIX-series and finer crystallites have considerable higher exchange bias.     

Brushless DC motor drives supplied by PV power system based on Z-source inverter and FL-IC MPPT controller

This paper discusses operation performance of a water pumping system consist of a brushless dc (BLDC) motor coupled a centrifugal pump and accompanying a Z-source inverter (ZSI) fed by a photovoltaic (PV) array, to be improved. Despite conventional double-stage power converters, this paper proposes utilizing a single-stage ZSI to extract the maximum power of the PV array and supply the BLDC motor simultaneously. Utilizing the ZSI provides some inherent advantages such as high efficiency and low cost, which is very promising for PV systems due to its novel voltage buck/boost capability. In addition, in order to precisely perform the maximum power point tracking (MPPT) of the PV array the fuzzy logic-incremental conductance (FL-IC) MPPT scheme is proposed. The proposed FL-IC MPPT scheme provides enough modification to the conventional IC method to enjoy an appropriate variable step size MPPT control signal for the ZSI. Moreover, direct torque control (DTC) is found more effective in comparison with hysteresis current control with current shaping to drive the BLDC motor, because it benefits from faster torque response, reduced torque ripple, less sensitivity to parameters variations, and simple implementation. In the mean time, due to the frequently variations of the PV power generation; delivered mechanical power to the centrifugal pump is variable. Thus, the BLDC motor should be driven with variable reference speed. In order to improve the speed transient response of the BLDC motor and enhance the energy saving aspect of the system, it should enjoy a high quality dynamic response characteristic. Therefore, to realize these purposes, particle swarm optimization (PSO) has been proposed to regulate the proportional-integral-derivative (PID) parameters of the BLDC motor speed controller. The system configuration, operation principle and control methods are presented in detail. Finally, the proposed system was simulated in different operation conditions of the PV array by computer simulations and the effectiveness of the proposed control strategies has been validated by comparative studies and simulation results.     

A DEA approach for comparing solution efficiency in U-line balancing problem using goal programming

Line balancing problem plays an important role in the decision making process to increase efficiency and productivity. Recently, U-shaped layout in many production lines has replaced the traditional straight line layout using just-in-time concept. Here, we propose a model, using multi-objective decision making approach to the U-shaped line balancing problem, to offer enhanced decision maker flexibility, by allowing for conflicting goals. The assembly line operation efficiency is the most significant aim in our study, and this efficiency relates to management of resources and the solution of line balancing problem. First, the U-shaped line balancing problem is solved considering the model's goals. Then, the index function of assembly line balancing is determined and the efficiencies of the optimal solution outputs are evaluated using data envelopment analysis (DEA). Finally, the discrimination weakness and distribution of illogical weight in simple DEA models are resolved using a mixed method.     

Low-cost optical approach for noncontact predicting moisture content of apple slices during hot air drying

Absorption and scattering properties of product change as moisture content is reduced, but it has not been investigated how these changes are correlated. This study was aimed to measure and test the feasibility of using optical properties in predicting the moisture content of sliced apple samples during hot air drying. In this investigation, the noninvasive backscattering laser imaging technique at three wavelengths (650, 780, and 880?nm) and Farrell’s diffusion theory were used to determine absorption and reduced scattering coefficients. Artificial neural network model was applied to correlate the optical coefficients and moisture content of samples. The highest correlation between above-mentioned parameters was found at 780?nm. The best moisture content prediction result was obtained when absorption and reduced scattering coefficients were combined at three wavelengths with R_p?=?0.984. The results suggested that this method can be effectively used to predict the moisture content and control the drying process.     

Investigation of Phase Formation and Magnetic Properties of Mn Ferrite Nanoparticles Prepared via Low-Power Ultrasonic Assisted Co-precipitation Method

MnFe₂O₄ nanoparticles were synthesized by low-power ultrasonic assisted co-precipitation at two different aging times. In order to investigate the effect of ultrasonic waves on phase formation and magnetic properties of Mn ferrite nanoparticles, two other samples were synthesized in the same conditions but in the absence of ultrasonic waves. Structural and morphological properties of the nanoparticles were examined by using X-ray diffraction (XRD) and scanning electron microscope (SEM). The presence of ultrasonic waves through the reaction medium led to form a single phase of MnFe₂O₄ at 15 min aging time, while this time was insufficient to form a single phase in the absence of ultrasonic waves. At 60 min aging time, the crystallinity of the sample synthesized in the presence of ultrasonic waves was greater and its particle size was bigger than those of the sample synthesized in the absence of ultrasonic waves. The observed results were evaluated from physico-chemical point of view. It was concluded that the ultrasonic waves led to a slower nucleation rate. The magnetic properties of the nanoparticles were examined by permeameter and Faraday-balance equipment. The saturation magnetization of the sample prepared in the presence of ultrasonic waves was enhanced and its Curie temperature was reduced.     

Modeling of glycolysis of flexible polyurethane foam wastes by artificial neural network methodology

The glycolysis process as a useful approach to recycling flexible polyurethane foam wastes is modeled in this work. To obtain high quality recycled polyol, the effects of influential processing and material parameters, i.e. process time, process temperature, catalyst‐to‐solvent (Cat/Sol) and solvent‐to‐foam (Sol/Foam) ratios, on the efficiency of the glycolysis reaction were investigated individually and simultaneously. For the continuous prediction of process behavior and interactive effects of parameters, an artificial neural network (ANN) model as an efficient statistical‐mathematical method has been developed. The results of modeling for the criteria that determine the glycolysis process efficiency including the hydroxyl value of the recycled polyol and isocyanate functional group conversion prove that the adopted ANN model successfully anticipates the recycling process responses over the whole range of experimental conditions. The Cat/Sol ratio showed the strongest influence on the quality of the recycled polyol among the studied parameters, where the minimum hydroxyl value was obtained at a medium amount of the assigned ratio. For the consumed polyurethane foam, a higher value of this ratio led to an increase in the hydroxyl value and isocyanate conversion. © 2015 Society of Chemical Industry