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Methods for determining color characteristics of vegetable raw materials. A review

Journal: Food systems (Vol.4, No. 4)

Publication Date:

Authors : ;

Page : 230-238

Keywords : color; methods for determining color; plant raw materials; quality; computer vision;

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Food product quality defines a complex of food product properties such size, shape, texture, color and others, and determines acceptability of these products for consumers. It is possible to detect defects in plant raw materials by color and classify them by color characteristics, texture, shape, a degree of maturity and so on. Currently, the work on modernization of color control systems has been carried out for rapid and objective measuring information about color of plant raw materials during their harvesting, processing and storage. The aim of the work is to analyze existing methods for determining color characteristics of plant raw materials described in foreign and domestic studies. Also, this paper presents the results of the experimental studies that describe the practical use of methods for measuring food product color. At present, the following methods for determining color characteristics by the sensor analysis principle are used: sensory, spectrophotometric and photometric. These methods have several disadvantages. Therefore, computer vision has found wide application as an automated method for food control. It is distinguished by high confidence and reliability in the process of determining freshness, safety, a degree of maturity and other parameters of plant raw materials that are heterogeneous in terms of the abovementioned indicators. The computer vision method is realized in the following systems: conventional, hyperspectral and multispectral. Each subsequent system is a component of the preceding one. Materials presented in the paper allow making a conclusion about the effectiveness of the computer vision systems with the aim of automatic sorting and determining quality of plant raw materials in the food industry.

Last modified: 2022-01-17 16:13:32