Application of Artificial Neural Networks (ANN) and Image Processing for Prediction of Gravimetrical Properties of Roasted Pistachio Nuts and Kernels
Subject Areas : MicrobiologyToktam Mohammadi Moghaddam 1 , Mohammad Ali Razavi 2
1 - Department of Food Science and Technology, Neyshabur University Of Medical Sciences, Neyshabur, Iran
Department of Food Science and Technology, Ferdowsi University of Mashhad (FUM), POBox:91775-1163, Mashhad, Iran
2 - Department of Food Science and Technology, Ferdowsi University of Mashhad (FUM), POBox:91775-1163, Mashhad, Iran
Keywords: image processing, Density, Uniformity, ANN, Ounce,
Abstract :
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.
Donya-e-eqtesad (2017) http://donya-e-eqtesad.com/news/441571V
El Masry G, Radwan S, El Amir M, El Gamal R (2009) Investigating the effect of moisture content on some properties of peanut by aid of digital image analysis. Food and Bioproducts Processing. 273 - 281.
Ercisli S, Sayinci B, Kara M, Yildiz C, Ozturk I (2012) Determination of size and shape features of walnut (Juglans regia L.) cultivars using image processing. Scientia Horticulturae. 133(6), 47-55.
FAOSTAT, FAOSTAT Database Results, 2014. <http://faostat.fao.org/site/339/default.aspx>. (2017).
Goktas Seyhan F (2003) Effect of soaking on salting, moisture uptake of pistachio nuts (Pistachia vera L.) from Turkiye. Gida / The Journal of Food. 28(4), 395-400.
Gonzalez RC, Woods RE (2002) Digital image processing, 2nd Edition, Pearson Education, Inc., Upper Saddle River, New Jersey, 797.
Harris LJ (Editor) (2013) improving the safety and quality of nuts, Woodhead publishing limited, pp.440.
Hsu MH, Mannapperuma JD, Singh RP (1991) Physical and thermal properties of pistachios. Journal of Agricultural Engineering Research. 49, 311-321.
Institute of Standards & Industrial Research of Iran (1999), Number 4920, Pistachio: test methods.
Karimi HR (2015) Nut fruits (pistachio, almond,walnut, filbert, pecan and cheastnut), Jahad Daneshgahi publication, Mashhad, Iran, 150
Kashaninejad K, Mortazavi A, Safekordi A, Tabil LG (2005) Some physical properties of pistachio (Pistachio vera L.) nut and its kernel. Journal of Food Engineering. 72(1), 30–38.
Kashaninejad M, Tabil LG (2011) Pistachio (Pistacia vera L.), in Integrated View of Postharvest Biology and Technology of Tropical and Subtropical Fruits, Ed by E. Yahia. Woodhead Publishing, ISBN 978-0-85709-090-4. pp. 1-30.
Maghsoudi H, Khoshtaghaza MH, Minaei S (2010) Selected geometric characteristics, density and mechanical properties of unsplit pistachio nut. International Journal of Food Properties. 13, 394–403.
Maghsudi Sh (2010) Pistachio (agricultural, industry, nutrition and treatment). Iran Agricultural Science Publishing Inc., Iran.pp. 134.
Mohamadi-Moghaddam T, Razavi SMA (2019) Application of artificial neural networks (ANN) and image processing for prediction of the geometrical properties of roasted pistachio nuts and kernels. Journal of Nuts. 10(1), 79-93.
Nazari Galedar M, Tabatabaeefar A, Jafari A, Sharifi A, Mohtasebi SS, Fadaei H (2011) Moisture Dependent Geometric and Mechanical Properties of Wild Pistachio (Pistacia vera L.) Nut and Kernel. International Journal of Food Properties. 13, 1323–1338.
Ozdemir M (2001) Mathematical analysis of color changes and chemical parameters of roasted hazelnuts, Ph.D Thesis, Turkey.
Polat R, Aydin C, Erol Ak B (2007) Some physical and mechanical properties of pistachio nut. Bulgarian Journal of Agricultural Science. 13, 237-246.
Razavi SMA, Edalatian MA (2012) Effect of moisture contents and compression axes on physical and mechanical properties of pistachio kernel.International Journal of Food Properties. 15 (3), 507-517.
Razavi SMA, Emadzadeh B, Rafe A, Mohammad Amini A (2007) The physical properties of pistachio nut and its kernel as a function of moisture content and variety: Part I. Geometrical properties. Journal of Food Engineering. 81, 209–217.
Razavi SMA, Mazaherinasab M, Nickfar F, Sanaeefard H (2008) Physical properties and image analysis of wild pistachio nut (Baneh). Iranian Food Science &Technology Research Journal. 3(2), 61-71.
Razavi SMA, Rafe A, Mohammadi- Moghaddam T, Mohammad Amini A (2007) Physical properties of pistachio nut and its kernel as a function of moisture content and variety. Part II. Gravimetrical properties. Journal of Food Engineering. 81, 218-225.
Yazdani N, Osanloo B, Lotfi M, Asefpour Vakilian K (2017) Application of image processing for investigating the effect of nanozeolite and nanosponge on flesh firmness of cold stored cantaloupe. International Journal of Horticultural Science and Technology. 4(1), 127-133.