Detection of Metallic and Non-Metallic Inclusions in Food Products by Electrometric Method

One of the most important indicators of the quality and safety of food products is the absence of extraneous inclusions. Extraneous inclusions are objects that are not typical for this food product and are invisible to the unaided eye. These include various packaging materials (plastic, wood, ceramics and glass), as well as foreign materials that can get into the food product due to violations of technological processes or due to improper operation of equipment (bone fragments in meat, leaves and stems in fruit, insects, etc.). Analysis of literature sources shows that promising means for detecting extraneous inclusions in food products are such types of control that, without changing the quality, parameters and characteristics of these products, allow to detect extraneous inclusions for indirect, secondary signs. The aim of the current study was to develop a method for determining the main parameters for detecting extraneous metallic and non-metallic inclusions in food products (in mincemeat, in particular) based on the use of electromagnetic methods, signal selection and automatic removal of particles from the product in a continuous production process. To study the possibility of using the electric contact method for detecting foreign particles, a detector sensor was estimated. The value of the signal from an extraneous particle was computed by the secondary field method, which was implemented in the device for detection. Based on experimental data, a circular phase diagram of secondary fields of local bodies was constructed, which shows that metals and non-metals have signal phases that differ both from controlled food products and between themselves. It follows that it is possible to use the phase selectivity method to select signals from metallic and non-metallic particles found in food products. The developed detector consists of sensors and an analyzer of extraneous inclusions. The sensor consists of 22 sensitive elements. Each of the sensors is included in the bridge measuring circuit. The research made it possible to develop an automatic device for removing detected particles without stopping the technological process in the production of spam, an experimental sample of which was tested in the production conditions of a meat-processing plant.

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