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    List of Articles تکتم محمدی مقدم


  • Article

    1 - Application of Artificial Neural Networks (ANN) and Image Processing for Prediction of Gravimetrical Properties of Roasted Pistachio Nuts and Kernels
    Journal of Nuts , Issue 5 , Year , Spring 2019
    Roasting is among the most common methods of nut processing causing physical and chemical changes and ultimately increasing overall acceptance of the product. In this research,the effects of temperature (90,120 ,and 150°C),time (20,35 ,and 50 min) ,and roasting air More
    Roasting is among the most common methods of nut processing causing physical and chemical changes and ultimately increasing overall acceptance of the product. In this research,the effects of temperature (90,120 ,and 150°C),time (20,35 ,and 50 min) ,and roasting air velocity (0.5,1.5 ,and 2.5 m/s) on gravimetrical properties of pistachio nuts and kernels including unit mass,true density,ounce,uniformity, size and shell percentage were investigated. Gravitational characteristics were measured by experimental and image processing methods. Artificial neural network method was used to predict the relationship between characteristics obtained from experiments and image processing. Volume,unit mass and true density for pistachio nuts were in a range of 1.06 – 1.24 mm3, 0.92 – 1.08 g and 866.01 - 871.35 kg / m3, respectively and they were0.61-0.77 mm3, 0.53 - 0.67 g and 862.21 - 871.29 kg / m3 for pistachio kernels. Number of pistachio nuts was found to be 29-32 per ounce and 102-109 per 100 grams. Uniformity of pistachios was in a range of 1.24-1.50 and their average kernel ratio was higher than 50%. Thus, it can be said that, they were of superior quality. Shell percentage of pistachio nuts was in a range of 38.24–41.98%. Results of the study revealed that ,artificial neural network could properly predict volume and mass of pistachio nuts, but, it had not appropriate ability to predict apparent density. Manuscript profile

  • Article

    2 - Application of Artificial Neural Networks (ANN) and Image Processing for Prediction of the Geometrical Properties of Roasted Pistachio Nuts and Kernels
    Journal of Nuts , Issue 2 , Year , Winter 2019
    Roasting is the most common way for pistachio nuts processing, and the purpose of that was to increase the products total acceptability. Purpose of this study was to investigate the effect of temperature (90, 120 and 150°C), time (20, 35 and 50 min), and roasting ai More
    Roasting is the most common way for pistachio nuts processing, and the purpose of that was to increase the products total acceptability. Purpose of this study was to investigate the effect of temperature (90, 120 and 150°C), time (20, 35 and 50 min), and roasting air velocity (0.5, 1.5 and 2.5 m/s) on geometrical attributes of pistachio nuts and kernels including principle dimensions, shape factor, sphericity, surface area, shell splitting, and true volume. An experimental method and image processing were used in order to measure the geometrical properties. The Artificial Neural Networks (ANN) method was used for predicting the correlation between experimental and image properties. The results showed that the time, temperature, and roasting air velocity didn’t have significant effect on principle dimensions, shape factor, sphericity, surface area, shell splitting, and true volume. In all cases, the shape factor of pistachio nuts and kernels were more than 1.25. So, pistachio samples had ellipsoid shape. Pistachio kernels had more similarity to ellipsoid shape in comparison with pistachio nuts. The results revealed that ANN could predict the length, width, height, shape factor, sphericity, shell splitting, surface area, and true volume of roasted pistachio nuts and kernels. Manuscript profile