جستجوی مقالات مرتبط با کلیدواژه « Infrared Dryer » در نشریات گروه « صنایع غذایی »

In this research, the effect of ultrasound treatment at different powers and temperatures on the drying process of cornelian cherry by infrared dryer was investigated and modeled. The effect of the applied power by the ultrasonic device at three levels of 0, 75 and 150 W and the effect of the ultrasonic treatment temperature at three levels of 20, 40 and 60 °C on the mass transfer rate and the effective moisture diffusivity coefficient during the drying process of cornelian cherry were investigated. The results of this research showed that ultrasonic pretreatment before drying cornelian cherry by the infrared dryer, by creating microscopic channels on the product surface due to the cavitation phenomenon, makes it easier for moisture to exit from the product and thus reduces the drying time. By increasing the ultrasonic power from 0 to 150 W, the average drying time of cornelian cherry decreased from 73.2 minutes to 51.4 minutes. By increasing the treatment temperature from 20 to 60 °C, the average drying time of cornelian cherry decreased from 69.7 minutes to 55.7 minutes. The effect of power and time of ultrasound treatment on the effective moisture diffusivity coefficient changes of cornelian cherry was investigated and the results showed that with the increase in the power and temperature of the ultrasonic device, the values of this coefficient increase. By increasing the sonication power from 0 to 150 W, it was observed that the effective moisture diffusivity coefficient increased from 6.63×10-9 m2s-1 to 10.11×10-9 m2s-1. The average effective moisture diffusivity coefficient of cornelian cherry treated at temperatures of 20, 40 and 60 °C were 7.26×10-9 m2s-1, 8.10×10-9 m2s-1, and 9.45×10-9 m2s-1, respectively. In order to investigate the drying kinetics of cornelian cherry, mathematical models were fitted to the experimental data.

Coating the fruits using edible gums increases the appearance quality, improves the color and reduces their shrinkage at the end of the drying process. The purpose of this study was to investigate the effect of coating with wild sage seed, basil seed and xanthan gums on the appearance characteristics of dried quince slices in the infrared system. In this study, quince slices with a thickness of 0.5 cm were coated using wild sage seed, basil seed and xanthan gums (concentration of 1%) and then placed in an infrared dryer and the effects of radiation power (250 and 375 W) on the appearance characteristics were examined. Also, for modeling the color change index, the Power, Quadratic, Gompertz, Logistic, Richards, MMF, and Weibull models were used. Color indexes including lightness, redness, yellowness and color changes as well as changes in the samples area during drying time were examined. The calculated lightness index for the drying process of quince samples showed that the coated samples with wild sage seed gum were brighter. In terms of color change index, coated quince slices with wild sage seed gum showed the lowest color changes during drying time and the average values of this index for the uncoated sample, coated with wild sage seed, basil seed and xanthan gums were equal to 35.09, 20.20, 43.40 and 28.33, respectively (250 W). For modeling the color change index, the MMF model had less error than the others models. The results showed that the coating with wild sage seed gum maintained the appearance of the dried product and also the least shrinkage in the drying duration and at different radiation powers were observed in these coated samples.

Dried fruits are one of the most important non-oil exports and the efforts should be made to grow the economy of the country by increasing their exports to world markets. Meanwhile, quince juice contains various minerals including iron, phosphorus, calcium, potassium and rich in vitamins such as vitamins A, C and B vitamins. Drying of food is one of the ways to keep its quality and increase its shelflife. During this process, the removal of moisture through the simultaneous transfer of heat and mass occurs. By transferring heat from the environment to the foodstuff, the heat energy evaporates the surface moisture. The drying process has a great impact on the product. In recent years, new and innovative techniques have been considered that increase the drying rate and maintain the quality of the product and infrared drying is one of these novel techniques.. Infrared systems are emitting electromagnetic waves with a wavelength of 700 nm to 1 mm. The advantage of using infrared is to minimize waste and prevent product quality loss due to reduced drying time can be mentioned. The need to predict product quality in each process makes it necesary to model and discover the relationship between factors that can affect the final quality of the product. Artificial neural networks have been considered as a meta-innovative algorithm for modeling and prediction, which can be favored by the ability of these networks to model and predict processes The complexity and discovery of non-random fluctuations in data and the ability to discover the interactions between variables, economical savings in the use and disconnection of classical model abusive constraints (Togrul et al., 2004), the ability to reduce The effect of non-effective variables on the model by setting internal parameters is the ability to predict the desired parameter variations with minimum parameters (Bowers et al., 2000).

In this research, quince fruit (Variety of Isfahan) was purchased as the premium product of Isfahan Gardens and was kept at 0°C in the cold room prior to further experiments. The fruits were removed from the refrigerator one hour before processing and exposed to ambient temperature. After washing, surface moisture was removed by moisture absorbent paper and turned into slices with a constant thickness of 4 mm. The specimens were subjected to pre-treatment with an osmotic solution (vacuum for 70 minutes at a temperature of 40 ° C for 5 hours). For drying the samples, an infrared convective dryer with three voltages (800.400 and 1200 watts) and a constant speed of 0.5 m / s was used. In this way, the samples were placed under infrared lamps on a plate made from a grid and the weight of the samples was measured in a scale of 10 minutes by means of a scale and recorded on the computer. In order to achieve stable conditions in the system, the dryer was switched on 30 minutes before the process. The distance between the samples and the infrared lamp was fixed in all treatments at 16 cm. The drying process continued to reach a moisture content of 0.22 basis. To perform a puncture tests, quince slices were used in a Brookfield-based American LFRA-4500 tissue analysis device. In order to model these parameters in the drying process, the results of examining the quality of the samples, including the firmness of the tissue as well as the drying time, were used as network outputs. The power, concentration and pressure parameters were considered as network inputs. In this research, a multilayer perceptron network (MLP) was used. Due to its simplicity and high precision, this model has a great application in modeling the drying of agricultural products. Many functions in transmitting numbers from the previous layer to the next layer may be used (Tripathy et al., 2008).

The results indicated that the stiffness of the tissue is reduced in vacuum conditions with increased power. So, the least amount of stiffness was related to osmotic sample dried at 1200 watts. By increasing the infrared power, the stiffness of the tissue decreases, the reason for this is probably the volume increase phenomenon that occurs during the rapid evaporation of moisture through infrared rays from inside the tissue. The results showed that at the start of the drying process, due to the high moisture content of the product, the moisture loss rate is high. Gradually, with the advent of time and reduced initial moisture content, the rate of moisture reduction naturally decreases. At lower power, the drying time is longer and with increasing power, the drying time decreases due to the increase of the thermal gradient inside the product and consequently the increase in the rate of evaporation of the moisture content of the product. The results of this study showed that the neural artificial network, as a powerful tool, can estimate the stiffness parameters of the tissue and the drying time with high precision. The most suitable neural network structure to predict these parameters with a 3-7-2 topology along with logarithmic activation functions with a total explanation coefficient above 0.9923 represent the best results. Also, by increasing the drying capacity and using osmotic dehydration, the drying time and the stiffness of the tissue samples is decreased.