Optimization of Closed-Cycle Fluidized Bed Drying of Sesame Seeds Using Response Surface Methodology and Genetic Algorithms

Our aim was to evaluate the qualitative properties of kiwifruits produced by refractance window (RW) as a novel drying method. The effects of slice thicknesses (0.8, 1.6 and 2.4 mm) and drying temperatures (80, 90 and 100C) on drying duration as well as qualitative parameters of dried samples including textural hardness, color, rehydration index and organoleptic properties were investigated. The required time to reach the final moisture content was considerably lower in RW method compared with oven drying, which was maximally 140 min lower for slice thickness of 2.4 mm at 100C. Generally, ΔE values and rehydration ratios of oven-dried kiwifruits were higher and lower than RW-dried samples, respectively. The average scores given to each sensory property of oven-dried samples were between 1 and 3, whereas they were in the range of 4-5 for RW-dried kiwifruits, exhibiting more satisfactory situations for the latter samples. PRACTICAL APPLICATIONSIt is necessary to develop alternative drying methods that could guarantee quality retention and maximize financial productivity during the drying process. Refractance window is a novel drying technique utilizing circulating hot water to transfer thermal energy to a thinly spread liquid material placed on a conveyor belt. In this work, we have successfully utilized this technique for drying kiwifruits, and the results have been compared with conventional oven drying for the first time.

Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Comparing Quality Characteristics of Oven-Dried and Refractance Window-Dried Kiwifruits

Jafari

Azizi

Mirzaei

et al. 2015

“…Among different available drying methods, fluidized bed drying is a productive drying technique in the food industry and is considered as one of the most favorite drying methods to prepare completely and evenly dried food products (Momenzadeh et al 2011). Fluidized bed drying could be economically favorable if it could be equipped with a heat pump to save the energy usage for heating the drying air (Malekjani et al 2013;Hashemi Shahraki et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Mathematical, Fuzzy Logic and Artificial Neural Network Modeling Techniques to Predict Drying Kinetics of Onion

Jafari

Ganje

Dehnad

et al. 2015

Self Cite

In this study, the influence of drying temperature (40, 50, 60C) and airflow velocity (2 and 3 m/s) on drying onion was evaluated by a custom designed fluidized bed dryer equipped with a heat pump dehumidifier. A comparative study was performed among nonlinear regression techniques, fuzzy logic and artificial neural networks to estimate the dynamic drying behavior of onion. Among nine mathematical models, approximation of diffusion with R 2 = 0.9999 and root mean square error = 0.004157 showed the best fit with experimental data. Fuzzy logic tool in MATLAB with Mamdani model in the form of If-Then rules along with triangular membership function used for simulation, interpolation and obtaining a theoretical increase in experimental moisture ratios were used. Feedforwardbackpropagation neural system with application of Levenberg-Marquardt training algorithm, hyperbolic tangent sigmoid transfer function, training cycle of 1,000 epoch and 2-5-1 topology was determined as the best neural model in terms of statistical indices. PRACTICAL APPLICATIONSForecasting kinetics of food drying by application of precise mathematical and dynamic modeling techniques as well as preparing particular patterns for describing such drying behaviors of diverse food products seem unavoidable for processing factories to optimize the quality of their dried food products and reduce operational costs. For this purpose, in this study, we applied different temperatures and airflow velocities to dry onion by a custom designed fluidized bed dryer equipped with a heat pump dehumidifier, predicting its drying behavior by regression, fuzzy logic and artificial neural network techniques and comparing accuracy of those models. Also, this paper compares prediction patterns of drying onion by fluidized bed drying with those of other food products dried by various drying methods. The results of this study will be helpful for all researchers and producers who want to know more about the nuances of impacts of different fluidized bed drying variables on the patterns of heat and mass transfer in fruits and vegetables.

“…Response surface methodology (RSM) is a kind of mathematical-optimizing method that is use as an accurate, effective and simple tool for optimizing the experimental process (Samavati 2013;Rakshit et al 2015), and is widely used in food fields (Myers et al 2009;Hashemi Shahraki et al 2013, 2014aMashkour et al 2014). D-Optimal mixture design (DMD) is one of the RSM techniques used to optimize complex processes.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Ultrasound-Assisted Stabilization and Formulation of Almond Milk

Maghsoudlou

Alami

Mashkour

et al. 2015

Self Cite

Almond extract has unique nutritional properties and it can be used as a nutritive beverage. One of the most important problems in the formulation of almond milk is the physical stability of the final product. In this study, the response surface methodology was used to optimize ultrasound (US) treatment and the amount of modified starch, lecithin and agar with respect to physical stability besides other physical properties such as particle size, viscosity, Brix and color attributes. Our results showed that the US treatment had a significant effect on physical responses (p < 0.05). In order to formulate the final product, stabilized almond milk was formulated using a D-Optimal mixture design by considering sensory evaluation. This study suggests using 8.05 sugar, 0.55 stevia and 6.38% rose water to obtain the best formulation. Rheological properties of the formulated milk showed pseudoplastic behavior, and the power law model had the best fitness to the experimental data. PRACTICAL APPLICATIONSOne of the most important problems in formulation of the almond milk as a nutritive beverage is the physical stability of the final product. Ultrasonic treatment and addition of various stabilizers can be useful to improve the stabilization of almond milk. The ultrasound treatment and the amount of modified starch, lecithin and agar were optimized with respect to the physical properties using response surface methodology. The best values for the ultrasound time and the amount of lecithin, modified starch and agar were 4.9 min, 0.09, 1.31% and 0.15, respectively. A D-Optimal mixture design was used to optimize the industrial formulation of final beverage by considering sensory evaluation. This study suggests using 8.05 sugar, 0.55 stevia and 6.38% rose water to obtain the best formulation. Rheological properties of the formulated milk showed that pseudoplastic behavior and power law model had the best fitness to the experimental data.