No abstract

This study investigated thin layer drying of squash seeds under semi fluidized and fluidized bed conditions with initial moisture content about 83. 99% (d.b.). An experimental fluidized bed dryer was also used in this study. Air temperature levels of 50, 60, 70 and 80°C were applied in drying samples. To estimate the drying kinetic of squash seed, seven mathematical models were used to fit the experimental data of thin layer drying. Among the applied models, Two-term model has the best performance to estimate the thin layer drying behavior of the squash seeds. Fick's second law in diffusion was used to determine the effective moisture diffusivity of squash seeds. The range of calculated values of effective moisture diffusivity for drying experiments were between 0.160×10 −9 and 0.551×10 −10 m 2 /s. Moisture diffusivity values decreased as the input air temperature decreased. Activation energy values were found to be between 31.94 and 34.49 kJ/mol for 50°C to 80°C, respectively. The specific energy consumption for squash seeds was calculated at the boundary of 0.783×10 6 and 2.303×10 6 kJ/kg. Increasing in drying air temperature in different bed conditions led to decrease in specific energy value. Results showed that applying the semi fluidized bed condition is more effective for convective drying of squash seeds. The aforesaid drying characteristics are useful to select the best operational point of fluidized bed dryer and to precise design of system.

A laboratory microwave convection dryer was used to dry the hawthorn fruit, applying microwave power in the range of 270–630 W, air temperature in the range of 40–70C and air velocity in the range of 0.4–1.6 m/s. Five empirical drying models for describing time dependence of the moisture ratio change were fitted to experimental data and model parameters in equations were determined by multiple regression analysis. Results showed that the Midilli et al. with R2 = 0.9983, χ2 = 0.0033 and RMSE = 0.0485 had the best performance (among the five models tested) in predicting the moisture. The effective moisture diffusivity, which ranged between 9.29 × 10−10 and 8.81 × 10−9 m2/s, increased with the increase in microwave power and air temperature. The activation energy of samples was found between 12.25 and 27.90 kJ/mol. Maximum shrinkage (64.39%) was achieved at the air temperature of 70C, microwave power of 630 W and air velocity of 0.4 m/s. Practical Applications Hawthorn has been considered as an important traditional herbal medicine due to its disease prevention effects. Advantages of microwave convection drying include short processing time, high mass transfer coefficients, low energy consumption and high quality. As heat and mass transfer and quality changes during drying of hawthorn with microwave‐convective method are not described in the literature, it is of importance to gather such data and compare them to find the optimum point of the process. In this study, drying kinetics of hawthorn slices at different air temperatures and microwave powers were studied. Furthermore, simple models for the simulation of drying process, taking into account the fruit shrinkage, were proposed. The results of this study will be helpful in the technological application of microwave‐hot air‐drying for hawthorn preservation.

Golpour I., Parian J.A., Chayjan R.A. (2014): Identification and classification of bulk paddy, brown, and white rice cultivars with colour features extraction using image analysis and neural network. Czech J. Food Sci., 32: 280-287.We identify five rice cultivars by mean of developing an image processing algorithm. After preprocessing operations, 36 colour features in RGB, HSI, HSV spaces were extracted from the images. These 36 colour features were used as inputs in back propagation neural network. The feature selection operations were performed using STEPDISC analysis method. The mean classification accuracy with 36 features for paddy, brown and white rice cultivars acquired 93.3, 98.8, and 100%, respectively. After the feature selection to classify paddy cultivars, 13 features were selected for this study. The highest mean classification accuracy (96.66%) was achieved with 13 features. With brown and white rice, 20 and 25 features acquired the highest mean classification accuracy (100%, for both of them). The optimised neural networks with two hidden layers and 36-6-5-5, 36-9-6-5, 36-6-6-5 topologies were obtained for the classification of paddy, brown, and white rice cultivars, respectively. These structures of neural network had the highest mean classification accuracy for bulk paddy, brown and white rice identification (98.8, 100, and 100%, respectively).

No abstract

Edible coatings can provide an alternative to enlarge fresh fruits' postharvest life. The effect of methylcellulose edible coating on some qualitative, chemical, physical and mechanical properties of strawberries was investigated. Coatings were used directly on the fruit surface then stored at 4C for 11 days. The results showed that no significant differences were statistically observed in total acidity, anthocyanin and antioxidant activity compared with the control ones. In contrast, the edible coating significantly prevents weight loss and decay and also, keep a small amount of fruit sugar, maintained the firmness of the strawberries, improved its quality and storage features. The cellulose coating had significant effects on surface color parameters. The color of the coated fruits was darker and clearly had less redness (lower L*, C* and H values). PRACTICAL APPLICATIONSThe maintenance of the quality of fresh produce is still a major challenge for the consumers. The most important quality attributes contributing to the marketability of fresh fruit include appearance, color, texture, flavor, nutritional value and microbial safety. Strawberry fruits should be firm but not crunchy. Decreased quality during postharvest handling is most often associated with water loss and decay. The postharvest life of strawberries can be extended by coating technique combined with refrigeration. Protective edible coatings are applied to fruits and vegetables as part of the postharvest treatment of fresh fruits and vegetables as a method of preservation. The purpose is to extend the shelf life of strawberries and to provide a barrier against hazards.

No abstract

In this research, a comparative approach was carried out between artificial neural networks (ANNs) and response surface methodology (RSM) to optimize the drying parameters during infrared-convective drying of white mulberry. The drying experiments were performed at different air temperatures (40, 55 and 70 °C), air velocities (0.4. 1 and 1.6 m/s) and infrared radiation power (500, 1000 and 1500 W). RSM focuses on maximization of effective moisture diffusivity ( eff D ) and minimization of specific energy consumption ( SEC ) in the drying process. The optimized conditions were encountered for the air temperature of 70 °C, the air velocity of 0.4 m/s and the infrared power level of 1464.57 W. The optimum values of eff D and SEC were 1.77×10 -9 m 2 /s and 166.554 MJ/kg, respectively, with the desirability of 0.9670. Based on the statistical indices, the results showed that the Feed and Cascade Forward Back Propagation neural systems with application of Levenberg-Marquardt training algorithm and topologies of 3-20-20-1 and 3-10-10-1 were the best neural models to predict eff D and SEC , respectively.