Volume 18, Issue 116 (2021)                   FSCT 2021, 18(116): 293-303 | Back to browse issues page


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Kiani H, BEHESHTI B, Borghei A M, Rahmati M H. Detection of olive oil contaminated with heavy metals using a three-electrode system based on the cyclic voltammetry. FSCT. 2021; 18 (116) :293-303
URL: http://fsct.modares.ac.ir/article-7-50451-en.html
1- Ph.D. student, Department of Biosystems Engineering, Faculty of Agricultural Sciences and Food Industry, Science and Research Branch, Islamic Azad University, Tehran, Iran.
2- Assistant Professor, Department of Biosystems Engineering, Faculty of Agricultural Sciences and Food Industry, Science and Research Branch, Islamic Azad University, Tehran, Iran , beheshti-b@srbiau.ac.ir
3- Professor, Department of Biosystems Engineering, Faculty of Agricultural Sciences and Food Industry, Science and Research Branch, Islamic Azad University, Tehran, Iran
4- Associate Professor, Department of Biosystem Mechanical Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
Abstract:   (674 Views)
Three electrode system simulates the human tongue taste system and can be used to assess the quality of food. The sense of taste is one of the five senses and tongue recognizes certain molecules. In recent years, three electrode system with an array of electrodes has been used to identify various molecules. In this research, a three electrode system is used based on voltammetric methods with three graphite electrodes (Pencil Graphite (PG)), Screen Printed (SP) and Glassy Carbon (GC) to identify heavy metals (cadmium , Lead, tin and nickel) in olive oil. Heavy metals are added to the edible oil in three concentrations of 0.05, 0.1 and 0.25 ppm and then the output of the device is classified by chemometric method. According to PCA results, the PG electrode contains 96% of the variance between the data in olive edible oils. Also, SP electrode contains 91% and GC contains 100% of the variance between the data in olive oil. The SVM method showed a high ability to classify heavy metals in edible oils. Also, The PLS method was also able to predict 99% of the data in olive oil for all electrodes. Finally, according to the results, it can be said that the built-in three electrode system has a high accuracy in identifying heavy metals in edible oils.
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Article Type: Original Research | Subject: Food quality control
Received: 2021/02/24 | Accepted: 2021/05/2 | Published: 2021/10/2

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