Mahdi Kashani nejad Articles List

List of Articles Mahdi Kashani nejad

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1 - Evaluation of Viscoelastic Properties of Rich Sponge Cake with Apples Powder
F. Salehi M. Kashaninejad

Introduction: Apple is a rich source of fiber and polyphenols. To investigate the effect of replacing apple powder with wheat flour on viscoelastic properties of sponge cake, stress relaxation test was performed. Materials and Methods: First apple was dried in optimal c More

Introduction: Apple is a rich source of fiber and polyphenols. To investigate the effect of replacing apple powder with wheat flour on viscoelastic properties of sponge cake, stress relaxation test was performed. Materials and Methods: First apple was dried in optimal conditions and milled, and then apple powder was used for enrichment of sponge cake at five levels of 0, 5, 10, 15 and 20 % (w/w) as substitute of wheat flour in the cake formulation. After preparing the samples, stress relaxation test was carried out using a texture analyzer during storage time and coefficients of the Peleg-Normand and the extended Maxwell models were calculated. Results: The results showed that by increasing the substitution of apple powder and storage time, the initial force and balance force values were increased. The parameters of Peleg-Normand model include k1 and k2 decreased with time that indicated a reduced elasticity of the cake with the time. The cakes showed solid viscoelastic behavior and by increasing the replacement, total reduced forces (F1+F2+F3) of generalized Maxwell model are increased which indicates that the elasticity is reduced. Conclusion: The results of stress relaxation modeling of experimental data with Peleg-Normand and the extended Maxwell models showed that the extended Maxwell model is more efficient to evaluate the viscoelastic properties of rich sponge cake with apples powder. Manuscript profile
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2 - Modeling of Soybean Snack Roasting by Infrared Heating Using Artificial Neural Network (ANN)
H. Bagheri M. Kashani Nejad

ntroduction: Soybean is recognized as a good source of essential nutrients including protein, oil and several bioactive compounds and soybean has the potential to be used as snack and roasted nut, but most significant factor responsible for such limitation is probably c More

ntroduction: Soybean is recognized as a good source of essential nutrients including protein, oil and several bioactive compounds and soybean has the potential to be used as snack and roasted nut, but most significant factor responsible for such limitation is probably considered as the characteristic flavor of soybean. Raw soybean has beany, bitter and astringent flavors. Therefore to improve its consumption, the particular flavor of raw soybean must be removed. Roasting might be considered as one of the best methods for this object. Materials and Methods: In this study, the infrared roaster is designed and soybean has been prepared and roasted according to the experimental condition. In this work, an artificial neural network model was developed for modeling of moisture content of soybean snack during infrared roasting. In order to do this, infrared lamp powers of 250, 350 and 450 W, distance between lamp and sample of 4, 7 and 10 cm and roasting time of 30 min were considered as the inputs and the amount of moisture ratio (MR) was estimated as the output. In addition, three different mathematical models were fitted to the experimental data and compared with the ANN model. Results: Based on these results, artificial neural network model for MR with one hidden layer, Sigmoid function as the transfer function, Levenberg-Marquardt method as the learning rule, 4 hidden neurons, 55% for training subset and 25 and 20 percent for each of validation and test subsets respectively had the best over fitting. The determination coefficient (R2) and root mean square error (RMSE) computed for the ANN model were 0.9992 and 0.01099and for the best mathematical model (Two term model) were 0.9776 and 0.02758, respectively. Conclusion: It was concluded that the artificial neural network model satisfied the work better than the mathematical model concerned with soybean snack roasting. Manuscript profile
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3 - Optimization of Hot Air Roasting of Peanut Kernels Using Response Surface Methodology
H. Bagheri M. Kashainejad M. Aalami A. M. Ziaiifar

Introduction: Roasting is a high temperature short time (HTST) heat treatment process and enhances the flavor of product and improves the textural and organoleptic properties of the nuts. Materials and Methods: In this study, a hot-air roasting process for the productio More

Introduction: Roasting is a high temperature short time (HTST) heat treatment process and enhances the flavor of product and improves the textural and organoleptic properties of the nuts. Materials and Methods: In this study, a hot-air roasting process for the production of peanut snack was optimized by response surface methodology (RSM) over a range of air temperatures (140–180°C) for various times (10-30 min). The color parameters including lightness (L*), redness (a*), yellowness (b*) and total color differences (ΔE), textural characteristics (hardness and compressive energy), sensory properties, moisture content of the peanuts and energy consumption were used as response parameters to develop predictive models and optimize the roasting process.Results: The results showed that by increasing the by temperature and time of roasting, the L*, b*, moisture content, hardness and compressive energy were decreased and ΔE* and energy consumption were increased. The result of RSM analysis showed that quality parameters could be used to control the roasting of peanut kernels in a hot-air roaster. In order to obtain the desired quality parameter, the optimum roasting for production of peanut snack was determined at 162°C for 29 min. Conclusion: This study revealed that RSM could be used to develop adequate prediction models for describing color and texture changes in peanut kernels during hot-air roasting. The changes in the quality parameters were adequately described by quadratic model. Successful optimization for the peanut kernels roasting process can also be made using desirability functions in RSM. Manuscript profile
Open Access Article
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4 - Modeling of Roasting Process of Peanut Kernels using Combined Infrared-Hot Air Method
H. Bagheri M. Kashaninejad A.M. Ziaiifar M. Alami

Introduction: Roasting is one of the common methods of nuts processing and its purpose is to increase the total acceptability of products. The conventional roasting using hot air oven has drawbacks of low production rate, poor product quality, and high energy cost. Ther More

Introduction: Roasting is one of the common methods of nuts processing and its purpose is to increase the total acceptability of products. The conventional roasting using hot air oven has drawbacks of low production rate, poor product quality, and high energy cost. Therefore, there is a need to develop new processing methods that can produce roasted products. The combined infrared-hot air system was explored as a new roasting method for peanut kernels. Materials and Methods: In this study the combination of infrared (IR) and hot-air was explored for roasting of peanut kernels and the effects of processing conditions including hot air temperature (100 and 120 °C) and infrared power (130 W, 165 W and 200 W) on different characteristics of kernels (moisture content and energy consumption) were investigated. Roasting kinetics of peanut kernels were explained and compared using five mathematical models. In order to determine the coefficients of these models, non-linear regression analysis was applied. Results: According to the statistical analysis, two-term and logarithmic models showed the best fitted results. These models have acceptable R2 and adj R2 and low RMSE under all roasting conditions. Effective diffusivity coefficient of peanut kernels varied between 1. 915× 10-7 - 6.054× 10-7 m2/s. The value of Deff increased by increasing temperature and IR power. The results also showed that by increasing temperature and IR power, the moisture content (%, db.) of samples decreased and energy consumption increased. Conclusion: This study demonstrated that combination of infrared and hot-air roasting can produce high-quality roasted peanuts with lower energy cost; therefore it could be considered as a new technology for the peanut roasting industry. Manuscript profile

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List of Articles Mahdi Kashani nejad